Here, we present a model where the counterfactual part of these striatal dopamine fluctuations originates in another valuation system that shadows the dopamine system by acting as its near-antipode in terms of spike-rate encoding yet co-releases dopamine alongside its own native neurotransmitter. We show that such a hypothesis engenders important representational consequences where valence processing appears subject to the efficient encoding considerations common to the visual and auditory systems. This new perspective opens up important computational consequences for understanding how value-predicting information should integrate with sensory processing streams. Current Opinion in Behavioral Sciences 2016, 11:121–129Computational modelingThis review comes from a themed issue on Peter Dayan and Daniel DurstewitzEdited by Issue and the EditorialFor a complete overview see the Available online 8th September 2016http://dx.doi.org/10.1016/j.cobeha.2016.08.002http://creativecommons.org/licenses/by/4.0/).2352-1546/© 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license  and finally, counterfactual error encoding •. The auThe idea proposed by Kishida and colleagues was that some other source/sink for dopamine existed that could encode information about foregone gains and losses (encoded in the game by bet level •). In thSeveral possibilities ensue from these observations. First, it is possible that midbrain dopamine neurons, in the context of this simple cognitive challenge, have prediction error and counterfactual error computations available and encoded appropriately as changes in spike rate. The reason this has not been observed before is that prior work never really challenged an animal in the same way  midbrain dopamine neurons known for generating reward prediction error signals also generate spike modulations consistent with prediction error and counterfactual error signaling, OR (2) there is another class of midbrain dopamine neuron dedicated to the counterfactual term, OR (3) there is an opponent to the dopaminergic reward prediction error signal that releases dopamine or controls the release of dopamine in striatal regions. This list is not biologically exhaustive. In this opinion piece, we restrict our focus to the possibility that the shadow system in possibility 3 are serotonergic neurons from the nucleus raphe and we lean on the fact that they can load dopamine into their terminals ••.et al. [et al. [l-DOPA treatment, serotonin terminals originating from neurons in the dorsal raphe nucleus contributed directly to dopaminergic transmission. This cross-loading has important downstream consequences including the fact that there are two dynamic sources of dopamine fluctuations — dopaminergic terminals and serotonergic terminals. In the event that the parent dopamine and serotonin neurons encode different operations, these operations would be combined due to cross-loading. This is exactly the possibility that we offered above to explain the human dopamine data recorded in humans during the simple betting game  •. Here, P and N (positive and negative), capable of learning and emitting prediction errors in future rewards and aversions respectively and suggest that the neurotransmitter couplings between these systems can be seen as one way to transform from separate P and N systems, let us call that the {P,N} bases, to a different basis {(P + N), (P − N)}, which act respectively as a salience channel (P + N) and a value contrast (P − N) channel  models  of how mTo learn from experience a mobile organism must possess adaptive mechanisms for valuing the world in the face of changing contingencies; an almost self-evident rendering of what it means to adapt to and learn from a variable world. One general approach to learning about rewarding and aversive events is called reinforcement learning (RL), which focuses on how an agent responds to, stores, and plans actions around the rewards and aversives it encounters or could have encountered . A typicVP to its current state St according to the discounted rewards expected from that state into the distant future [P indicates positive valence. This simple hypothesis embeds the Markovian or history-independent assumption — how a state is acquired is not relevant to its valuation, only the future that it portends influences its value:In reinforcement learning, the main valuation hypothesis is that a learning agent should assign a value t future . Here thE is the expected value operator, γ is a discount factor set somewhere between 0 and 1 that devalues rewards expected to the future of the current state, and t is discretized time. According to the same idea, the valuation of the next state St+1 follows similarly:From these expressions, one arrives at a form of the well-known Bellman equation 4 that relates the value of the state at one moment to the value of the state in the next moment :If a learning agent (like a rat) was using a similar scheme to value its states then a natural ‘error signal’ would be the difference between the right and left hand sides of Equation 3:This kind of error signal can be used simply and directly to update parameters used to estimate the value function:perturbations in their spike rate [neurotransmitter in those terminals converts There is now substantial evidence that a subset of mammalian midbrain dopamine neurons encode ike rate , 19, 20.VN associated with a state St is the expected value of exponentially discounted aversives expected from St forward into the distant future:An exactly