Stakeholder influence on teaming and absorptive capacity in innovation networks

Through technological developments, innovation increasingly occurs within a network of organizations such as Industry 4.0 fieldlabs. As a result, collaboration between different companies and institutions with different interests needs to take place. Three Dutch smart industry fieldlabs were analysed to study how these collaborative relationships are being established and what their impact is on the absorptive capacity of the network in question. Contrary to what was expected, we found that stakeholders hardly exercised power. Also, a high level of psychological safety was found in the network, which positively affects collaboration. Furthermore, collaborative elements—such as open conversation, collaborating, experimenting and reflecting—are important factors affecting the absorptive capacity in the fieldlabs examined. The article concludes with several practical implications on how to stimulate innovation capability

A Neural Circuit Arbitrates between Persistence and Withdrawal in Hungry Drosophila

In pursuit of food, hungry animals mobilize significant energy resources and overcome exhaustion and fear. How need and motivation control the decision to continue or change behavior is not understood. Using a single fly treadmill, we show that hungry flies persistently track a food odor and increase their effort over repeated trials in the absence of reward suggesting that need dominates negative experience. We further show that odor tracking is regulated by two mushroom body output neurons (MBONs) connecting the MB to the lateral horn. These MBONs, together with dopaminergic neurons and Dop1R2 signaling, control behavioral persistence. Conversely, an octopaminergic neuron, VPM4, which directly innervates one of the MBONs, acts as a brake on odor tracking by connecting feeding and olfaction. Together, our data suggest a function for the MB in internal state-dependent expression of behavior that can be suppressed by external inputs conveying a competing behavioral drive

Agave negatively regulates YAP and TAZ transcriptionally and post-translationally in osteosarcoma cell lines

Osteosarcoma (OS) is the most aggressive type of primary solid tumor that develops in bone. Whilst conventional chemotherapy can improve survival rates, the outcome for patients with metastatic or recurrent OS remains poor, so novel treatment agents and strategies are required. Research into new anticancer therapies has paved the way for the utilisation of natural compounds as they are typically less expensive and less toxic compared to conventional chemotherapeutics. Previously published works indicate that Agave exhibits anticancer properties, however potential molecular mechanisms remain poorly understood. In the present study, we investigate the anticancer effects of Agave leaf extract in OS cells suggesting that Agave inhibits cell viability, colony formation, and cell migration, and can induce apoptosis in OS cell lines. Moreover, Agave sensitizes OS cells to cisplatin (CDDP) and radiation, to overcome chemo- and radio-resistance. We demonstrate that Agave extract induces a marked decrease of Yes Associated Protein (YAP) and Tafazzin (TAZ) mRNA and protein expression upon treatment. We propose an initial mechanism of action in which Agave induces YAP/TAZ protein degradation, followed by a secondary event whereby Agave inhibits YAP/TAZ transcription, effectively deregulating the Nuclear Factor kappa B (NF-\u3baB) p65:p50 heterodimers responsible for transcriptional induction of YAP and TAZ

Tackling the "Galacticos" effect: team familiarity and the performance of star-studded projects

Findings on the performance implications of assembling star-studded teams have remained rather mixed. We elaborate on the theoretical reasons for current inconclusive findings and delineate more precise boundary conditions for studying the relationship between stars and project-level performance. Specifically, we argue that lack of scholarly attention to team familiarity may account for empirical results’ observed inconsistency. Our findings show that a history of past collaboration reduces the downsides of having too many stars within the same team. Previous interactions enhance coordination efforts by reducing conflicts among team members. We situate the analysis within the context of the Hollywood film industry over the period 1992–2004. The theoretical implications of the results are discussed

Iso-osmotic regulation of nitrate accumulation in lettuce (Lactuca sativa L.)

