University of Fribourg

Collinearity refers to the non independence of predictor variables, usually in a regression‐type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one region or time, and predicted to another with a different or unknown structure of collinearity. To demonstrate the reach of the problem of collinearity in ecology, we show how relationships among predictors differ between biomes, change over spatial scales and through time. Across disciplines, different approaches to addressing collinearity problems have been developed, ranging from clustering of predictors, threshold‐based pre‐selection, through latent variable methods, to shrinkage and regularisation. Using simulated data with five predictor‐response relationships of increasing complexity and eight levels of collinearity we compared ways to address collinearity with standard multiple regression and machine‐learning approaches. We assessed the performance of each approach by testing its impact on prediction to new data. In the extreme, we tested whether the methods were able to identify the true underlying relationship in a training dataset with strong collinearity by evaluating its performance on a test dataset without any collinearity. We found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold‐based pre‐selection. Our results highlight the value of GLM in combination with penalised methods (particularly ridge) and threshold‐based pre‐selection when omitted variables are considered in the final interpretation. However, all approaches tested yielded degraded predictions under change in collinearity structure and the ‘folk lore’‐thresholds of correlation coefficients between predictor variables of |r| >0.7 was an appropriate indicator for when collinearity begins to severely distort model estimation and subsequent prediction. The use of ecological understanding of the system in pre‐analysis variable selection and the choice of the least sensitive statistical approaches reduce the problems of collinearity, but cannot ultimately solve them.

The capacity to predict future events permits a creature to detect, model, and manipulate the causal structure of its interactions with its environment. Behavioral experiments suggest that learning is driven by changes in the expectations about future salient events such as rewards and punishments. Physiological work has recently complemented these studies by identifying dopaminergic neurons in the primate whose fluctuating output apparently signals changes or errors in the predictions of future salient and rewarding events. Taken together, these findings can be understood through quantitative theories of adaptive optimizing control.

AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425,
\nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981,
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\nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374,
\nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822,
\nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480,
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\nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24,
\nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700,
\nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983,
\nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002,
\nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318,
\nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462,
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\nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003,
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\nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783,
\nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514,
\nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172,
\nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113,
\nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135,
\nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702,
\nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703,
\nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308,
\nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290,
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\nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563,
\nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936,
\nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657,
\nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254,
\nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694,
\nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781,
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\nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829,
\nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395,
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\nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767,
\nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301,
\nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919,
\nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576,
\nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572,
\nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940,
\nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340,
\nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254,
\nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604,
\nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182,
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The effects of lesions, receptor blocking, electrical self-stimulation, and drugs of abuse suggest that midbrain dopamine systems are involved in processing reward information and learning approach behavior. Most dopamine neurons show phasic activations after primary liquid and food rewards and conditioned, reward-predicting visual and auditory stimuli. They show biphasic, activation-depression responses after stimuli that resemble reward-predicting stimuli or are novel or particularly salient. However, only few phasic activations follow aversive stimuli. Thus dopamine neurons label environmental stimuli with appetitive value, predict and detect rewards and signal alerting and motivating events. By failing to discriminate between different rewards, dopamine neurons appear to emit an alerting message about the surprising presence or absence of rewards. All responses to rewards and reward-predicting stimuli depend on event predictability. Dopamine neurons are activated by rewarding events that are better than predicted, remain uninfluenced by events that are as good as predicted, and are depressed by events that are worse than predicted. By signaling rewards according to a prediction error, dopamine responses have the formal characteristics of a teaching signal postulated by reinforcement learning theories. Dopamine responses transfer during learning from primary rewards to reward-predicting stimuli. This may contribute to neuronal mechanisms underlying the retrograde action of rewards, one of the main puzzles in reinforcement learning. The impulse response releases a short pulse of dopamine onto many dendrites, thus broadcasting a rather global reinforcement signal to postsynaptic neurons. This signal may improve approach behavior by providing advance reward information before the behavior occurs, and may contribute to learning by modifying synaptic transmission. The dopamine reward signal is supplemented by activity in neurons in striatum, frontal cortex, and amygdala, which process specific reward information but do not emit a global reward prediction error signal. A cooperation between the different reward signals may assure the use of specific rewards for selectively reinforcing behaviors. Among the other projection systems, noradrenaline neurons predominantly serve attentional mechanisms and nucleus basalis neurons code rewards heterogeneously. Cerebellar climbing fibers signal errors in motor performance or errors in the prediction of aversive events to cerebellar Purkinje cells. Most deficits following dopamine-depleting lesions are not easily explained by a defective reward signal but may reflect the absence of a general enabling function of tonic levels of extracellular dopamine. Thus dopamine systems may have two functions, the phasic transmission of reward information and the tonic enabling of postsynaptic neurons.