analogous argument could be made for the learning of future aversive stimuli and the way a state should be valued in terms of predicting this discounted aversive future. The hypothesis here is that the potential negative value Which can be used to update the value function over aversives:P pathway and N pathway, which would translate into signed fluctuations in dopamine and serotonin release. The extracellular space ‘adds up’ the ensuing changes in these transmitters to encode VP(St) − VN(St). This conceptual framing of the valuation and prediction problem (without committing to any specific representation) closely resembles Daw et al. [The basic idea for the two systems is that each updates its predictions of future rewards and aversives separately but these predictions combine to produce a composite error signal encoded as signed pertubations in baseline spike rates, w et al. •• exceptunderstood by downstream receptor systems as updating respectively future predictions about positively valenced and negatively valenced stimuli. So one key conceptual step is to separate the error encoding by the parent neurons (expressed as perturbations in spike rate) from the neurotransmitter semantics (as interpreted by downstream effector mechanisms).One important assumption in this account is that neurotransmitter fluctuations  are already P and separately imagining that the serotonin system is the negative valence pathway N. We have sketched how P and N could direct reward and aversive prediction learning in fashion aligned with reinforcement learning models generally, and argued for midbrain dopamine and serotonin systems as a possible substrates. This style of model has been used fruitfully to understand a wide range of behavioral data and has informed possibilities for mapping these models to supporting biological substrates [We have presented a caricaturized view of valence processing by considering the dopamine system as the positive valence pathway bstrates , 23, 24.bstrates , 12, 13.P and N pathways represent separate positive and negative valence prediction capacity. Here we show a depiction of the bi-directionally coupled P and N systems where perturbations in the dynamics of the two neurotransmitters (δD(t), δS(t)) are controlled by both the spike-encoded reward prediction errors As suggest in α is the fraction of the native neurotransmitter (labeled D here for ‘dopamine’) in the P pathway that is present in the P terminal and the remainder (1 − α) is assigned to the N pathway terminal. Similarly, β is the fraction of native neurotransmitter (labeled S for ‘serotonin’) in the N pathway terminal and the remainder (1 − β) is assigned to the P pathway terminal. Noise terms ND(t) and NS(t) for each transmitter include synaptic noise and unaccounted for extrasynaptic sources/sinks for D and S.P and N pathways to perturbations in neurotransmitter release, and (2) the neurotransmitter coupling between the two systems; a feature we have termed soft cross-wiring. For α = β = 1, the ‘normal’ situation ensues where dopamine and serotonin separately carry the reward prediction error and aversive prediction error information. Ignoring issues about diffusion, this is the situation where the prediction errors from moment-to-moment could be monitored separately by recording dopamine and serotonin simultaneously in the vicinity (receptors could do this). Once cross-loading occurs because either or both alpha and beta deviate from 1, then the prediction errors and the learned weights that instantiate them become mixed. One can then imagine wanting to unmix these signals or detect both serotonin and dopamine in a combination that had computational relevance. We explore this below.Equation 9 expresses two couplings: (1) the coupling of spike-encoded prediction errors along P and N pathways is to imagine that these systems’ sensitivities are close in order to discriminate valence in a world where the positive and negative valuations pertinent for survival are close. So let us take the closeness as evidence of an adaptation to a tough set of valence discrimination problems — ignoring the fact that a nervous system does not simply discriminate raw valence but instead assigns it to objects (including living objects), which possess a range of other properties not considered here. Consequently, the near redundancy along the P and N pathways is not the best representation to process the valence information since it wastes resources because of the high degree of correlation between the systems. One way to deal with this correlation is to decorrelate the signals. One simple way to accomplish this is to rotate to a different set of directions with the obvious ones being P + N and P − N. Downstream receptors can easily effect such a transformation either by direct binding or through convergence onto intracellular signaling cascades. This new {P + N, P − N} basis provides natural directions where P + N is a salience signal and P − N a valence contrast signal. It is important to note that both dopamine and serotonin would be involved in coding the response along each new direction. Taking the system in Equation 9 expressed in the {P,N} basis, we can rotate into the {P + N, P − N} basis but keeping things expressed in terms of the changes in transmitters to make clear how downstream effector mechanisms could ‘sense’ valence responses along directions that incorporated an efficient encoding principle [One way to understand the nearly anti-correlated responses of the rinciple , 12, 13:P − N and P + N directions. They can simply respond to the sum or difference in the fluctuations. This could take place on the surface of a cell or using intracellular cascades (both serotonin and dopamine couple to g-protein coupled receptors for example):Multiplying out the left hand side shows in Equation 11 how downstream receptors could sense and respond to dopamine and serotonin changes in a manner aligned with We can express the situation, ignoring lots of potential complications, as:α = β = 1, there is no mixing and the transformation here is a simple decorrelation that would define a salience channel and a valence difference channel. We have left off the issue of how to adjust the sensitivity for the different directions in order to focus on the idea of handling the valence processing problem in terms of efficient encoding and separate value systems  vision and red/green cone sensitivities. In primates, the peak spectral sensitivities of red and green cones are very close (∼30 nm), which apparently reflect the range of wavelengths where such discrimation is computationally pertinent , 11•. Th primate ••. This l-DOPA drugs used to treat Parkinson's and computational ideas about basal ganglia function [In summary, we began with a new measurement of striatal dopamine in human subjects and found that existing computational models of dopaminergic function were inadequate to capture the possibility that dopamine encodes prediction errors in reward and counterfactual errors in reward. One trivial possibility is that some simplistic element of the behavioral task  is accidentally creating a situation for dopamine release that is not normal and only appears to encode a bet-dependent counterfactual signal — this is indeed possible since the subjects involved have a disease of their dopaminergic system (Parkinson's Disease). The interactions that we posit here are quite specific in terms of transmitters and neural elements; however, other work has observed loosely similar coupling and suggested a way to relate function , 24, 25.P and N (positive and negative) dedicated to making this assignment. We think here of P and N as directions in some valence space and claim that they rate the reward-predicting or aversive-predicting valence of situations that represent difficult valence detection problems. These same systems can share transmitter at their terminals when those terminals happen to be sufficiently close; a fact that immediately mixes reward and aversive prediction information. In the context of the behavioral task in Several new possibilities emerge from the opinion presented here. First, we suggest that all stimuli have the possibility to be assigned a composite of positive and negative valence through the operation of two prediction systems P and N channel modulation. It could even be the case that the exquisite structural arrangements in the striatum can be understood as natural ways to organize P and N information in a fashion homologous to similar analyses in visual cortex [We have completely avoided treating learned timing among stimuli and the near-term rewards and punishments that they portend. However, there should be very interesting connections of this framework to related analyses in the visual system. For example, there is strong evidence that independent objects in the visual world are the source of natural visual scaling statistics • and thal cortex , 13.Nothing declared.• of special interest•• of outstanding interestPapers of particular interest, published within the period of review, have been highlighted as:


FT-IR spectra showed nitrile groups in the PAN were partly converted into amidoxime groups. SEM examination demonstrated that there were no serious cracks or sign of degradation on the surface of the PAN nanofibers after chemical modification. The adsorption capacities of both copper and iron ions onto the AOPAN nanofiber mats were higher than those into the raw PAN nanofiber mats. The adsorption data of Cu2+ and Fe3+ ions fitted particularly well with the Langmuir isotherm. The maximal adsorption capacities of Cu2+ and Fe3+ ions were 215.18 and 221.37 mg/g, respectively.Polyacrylonitrile (PAN) nanofibers were prepared by electrospinning and they were modified with hydroxylamine to synthesize amidoxime polyacrylonitrile (AOPAN) chelating nanofibers, which were applied to adsorb copper and iron ions. The conversion of the nitrile group in PAN was calculated by the gravimetric method. The structure and surface morphology of the AOPAN nanofiber were characterized by a Fourier transform infrared spectrometer (FT-IR) and a scanning electron microscope (SEM), respectively. The adsorption abilities of Cu With the rapid development of global industry and the advent of new technologies, environmental contamination has presented a great threat to human health; especially with significantly the amounts of heavy metal ions in wastewater . Heavy metc. [etc. [Various techniques have been utilized to remove and recycle heavy metals from aqueous solutions such as chemical precipitation, ion exchange, membrane separation, electrochemical treatment, adsorption, etc. ,6,7,8. Ac. [etc. , to formetc. [Recently, the electrospinning technique, a simple and versatile method, has been widely applied to produce nanofibers. Electrospun nanofibers are known to possess numerous interesting characteristics such as high porosity, small interfibrous pore size, and most importantly much largee specific surface in comparison to conventional fibers. Nanofibers are applied widely in