Induced innovation in energy technologies and systems: a review of evidence and potential implications for CO2 mitigation

We conduct a systematic, interdisciplinary review of empirical literature assessing evidence on induced innovation in energy and related technologies. We explore links between demand-drivers (both market-wide and targeted); indicators of innovation (principally, patents); and outcomes (cost reduction, efficiency, and multi-sector/macro consequences). We build on existing reviews in different fields and assess over 200 papers containing original data analysis. Papers linking drivers to patents, and indicators of cumulative capacity to cost reductions (experience curves), dominate the literature. The former does not directly link patents to outcomes; the latter does not directly test for the causal impact of on cost reductions). Diverse other literatures provide additional evidence concerning the links between deployment, innovation activities, and outcomes. We derive three main conclusions. (1) Demand-pull forces enhance patenting; econometric studies find positive impacts in industry, electricity and transport sectors in all but a few specific cases. This applies to all drivers - general energy prices, carbon prices, and targeted interventions that build markets. (2) Technology costs decline with cumulative investment for almost every technology studied across all time periods, when controlled for other factors. Numerous lines of evidence point to dominant causality from at-scale deployment (prior to self-sustaining diffusion) to cost reduction in this relationship. (3) Overall Innovation is cumulative, multi-faceted, and self-reinforcing in its direction (path-dependent). We conclude with brief observations on implications for modeling and policy. In interpreting these results, we suggest distinguishing the economics of active deployment, from more passive diffusion processes, and draw the following implications. There is a role for policy diversity and experimentation, with evaluation of potential gains from innovation in the broadest sense. Consequently, endogenising innovation in large-scale models is important for deriving policy-relevant conclusions. Finally, seeking to relate quantitative economic evaluation to the qualitative socio-technical transitions literatures could be a fruitful area for future research

Two Years Later: Journals Are Not Yet Enforcing the ARRIVE Guidelines on Reporting Standards for Pre-Clinical Animal Studies

There is growing concern that poor experimental design and lack of transparent reporting contribute to the frequent failure of pre-clinical animal studies to translate into treatments for human disease. In 2010, the Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines were introduced to help improve reporting standards. They were published in PLOS Biology and endorsed by funding agencies and publishers and their journals, including PLOS, Nature research journals, and other top-tier journals. Yet our analysis of papers published in PLOS and Nature journals indicates that there has been very little improvement in reporting standards since then. This suggests that authors, referees, and editors generally are ignoring guidelines, and the editorial endorsement is yet to be effectively implemented

Adoptive transfer of dendritic cells expressing CD11c reduces the immunological response associated with experimental colitis in BALB/c mice.

Introduction In addition to conventional therapies, several new strategies have been proposed for modulating autoimmune diseases, including the adoptive transfer of immunological cells. In this context, dendritic cells (DCs) appear to be one of the most promising treatments for autoimmune disorders. The present study aimed to evaluate the effects of adoptive transfer of DCs obtained from both na?ve and ovalbumin (OVA)-tolerant mice on the severity of TNBS induced colitis and analyze the eventual protective mechanisms. Methods and results To induce oral tolerance, BALB/c mice were fed 4mg/mL OVA solution for seven consecutive days. Spleen DCs were isolated from tolerant (tDC) and na?ve (nDC) mice, and then adoptively transferred to syngeneic mice. Three days later, colitis was induced in DC treated mice by intrarectal instillation of 100?g2,4,6-trinitrobenzenesulfonic acid (TNBS) dissolved in 50% ethanol. Control subjects received only intrarectal instillation of either TNBS solution or a vehicle. Five days later, mice from all groups were euthanized and examined for physiological and immunological parameters. Regarding the phenotype, we observed that the frequencies of CD11+ MHC II+ and CD11+ MHCII+ CD86+ cells were significantly lower in DCs isolated from tolerant mice than in those from naive mice. However, pretreatment with both types of DCs was able to significantly reduce clinical signs of colitis such as diarrhea, rectal prolapse, bleeding, and cachexia, although only treatment with tDCs was able to prevent weight loss from instillation of TNBS. In vitro proliferation of spleen cells from mice treated with either type of DCs was significantly lower than that observed in splenic cell cultures of na?ve mice. Although no significant difference was observed in the frequencies of Treg cells in the experimental groups, the frequency of Th17+CD4+cellsand the secretion of IL-17 were more reduced in the cultures of spleen cells from mice treated with either type of DCs. The levels of IL-9 and IFN-? were lower in supernatants of cells from mice treated with nDCs. Conclusion The results allow us to conclude that the adoptive transfer of cells expressing CD11c is able to reduce the clinical and immunological signs of drug-induced colitis. Adoptive transfer of CD11c+DC isolated from both naive and tolerant mice altered the proliferative and T cell responses. To the best of our knowledge, there is no previously published data showing the protective effects of DCs from na?ve or tolerant mice in the treatment of colitis

Reducing uncertainty in health-care resource allocation

A key task for health policymakers is to optimise the outcome of health care interventions. The pricing of a new generation of cancer drugs, in combination with limited health care resources, has highlighted the need for improved methodology to estimate outcomes of different treatment options. Here we introduce new general methodology, which for the first time employs continuous hazard functions for analysis of survival data. Access to continuous hazard functions allows more precise estimations of survival outcomes for different treatment options. We illustrate the methodology by calculating outcomes for adjuvant treatment of gastrointestinal stromal tumours with imatinib mesylate, which selectively inhibits the activity of a cancer-causing enzyme and is a hallmark representative for the new generation of cancer drugs. The calculations reveal that optimal drug pricing can generate all win situations that improve drug availability to patients, make the most of public expenditure on drugs and increase pharmaceutical company gross profits. The use of continuous hazard functions for analysis of survival data may reduce uncertainty in health care resource allocation, and the methodology can be used for drug price negotiations and to investigate health care intervention thresholds. Health policy makers, pharmaceutical industry, reimbursement authorities and insurance companies, as well as clinicians and patient organisations, should find the methodology useful

Why Is the Correlation between Gene Importance and Gene Evolutionary Rate So Weak?

