Hydra morphogenesis as phase-transition dynamics

We utilize whole-body Hydra regeneration from a small tissue segment to develop a physics framework for animal morphogenesis. Introducing experimental controls over this process, an external electric field and a drug that blocks gap junctions, allows us to characterize the essential step in the morphological transition - from a spherical shape to an elongated spheroid. We find that spatial fluctuations of the Ca2+ distribution in the Hydra's tissue drive this transition and construct a field-theoretic model that explains the morphological transition as a first-order-like phase transition resulting from the coupling of the Ca2+ field and the tissue's local curvature. Various predictions of this model are verified experimentally.Comment: 8 pages, 4 figures, Supplementary Materia

Universal Calcium fluctuations in Hydra morphogenesis

Morphogenesis in development involves significant morphological transitions toward the emerging body plan of a mature animal. Understanding how the collective physical processes drive robust morphological patterning requires the characterization of the underlying relevant fields. Calcium (Ca2+) is known to be such a field. Here we show that the Ca2+ spatial fluctuations, in whole-body Hydra regeneration, exhibit universal properties captured by a field-theoretic model describing fluctuations in a tilted double-well potential. We utilize an external electric field and Heptanol, a drug blocking gap junctions, as two separate controls affecting the Ca2+ activity and pausing the regeneration process in a reversible way. Subjecting the Hydra tissue to an electric field increases the calcium activity and its spatial correlations, while applying Heptanol inhibits the activity and weakens the spatial correlations. Statistical characteristics of the Ca2+ spatial fluctuations, i.e., the coefficient of variation and the skewness, exhibit universal shape distributions across tissue samples and conditions, demonstrating the existence of global constraints over this field. Our analysis shows that the Hydra's tissue resides near the onset of bistability. The controls modulate the dynamics near that onset in a way that preserves the tissue's ability to regenerate, which is reflected by the aforementioned universality

Single-cell protein dynamics reproduce universal fluctuations in cell populations

Protein variability in single cells has been studied extensively in populations, but little is known about temporal protein fluctuations in a single cell over extended times. We present here traces of protein copy number measured in individual bacteria over multiple generations and investigate their statistical properties, comparing them to previously measured population snapshots. We find that temporal fluctuations in individual traces exhibit the same universal features as those previously observed in populations. Scaled fluctuations around the mean of each trace exhibit the same universal distribution shape as found in populations measured under a wide range of conditions and in two distinct microorganisms. Additionally, the mean and variance of the traces over time obey the same quadratic relation. Analyzing the temporal features of the protein traces in individual cells, reveals that within a cell cycle protein content increases as an exponential function with a rate that varies from cycle to cycle. This leads to a compact description of the protein trace as a 3-variable stochastic process - the exponential rate, the cell-cycle duration and the value at the cycle start - sampled once each cell cycle. This compact description is sufficient to preserve the universal statistical properties of the protein fluctuations, namely, the protein distribution shape and the quadratic relationship between variance and mean. Our results show that the protein distribution shape is insensitive to sub-cycle intracellular microscopic details and reflects global cellular properties that fluctuate between generations

On the Precarious Path of Reverse Neuro-Engineering

In this perspective we provide an example for the limits of reverse engineering in neuroscience. We demonstrate that application of reverse engineering to the study of the design principle of a functional neuro-system with a known mechanism, may result in a perfectly valid but wrong induction of the system's design principle. If in the very simple setup we bring here (static environment, primitive task and practically unlimited access to every piece of relevant information), it is difficult to induce a design principle, what are our chances of exposing biological design principles when more realistic conditions are examined? Implications to the way we do Biology are discussed

Conceptualising Gamification Risks to Teamwork within Enterprise

Gamification in businesses refers to the use of technology-assisted solutions to boost or change staff attitude, perception and behaviour, in relation to certain business goals and tasks, individually or collectively. Previous research indicated that gamification techniques can introduce risks to the business environment, and not only fail to make a positive change, but also raise concerns in relation to ethics, quality of work, and well-being at a workplace. Although the problem is already recognised in principle, there is still a need to clarify and concretise those risks, their factors and their relation to the gamification dynamics and mechanics. To address this, we conducted multi-staged empirical research, including two months’ observation and interview study, in two large-scale businesses using gamification in their workplace. In this paper, we focus on gamification risks related to teamwork within the enterprise. We outline various risk mitigation strategies and map them to primary types of gamification risks. By accomplishing such conceptualisation, we pave the way towards methods to model, detect and predict gamification risks on teamwork and recommend and design practices and strategies to tackle them