Concerns about possible health hazards arising from human consumption of lettuce and other edible vegetable crops with high concentrations of nitrate have generated demands for a greater understanding of processes involved in its uptake and accumulation in order to devise more sustainable strategies for its control. This paper evaluates a proposed iso-osmotic mechanism for the regulation of nitrate accumulation in lettuce (Lactuca sativa L.) heads. This mechanism assumes that changes in the concentrations of nitrate and all other endogenous osmotica (including anions, cations and neutral solutes) are continually adjusted in tandem to minimise differences in osmotic potential of the shoot sap during growth, with these changes occurring independently of any variations in external water potential. The hypothesis was tested using data from six new experiments, each with a single unique treatment comprising a separate combination of light intensity, N source (nitrate with or without ammonium) and nitrate concentration carried out hydroponically in a glasshouse using a butterhead lettuce variety. Repeat measurements of plant weights and estimates of all of the main soluble constituents (nitrate, potassium, calcium, magnesium, organic anions, chloride, phosphate, sulphate and soluble carbohydrates) in the shoot sap were made at intervals from about 2 weeks after transplanting until commercial maturity, and the data used to calculate changes in average osmotic potential in the shoot. Results showed that nitrate concentrations in the sap increased when average light levels were reduced by between 30 and 49 % and (to a lesser extent) when nitrate was supplied at a supra-optimal concentration, and declined with partial replacement of nitrate by ammonium in the external nutrient supply. The associated changes in the proportions of other endogenous osmotica, in combination with the adjustment of shoot water content, maintained the total solute concentrations in shoot sap approximately constant and minimised differences in osmotic potential between treatments at each sampling date. There was, however, a gradual increase in osmotic potential (ie a decline in total solute concentration) over time largely caused by increases in shoot water content associated with the physiological and morphological development of the plants. Regression analysis using normalised data (to correct for these time trends) showed that the results were consistent with a 1:1 exchange between the concentrations of nitrate and the sum of all other endogenous osmotica throughout growth, providing evidence that an iso-osmotic mechanism (incorporating both concentration and volume regulation) was involved in controlling nitrate concentrations in the shoot

Use of Advanced Flexible Modeling Approaches for Survival Extrapolation from Early Follow-up Data in two Nivolumab Trials in Advanced NSCLC with Extended Follow-up

Objectives: Immuno-oncology (IO) therapies are often associated with delayed responses that are deep and durable, manifesting as long-term survival benefits in patients with metastatic cancer. Complex hazard functions arising from IO treatments may limit the accuracy of extrapolations from standard parametric models (SPMs). We evaluated the ability of flexible parametric models (FPMs) to improve survival extrapolations using data from 2 trials involving patients with non–small-cell lung cancer (NSCLC). Methods: Our analyses used consecutive database locks (DBLs) at 2-, 3-, and 5-y minimum follow-up from trials evaluating nivolumab versus docetaxel in patients with pretreated metastatic squamous (CheckMate-017) and nonsquamous (CheckMate-057) NSCLC. For each DBL, SPMs, as well as 3 FPMs—landmark response models (LRMs), mixture cure models (MCMs), and Bayesian multiparameter evidence synthesis (B-MPES)—were estimated on nivolumab overall survival (OS). The performance of each parametric model was assessed by comparing milestone restricted mean survival times (RMSTs) and survival probabilities with results obtained from externally validated SPMs. Results: For the 2- and 3-y DBLs of both trials, all models tended to underestimate 5-y OS. Predictions from nonvalidated SPMs fitted to the 2-y DBLs were highly unreliable, whereas extrapolations from FPMs were much more consistent between models fitted to successive DBLs. For CheckMate-017, in which an apparent survival plateau emerges in the 3-y DBL, MCMs fitted to this DBL estimated 5-y OS most accurately (11.6% v. 12.3% observed), and long-term predictions were similar to those from the 5-y validated SPM (20-y RMST: 30.2 v. 30.5 mo). For CheckMate-057, where there is no clear evidence of a survival plateau in the early DBLs, only B-MPES was able to accurately predict 5-y OS (14.1% v. 14.0% observed [3-y DBL]). Conclusions: We demonstrate that the use of FPMs for modeling OS in NSCLC patients from early follow-up data can yield accurate estimates for RMST observed with longer follow-up and provide similar long-term extrapolations to externally validated SPMs based on later data cuts. B-MPES generated reasonable predictions even when fitted to the 2-y DBLs of the studies, whereas MCMs were more reliant on longer-term data to estimate a plateau and therefore performed better from 3 y. Generally, LRM extrapolations were less reliable than those from alternative FPMs and validated SPMs but remained superior to nonvalidated SPMs. Our work demonstrates the potential benefits of using advanced parametric models that incorporate external data sources, such as B-MPES and MCMs, to allow for accurate evaluation of treatment clinical and cost-effectiveness from trial data with limited follow-up. Flexible advanced parametric modeling methods can provide improved survival extrapolations for immuno-oncology cost-effectiveness in health technology assessments from early clinical trial data that better anticipate extended follow-up. Advantages include leveraging additional observable trial data, the systematic integration of external data, and more detailed modeling of underlying processes. Bayesian multiparameter evidence synthesis performed particularly well, with well-matched external data. Mixture cure models also performed well but may require relatively longer follow-up to identify an emergent plateau, depending on the specific setting. Landmark response models offered marginal benefits in this scenario and may require greater numbers in each response group and/or increased follow-up to support improved extrapolation within each subgroup