One of the few commonly believed principles of molecular evolution is that functionally more important genes (or DNA sequences) evolve more slowly than less important ones. This principle is widely used by molecular biologists in daily practice. However, recent genomic analysis of a diverse array of organisms found only weak, negative correlations between the evolutionary rate of a gene and its functional importance, typically measured under a single benign lab condition. A frequently suggested cause of the above finding is that gene importance determined in the lab differs from that in an organism's natural environment. Here, we test this hypothesis in yeast using gene importance values experimentally determined in 418 lab conditions or computationally predicted for 10,000 nutritional conditions. In no single condition or combination of conditions did we find a much stronger negative correlation, which is explainable by our subsequent finding that always-essential (enzyme) genes do not evolve significantly more slowly than sometimes-essential or always-nonessential ones. Furthermore, we verified that functional density, approximated by the fraction of amino acid sites within protein domains, is uncorrelated with gene importance. Thus, neither the lab-nature mismatch nor a potentially biased among-gene distribution of functional density explains the observed weakness of the correlation between gene importance and evolutionary rate. We conclude that the weakness is factual, rather than artifactual. In addition to being weakened by population genetic reasons, the correlation is likely to have been further weakened by the presence of multiple nontrivial rate determinants that are independent from gene importance. These findings notwithstanding, we show that the principle of slower evolution of more important genes does have some predictive power when genes with vastly different evolutionary rates are compared, explaining why the principle can be practically useful despite the weakness of the correlation

Exploring the growth of correlations in a quasi one-dimensional trapped Bose gas

Phase correlations, density fluctuations and three-body loss rates are relevant for many experiments in quasi one-dimensional geometries. Extended mean-field theory is used to evaluate correlation functions up to third order for a quasi one-dimensional trapped Bose gas at zero and finite temperature. At zero temperature and in the homogeneous limit, we also study the transition from the weakly correlated Gross-Pitaevskii regime to the strongly correlated Tonks-Girardeau regime analytically. We compare our results with the exact Lieb-Liniger solution for the homogeneous case and find good agreement up to the cross-over regime.Comment: 36 pages, 21 color pdf/jpeg figures, submitted to NJP, corrected reference

Regular Patterns for Proteome-Wide Distribution of Protein Abundance across Species

A proteome of the bio-entity, including cell, tissue, organ, and organism, consists of proteins of diverse abundance. The principle that determines the abundance of different proteins in a proteome is of fundamental significance for an understanding of the building blocks of the bio-entity. Here, we report three regular patterns in the proteome-wide distribution of protein abundance across species such as human, mouse, fly, worm, yeast, and bacteria: in most cases, protein abundance is positively correlated with the protein's origination time or sequence conservation during evolution; it is negatively correlated with the protein's domain number and positively correlated with domain coverage in protein structure, and the correlations became stronger during the course of evolution; protein abundance can be further stratified by the function of the protein, whereby proteins that act on material conversion and transportation (mass category) are more abundant than those that act on information modulation (information category). Thus, protein abundance is intrinsically related to the protein's inherent characters of evolution, structure, and function

Palaeoclimatic events, dispersal and migratory losses along the Afro-European axis as drivers of biogeographic distribution in Sylvia warblers

<p>Abstract</p> <p>Background</p> <p>The Old World warbler genus <it>Sylvia </it>has been used extensively as a model system in a variety of ecological, genetic, and morphological studies. The genus is comprised of about 25 species, and 70% of these species have distributions at or near the Mediterranean Sea. This distribution pattern suggests a possible role for the Messinian Salinity Crisis (from 5.96-5.33 Ma) as a driving force in lineage diversification. Other species distributions suggest that Late Miocene to Pliocene Afro-tropical forest dynamics have also been important in the evolution of <it>Sylvia </it>lineages. Using a molecular phylogenetic hypothesis and other methods, we seek to develop a biogeographic hypothesis for <it>Sylvia </it>and to explicitly assess the roles of these climate-driven events.</p> <p>Results</p> <p>We present the first strongly supported molecular phylogeny for <it>Sylvia</it>. With one exception, species fall into one of three strongly supported clades: one small clade of species distributed mainly in Africa and Europe, one large clade of species distributed mainly in Africa and Asia, and another large clade with primarily a circum-Mediterranean distribution. Asia is reconstructed as the ancestral area for <it>Sylvia</it>. Long-distance migration is reconstructed as the ancestral character state for the genus, and sedentary behavior subsequently evolved seven times.</p> <p>Conclusion</p> <p>Molecular clock calibration suggests that <it>Sylvia </it>arose in the early Miocene and diverged into three main clades by 12.6 Ma. Divergence estimates indicate that the Messinian Salinity Crisis had a minor impact on <it>Sylvia</it>. Instead, over-water dispersals, repeated loss of long-distance migration, and palaeo-climatic events in Africa played primary roles in <it>Sylvia </it>divergence and distribution.</p