Abstract Studies of local adaptation provide important insights into the power of natural selection relative to gene flow and other evolutionary forces. They are a paradigm for testing evolutionary hypotheses about traits favoured by particular environmental factors. This paper is an attempt to summarize the conceptual framework for local adaptation studies. We first review theoretical work relevant for local adaptation. Then we discuss reciprocal transplant and common garden experiments designed to detect local adaptation in the pattern of deme × habitat interaction for fitness. Finally, we review research questions and approaches to studying the processes of local adaptation – divergent natural selection, dispersal and gene flow, and other processes affecting adaptive differentiation of local demes. We advocate multifaceted approaches to the study of local adaptation, and stress the need for experiments explicitly addressing hypotheses about the role of particular ecological and genetic factors that promote or hinder local adaptation. Experimental evolution of replicated populations in controlled spatially heterogeneous environments allow direct tests of such hypotheses, and thus would be a valuable way to complement research on natural populations.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Although research on human-mediated exchanges of species has substantially intensified during the last centuries, we know surprisingly little about temporal dynamics of alien species accumulations across regions and taxa. Using a novel database of 45,813 first records of 16,926 established alien species, we show that the annual rate of first records worldwide has increased during the last 200 years, with 37% of all first records reported most recently (1970-2014). Inter-continental and inter-taxonomic variation can be largely attributed to the diaspora of European settlers in the nineteenth century and to the acceleration in trade in the twentieth century. For all taxonomic groups, the increase in numbers of alien species does not show any sign of saturation and most taxa even show increases in the rate of first records over time. This highlights that past efforts to mitigate invasions have not been effective enough to keep up with increasing globalization.

Most physiology and behavior of mammalian organisms follow daily oscillations. These rhythmic processes are governed by environmental cues (e.g., fluctuations in light intensity and temperature), an internal circadian timing system, and the interaction between this timekeeping system and environmental signals. In mammals, the circadian timekeeping system has a complex architecture, composed of a central pacemaker in the brain's suprachiasmatic nuclei (SCN) and subsidiary clocks in nearly every body cell. The central clock is synchronized to geophysical time mainly via photic cues perceived by the retina and transmitted by electrical signals to SCN neurons. In turn, the SCN influences circadian physiology and behavior via neuronal and humoral cues and via the synchronization of local oscillators that are operative in the cells of most organs and tissues. Thus, some of the SCN output pathways serve as input pathways for peripheral tissues. Here we discuss knowledge acquired during the past few years on the complex structure and function of the mammalian circadian timing system.

Hydrogen storage is a materials science challenge because, for all six storage methods currently being investigated, materials with either a strong interaction with hydrogen or without any reaction are needed. Besides conventional storage methods, i.e. high pressure gas cylinders and liquid hydrogen, the physisorption of hydrogen on materials with a high specific surface area, hydrogen intercalation in metals and complex hydrides, and storage of hydrogen based on metals and water are reviewed. The goal is to pack hydrogen as close as possible, i.e. to reach the highest volumetric density by using as little additional material as possible. Hydrogen storage implies the reduction of an enormous volume of hydrogen gas. At ambient temperature and atmospheric pressure, 1 kg of the gas has a volume of 11 m3. To increase hydrogen density, work must either be applied to compress the gas, the temperature decreased below the critical temperature, or the repulsion reduced by the interaction of hydrogen with another material.