Collective Dynamics of Gene Expression in Cell Populations

The phenotypic state of the cell is commonly thought to be determined by the set of expressed genes. However, given the apparent complexity of genetic networks, it remains open what processes stabilize a particular phenotypic state. Moreover, it is not clear how unique is the mapping between the vector of expressed genes and the cell's phenotypic state. To gain insight on these issues, we study here the expression dynamics of metabolically essential genes in twin cell populations. We show that two yeast cell populations derived from a single steady-state mother population and exhibiting a similar growth phenotype in response to an environmental challenge, displayed diverse expression patterns of essential genes. The observed diversity in the mean expression between populations could not result from stochastic cell-to-cell variability, which would be averaged out in our large cell populations. Remarkably, within a population, sets of expressed genes exhibited coherent dynamics over many generations. Thus, the emerging gene expression patterns resulted from collective population dynamics. It suggests that in a wide range of biological contexts, gene expression reflects a self-organization process coupled to population-environment dynamics

Energy-efficient quantum frequency estimation

The problem of estimating the frequency of a two-level atom in a noisy environment is studied. Our interest is to minimise both the energetic cost of the protocol and the statistical uncertainty of the estimate. In particular, we prepare a probe in a `GHZ-diagonal' state by means of a sequence of qubit gates applied on an ensemble of n atoms in thermal equilibrium. Noise is introduced via a phenomenological time-nonlocal quantum master equation, which gives rise to a phase-covariant dissipative dynamics. After an interval of free evolution, the n-atom probe is globally measured at an interrogation time chosen to minimise the error bars of the final estimate. We model explicitly a measurement scheme which becomes optimal in a suitable parameter range, and are thus able to calculate the total energetic expenditure of the protocol. Interestingly, we observe that scaling up our multipartite entangled probes offers no precision enhancement when the total available energy E is limited. This is at stark contrast with standard frequency estimation, where larger probes---more sensitive but also more `expensive' to prepare---are always preferred. Replacing E by the resource that places the most stringent limitation on each specific experimental setup, would thus help to formulate more realistic metrological prescriptions

Elliptic flow of charged particles in Pb-Pb collisions at 2.76 TeV

We report the first measurement of charged particle elliptic flow in Pb-Pb collisions at 2.76 TeV with the ALICE detector at the CERN Large Hadron Collider. The measurement is performed in the central pseudorapidity region (|$\eta$|<0.8) and transverse momentum range 0.2< $p_{\rm T}$< 5.0 GeV/$c$. The elliptic flow signal v$_2$, measured using the 4-particle correlation method, averaged over transverse momentum and pseudorapidity is 0.087 $\pm$ 0.002 (stat) $\pm$ 0.004 (syst) in the 40-50% centrality class. The differential elliptic flow v$_2(p_{\rm T})$ reaches a maximum of 0.2 near $p_{\rm T}$ = 3 GeV/$c$. Compared to RHIC Au-Au collisions at 200 GeV, the elliptic flow increases by about 30%. Some hydrodynamic model predictions which include viscous corrections are in agreement with the observed increase.Comment: 10 pages, 4 captioned figures, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/389

Critical Role of VCP/p97 in the Pathogenesis and Progression of Non-Small Cell Lung Carcinoma

Valosin-containing protein (VCP)/p97 is an AAA ATPase molecular chaperone that regulates vital cellular functions and protein-processing. A recent study indicated that VCP expression levels are correlated with prognosis and progression of non-small cell lung carcinoma (NSCLC). We not only verified these findings but also identified the specific role of VCP in NSCLC pathogenesis and progression.Our results show that VCP is significantly overexpressed in non-small cell lung carcinoma (NSCLC) as compared to normal tissues and cell lines (p<0.001). Moreover, we observed the corresponding accumulation of ubiquitinated-proteins in NSCLC cell lines and tissues as compared to the normal controls. VCP inhibition by si/shRNA or small-molecule (Eeyarestatin I, EerI) significantly (p<0.05, p<0.00007) suppressed H1299 proliferation and migration but induced (p<0.00001) apoptosis. Cell cycle analysis by flow cytometry verified this data and shows that VCP inhibition significantly (p<0.001, p<0.003) induced cell cycle arrest in the G0/G1 phases. We also found that VCP directly regulates p53 and NFκB protein levels as a potential mechanism to control tumor cell proliferation and progression. Finally, we evaluated the therapeutic potential of VCP inhibition and observed significantly reduced NSCLC tumor growth in both in vitro and xenograft murine (athymic-nude) models after EerI treatment (p<0.05).Thus, targeting VCP in NSCLC may provide a novel strategy to restore p53 and NFκB levels and ameliorate the growth and tumorigenicity, leading to improved clinical outcomes