A Transcriptomic Signature of Mouse Liver Progenitor Cells

Liver progenitor cells (LPCs) can proliferate extensively, are able to differentiate into hepatocytes and cholangiocytes, and contribute to liver regeneration. The presence of LPCs, however, often accompanies liver disease and hepatocellular carcinoma (HCC), indicating that they may be a cancer stem cell. Understanding LPC biology and establishing a sensitive, rapid, and reliable method to detect their presence in the liver will assist diagnosis and facilitate monitoring of treatment outcomes in patients with liver pathologies. A transcriptomic meta-analysis of over 400 microarrays was undertaken to compare LPC lines against datasets of muscle and embryonic stem cell lines, embryonic and developed liver (DL), and HCC. Three gene clusters distinguishing LPCs from other liver cell types were identified. Pathways overrepresented in these clusters denote the proliferative nature of LPCs and their association with HCC. Our analysis also revealed 26 novel markers, LPC markers, including Mcm2 and Ltbp3, and eight known LPC markers, including M2pk and Ncam. These markers specified the presence of LPCs in pathological liver tissue by qPCR and correlated with LPC abundance determined using immunohistochemistry. These results showcase the value of global transcript profiling to identify pathways and markers that may be used to detect LPCs in injured or diseased liver

Interchange Slip-Running Reconnection and Sweeping SEP Beams

We present a new model to explain how particles (solar energetic particles; SEPs), accelerated at a reconnection site that is not magnetically connected to the Earth, could eventually propagate along the well-connected open flux tube. Our model is based on the results of a low-beta resistive magnetohydrodynamics simulation of a three-dimensional line-tied and initially current-free bipole, that is embedded in a non-uniform open potential field. The topology of this configuration is that of an asymmetric coronal null-point, with a closed fan surface and an open outer spine. When driven by slow photospheric shearing motions, field lines, initially fully anchored below the fan dome, reconnect at the null point, and jump to the open magnetic domain. This is the standard interchange mode as sketched and calculated in 2D. The key result in 3D is that, reconnected open field lines located in the vicinity of the outer spine, keep reconnecting continuously, across an open quasi-separatrix layer, as previously identified for non-open-null-point reconnection. The apparent slipping motion of these field lines leads to form an extended narrow magnetic flux tube at high altitude. Because of the slip-running reconnection, we conjecture that if energetic particles would be traveling through, or be accelerated inside, the diffusion region, they would be successively injected along continuously reconnecting field lines that are connected farther and farther from the spine. At the scale of the full Sun, owing to the super-radial expansion of field lines below 3 solar radii, such energetic particles could easily be injected in field lines slipping over significant distances, and could eventually reach the distant flux tube that is well-connected to the Earth

GAMA: towards a physical understanding of galaxy formation

The Galaxy And Mass Assembly (GAMA) project is the latest in a tradition of large galaxy redshift surveys, and is now underway on the 3.9m Anglo-Australian Telescope at Siding Spring Observatory. GAMA is designed to map extragalactic structures on scales of 1kpc - 1Mpc in complete detail to a redshift of z~0.2, and to trace the distribution of luminous galaxies out to z~0.5. The principal science aim is to test the standard hierarchical structure formation paradigm of Cold Dark Matter (CDM) on scales of galaxy groups, pairs, discs, bulges and bars. We will measure (1) the Dark Matter Halo Mass Function (as inferred from galaxy group velocity dispersions); (2) baryonic processes, such as star formation and galaxy formation efficiency (as derived from Galaxy Stellar Mass Functions); and (3) the evolution of galaxy merger rates (via galaxy close pairs and galaxy asymmetries). Additionally, GAMA will form the central part of a new galaxy database, which aims to contain 275,000 galaxies with multi-wavelength coverage from coordinated observations with the latest international ground- and space-based facilities: GALEX, VST, VISTA, WISE, HERSCHEL, GMRT and ASKAP. Together, these data will provide increased depth (over 2 magnitudes), doubled spatial resolution (0.7"), and significantly extended wavelength coverage (UV through Far-IR to radio) over the main SDSS spectroscopic survey for five regions, each of around 50 deg^2. This database will permit detailed investigations of the structural, chemical, and dynamical properties of all galaxy types, across all environments, and over a 5 billion year timeline.Comment: GAMA overview which appeared in the October 2009 issue of Astronomy & Geophysics, ref: Astron.Geophys. 50 (2009) 5.1