Biological invasions are a global consequence of an increasingly connected world and the rise in human population size. The numbers of invasive alien species - the subset of alien species that spread widely in areas where they are not native, affecting the environment or human livelihoods - are increasing. Synergies with other global changes are exacerbating current invasions and facilitating new ones, thereby escalating the extent and impacts of invaders. Invasions have complex and often immense long-term direct and indirect impacts. In many cases, such impacts become apparent or problematic only when invaders are well established and have large ranges. Invasive alien species break down biogeographic realms, affect native species richness and abundance, increase the risk of native species extinction, affect the genetic composition of native populations, change native animal behaviour, alter phylogenetic diversity across communities, and modify trophic networks. Many invasive alien species also change ecosystem functioning and the delivery of ecosystem services by altering nutrient and contaminant cycling, hydrology, habitat structure, and disturbance regimes. These biodiversity and ecosystem impacts are accelerating and will increase further in the future. Scientific evidence has identified policy strategies to reduce future invasions, but these strategies are often insufficiently implemented. For some nations, notably Australia and New Zealand, biosecurity has become a national priority. There have been long-term successes, such as eradication of rats and cats on increasingly large islands and biological control of weeds across continental areas. However, in many countries, invasions receive little attention. Improved international cooperation is crucial to reduce the impacts of invasive alien species on biodiversity, ecosystem services, and human livelihoods. Countries can strengthen their biosecurity regulations to implement and enforce more effective management strategies that should also address other global changes that interact with invasions.

Uncertainty is critical in the measure of information and in assessing the accuracy of predictions. It is determined by probability P, being maximal at P = 0.5 and decreasing at higher and lower probabilities. Using distinct stimuli to indicate the probability of reward, we found that the phasic activation of dopamine neurons varied monotonically across the full range of probabilities, supporting past claims that this response codes the discrepancy between predicted and actual reward. In contrast, a previously unobserved response covaried with uncertainty and consisted of a gradual increase in activity until the potential time of reward. The coding of uncertainty suggests a possible role for dopamine signals in attention-based learning and risk-taking behavior.

Permafrost warming has the potential to amplify global climate change, because when frozen sediments thaw it unlocks soil organic carbon. Yet to date, no globally consistent assessment of permafrost temperature change has been compiled. Here we use a global data set of permafrost temperature time series from the Global Terrestrial Network for Permafrost to evaluate temperature change across permafrost regions for the period since the International Polar Year (2007-2009). During the reference decade between 2007 and 2016, ground temperature near the depth of zero annual amplitude in the continuous permafrost zone increased by 0.39 ± 0.15 °C. Over the same period, discontinuous permafrost warmed by 0.20 ± 0.10 °C. Permafrost in mountains warmed by 0.19 ± 0.05 °C and in Antarctica by 0.37 ± 0.10 °C. Globally, permafrost temperature increased by 0.29 ± 0.12 °C. The observed trend follows the Arctic amplification of air temperature increase in the Northern Hemisphere. In the discontinuous zone, however, ground warming occurred due to increased snow thickness while air temperature remained statistically unchanged.

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTPhotoremovable Protecting Groups in Chemistry and Biology: Reaction Mechanisms and EfficacyPetr Klán*†‡, Tomáš Šolomek†‡, Christian G. Bochet§, Aurélien Blanc∥, Richard Givens⊥, Marina Rubina⊥, Vladimir Popik#, Alexey Kostikov#, and Jakob Wirz∇View Author Information† Department of Chemistry, Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic‡ Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Kamenice 3, 625 00 Brno, Czech Republic§ Department of Chemistry, University of Fribourg, Chemin du Musée 9, CH-1700 Fribourg, Switzerland∥ Institut de Chimie, University of Strasbourg, 4 rue Blaise Pascal, 67000 Strasbourg, France⊥ Department of Chemistry, University of Kansas, 1251 Wescoe Hall Drive, 5010 Malott Hall, Lawrence, Kansas 66045, United States# Department of Chemistry, University of Georgia, Athens, Georgia 30602, United States∇ Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland*E-mail: [email protected]. Phone: +420-54949-4856. Fax: +420-54949-2443.Cite this: Chem. Rev. 2013, 113, 1, 119–191Publication Date (Web):December 21, 2012Publication History Received29 April 2012Published online21 December 2012Published inissue 9 January 2013https://doi.org/10.1021/cr300177kCopyright © 2012 American Chemical SocietyRIGHTS & PERMISSIONSACS AuthorChoiceArticle Views77851Altmetric-Citations1248LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (17 MB) Get e-AlertscloseSUBJECTS:Alcohols,Fluorescence,Irradiation,Organic compounds,Reaction products Get e-Alerts

Although the interest in experimental evidence of magnetic field effects (MFEs) on the kinetics of chemical reactions, which might be characterized by the term magnetokinetics , has a long tradition, an impressive evolution of the field took place only after the discovery and understanding of nuclear and electronic spin polarization phenomena during chemical reactions (CIDNP, CIDEP) in the late 1960s. The so-called radical pair mechanism lying at the heart of these phenomena turned out to be a most valuable key for systematically tracing out MFEs on chemical yields and kinetics.<br />Nevertheless one should be aware that other mechanisms, too, with pairs of triplets, triplet-doublet pairs, or individual triplets, which originated at about the same time and were initially developed for explaining magnetic phenomena on luminescence in organic solids, also have their implication on chemical, particularly on photochemical, kinetics.<br />Phenomenologically, the basic mechanisms of magnetic-field-dependent reaction mechanisms may become apparent in fields and systems as different as the gas phase, the solid and liquid states, interfaces, and microheterogeneous systems such as micelles and in billogical systems. In all of these applications they have specific experimental and theoretical characteristics. Also, the techniques applied to study magnetokinetic phenomena span a large variety, ranging from magnetic resonance detection of spin polarization (CIDNP, CIDEP, ODMR) through simple detection of magneticfield-dependent reaction yields and magnetic isotope effects (MIE) to reaction-yield-detected magnetic resonance (RYDMR).<br />Thus the field of magnetokinetic chemical and related physical phenomena appears as a tree with several roots and many branches. Although each of these branches has been reviewed from time to time (cf. Table l), most of the treatments have been rather specialized, and it is not easy to provide oneself with a broad and general view of the scope, objectives, and achievements of the field. Thus we have found it worthwhile to write this survey, developing the different aspects from a fairly general point of view (cf. section 11), and to review, as comprehensively as possible, the original experimental (section IV) and theoretical (section V) work published since the early 1970s, providing whenever possible a systematic compilation in the form of tables. Furthermore, in section I11 an outline of the various experimental techniques applied in the field is given.<br />Of course, the goals of completeness and compactness were not attainable without compromise. Thus the large field of chemically induced spin polarization phenomena would have been beyond the scope of this review. We have, however, attempted to include those theoretical papers in the field that have a general bearing on the understanding of magnetokinetic effects in general. We felt that, especially where photochemistry is concerned, the borderline between truly chemical and purely physical phenomena should not be defined too formally, since from the mechanistic and theoretical point of view they may be closely related.<br />In order to account for this we included what has been termed related phenomena in the title of this review. Of course. the problem of delimitation cannot be solved without arbitrariness. The more photophysical aspects are mainly to be found in the sections on gas-phase and solid-state phenomena. In the solid state our attention has been mainly directed on work with organic molecular crystals. Only some representative references on inorganic solids and semiconductors are given.<br />We hope that this review may provide a welcome guide to the present body of literature on magnetokinetics, that it may help those working in the field to assess the achievements of current original work, and that it may be a useful framework of orientation for those who want to get into it or get an impression of the present scope of magnetokinetics.

Infection of plants by necrotizing pathogens or colonization of plant roots with certain beneficial microbes causes the induction of a unique physiological state called "priming." The primed state can also be induced by treatment of plants with various natural and synthetic compounds. Primed plants display either faster, stronger, or both activation of the various cellular defense responses that are induced following attack by either pathogens or insects or in response to abiotic stress. Although the phenomenon has been known for decades, most progress in our understanding of priming has been made over the past few years. Here, we summarize the current knowledge of priming in various induced-resistance phenomena in plants.

The endogenous plant hormones salicylic acid (SA) and jasmonic acid (JA), whose levels increase on pathogen infection, activate separate sets of genes encoding antimicrobial proteins in Arabidopsis thaliana. The pathogen-inducible genes PR-1, PR-2, and PR-5 require SA signaling for activation, whereas the plant defensin gene PDF1.2, along with a PR-3 and PR-4 gene, are induced by pathogens via an SA-independent and JA-dependent pathway. An Arabidopsis mutant, coi1, that is affected in the JA-response pathway shows enhanced susceptibility to infection by the fungal pathogens Alternaria brassicicola and Botrytis cinerea but not to Peronospora parasitica, and vice versa for two Arabidopsis genotypes (npr1 and NahG) with a defect in their SA response. Resistance to P. parasitica was boosted by external application of the SA-mimicking compound 2, 6-dichloroisonicotinic acid [Delaney, T., et al. (1994) Science 266, 1247-1250] but not by methyl jasmonate (MeJA), whereas treatment with MeJA but not 2,6-dichloroisonicotinic acid elevated resistance to Alternaria brassicicola. The protective effect of MeJA against A. brassicicola was the result of an endogenous defense response activated in planta and not a direct effect of MeJA on the pathogen, as no protection to A. brassicicola was observed in the coi1 mutant treated with MeJA. These data point to the existence of at least two separate hormone-dependent defense pathways in Arabidopsis that contribute to resistance against distinct microbial pathogens.

Associative learning enables animals to anticipate the occurrence of important outcomes. Learning occurs when the actual outcome differs from the predicted outcome, resulting in a prediction error. Neurons in several brain structures appear to code prediction errors in relation to rewards, punishments, external stimuli, and behavioral reactions. In one form, dopamine neurons, norepinephrine neurons, and nucleus basalis neurons broadcast prediction errors as global reinforcement or teaching signals to large postsynaptic structures. In other cases, error signals are coded by selected neurons in the cerebellum, superior colliculus, frontal eye fields, parietal cortex, striatum, and visual system, where they influence specific subgroups of neurons. Prediction errors can be used in postsynaptic structures for the immediate selection of behavior or for synaptic changes underlying behavioral learning. The coding of prediction errors may represent a basic mode of brain function that may also contribute to the processing of sensory information and the short-term control of behavior.

Kinetic interfaces form the basis of a fascinating, interdisciplinary branch of statistical mechanics. Diverse stochastic growth processes can be unified via an intriguing nonlinear stochastic partial differential equation whose consequences and generalizations have mobilized a sizeable community of physicists concerned with a statistical description of kinetically roughened surfaces. Substantial analytical, experimental and numerical effort has already been expended. Despite impressive successes, however, there remain many open questions, with much richness and subtlety still to be revealed. In this review, we give an unorthodox account of this rapidly growing field, concentrating on two main lines — the interface growth equations themselves, and their directed polymer counterparts. We emphasize the intrinsic links among the topics discussed, as well as the relationships to other branches of natural science. Our aim is to persuade the reader that multidisciplinary statistical mechanics can be challenging, enjoyable pursuit of surprising depth.

Polymyxins are well-established antibiotics that have recently regained significant interest as a consequence of the increasing incidence of infections due to multidrug-resistant Gram-negative bacteria. Colistin and polymyxin B are being seriously reconsidered as last-resort antibiotics in many areas where multidrug resistance is observed in clinical medicine. In parallel, the heavy use of polymyxins in veterinary medicine is currently being reconsidered due to increased reports of polymyxin-resistant bacteria. Susceptibility testing is challenging with polymyxins, and currently available techniques are presented here. Genotypic and phenotypic methods that provide relevant information for diagnostic laboratories are presented. This review also presents recent works in relation to recently identified mechanisms of polymyxin resistance, including chromosomally encoded resistance traits as well as the recently identified plasmid-encoded polymyxin resistance determinant MCR-1. Epidemiological features summarizing the current knowledge in that field are presented.

This paper examines induced resistance (SAR) in plants against various insect and pathogenic invaders. SAR confers quantitative protection against a broad spectrum of microorganisms in a manner comparable to immunization in mammals, although the underlying mechanisms differ. Discussed here are the molecular events underlying SAR: the mechanisms involved in SAR, including lignification and other structural barriers, pathogenesis-related proteins and their expression, and the signals for SAR including salicylic acid. Recent findings on the biological role of systemin, ethylene, jasmonates, and electrical signals are reviewed. Chemical activators of SAR comprise inorganic compounds, natural compounds, and synthetic compounds. Plants known to exhibit SAR and induced systemic resistance are listed.