tissue engineering , drug deetc. . Thus, nPolyacrylonitrile (PAN) has been recognized as a highly efficient material for the removal and enrichment of heavy metals . In the Mw = 30,000–50,000 g/mol) were purchased from America. The ferric chloride (FeCl3·6H2O), copper chloride (CuCl2·2H2O), and N,N-Dimethyl Formamide (DMF) were obtained from SCRC. All the chemicals were analytical grade and were used without further purification.The PAN powders . A Fourier transform infrared (FT-IR) spectrometer, Nicolet is10, from Thermo Fisher Scientific Inc. (China) was employed to analyze the chemical structure. A Spectr AA-220 atomic absorption spectroscopy (AAS) was used to measure the concentration of copper and iron ions in solutions.The PAN powders were dissolved in DMF at 10 wt % concentration under constant stirring at room temperature for 24 h to make even spinning solution. The prepared solution was loaded in a 10 mL of plastics syringe with a metal needle . The electrospinning parameters were determined based on the previous research achievements . The appElectrospun PAN nanofibers were modified into chelating nanofibers containing amidoxime groups by reacting with hydroxylamine hydrochloride, transforming nitrile groups into amidoxime groups as shown in C (%) is the conversion of nitrile group into amidoxime group in the PAN, W0 is the weight of the initial PAN nanofiber membranes, W1 is the weight of the modified PAN nanofiber membranes, 53 and 33 are the molecular weights of acrylonitrile monomer and hydroxylamine, respectively.The conversion of nitrile group in the PAN was calculated as follows :(1)C=W1Q is the adsorption amount (mg/g) onto the PAN nanofibers, C0 is the initial concentration of metal ions (mg/L), C1 is the final concentration (mg/L),  m is the weight of nanofiber mats (g).All adsorption experiments were conducted in 250 mL of beakers at 303 K. Dried raw PAN nanofiber and modified nanofiber mats, with the same total specific surface area, were immersed in 50 mL aqueous metal salt solutions for different time duration, and then removed from the beakers at 0.5, 1, 2, 3, 6, 24 h. The obtained nanofiber mats were washed with deionized water. The lotion and the remaining metal salt aqueous solutions were transferred to a 100 mL of volumetric flask, evenly mixed for measurement. The equilibrium isotherm time was determined, and the equilibrium isotherm was investigated at 72 h and at 303 K. The concentration of metal-ions in solutions was measured by atomic absorption spectroscopy (AAS). The adsorption amounts were calculated as follows:−1 (–C≡N) and 1735 cm−1 (C=O), which indicated that the PAN was a copolymer or the DMF solvents and not volatilized completely. The FT-IR spectrum of modified PAN  in a 1 mg/L of solution as a function of time (for 72 h). The experiment for each sample was repeated five times. The error analysis was also shown in the figure. It was evident that the chemical modification of PAN nanofibers had a significant effect on the adsorption ability. The adsorption capacities of Cu2+ and Fe3+ ions onto PAN nanofibers were 198.46 and 278 mg/g, respectively. However, the capacities onto AOPAN nanofibers were 320 and 380 mg/g, respectively. The capacities adsorbed on the PAN nanofibers were obviously lower than those onto the AOPAN nanofibers. The results in 3+ ion onto nanofibers was higher than that of Cu2+ ion, as shown in 3+ ion is a hard acid, with a small size and strong electropositive, which more easily accepted electrons from the ligand. However, Cu2+ ion displayed a weaker electron-accepting nature compared to Fe3+ ion. PAN and AOPAN, containing hydroxyl and amine group, had the structure characteristics of hard acid, with an electron-donating nature and strongly electronegativity. According to HSAB (Hard-Soft Acid Base) theory and Lewis acid-base theory [3+ ions were expected to give stronger complexes with PAN and AOPAN, which led to Fe3+ ion having a higher adsorption capacity than Cu2+ ion.It was observed that the adsorption capacity of Fee theory , Fe3+ ioQe) of Cu2+ and Fe3+ ions onto AOPAN nanofiber mats after the equilibrium time (72 h) as a function of equilibrium concentration (Ce). Qe increased sharply and then gradually with an increase in Ce. At equilibrium, an adsorption isotherm can be constructed at a given constant temperature. Adsorption data should accurately fit into different isotherm models. The most common ones are the Langmuir and the Freundlich models. These equations are as follows, respectively:Qe is the equilibrium amount of the metal adsorbed onto the AOPAN nanofiber mat (mg/g); Qm is the maximum adsorption capacity (mg/g); b is the Langmuir constant related to binging energy (L/mg); Ce is the equilibrium concentration (mg/L). The values of Qm and b were calculated, as shown in K and n are the Freundlich constants. The values of these parameters were also analyzed from the plots shown in r2). The Langmuir model is used to describe the adsorption taking place at specific homogeneous sites. Once an adsorptive site is occupied, no further adsorption can occur. Thus, the adsorption of copper and iron ions followed the formation of a monolayer. The reported value for the maximum adsorption of Cu2+ ion onto AOPAN nanofibers is approximately that of Fe3+ ion. However, this value is not consistent with the results shown in As shown in 2+ and Fe3+ ions on the AOPAN nanofiber mat increased with increase in adsorption time, and then leveled off at approximately 6 h. The adsorption data of both Cu2+ and Fe3+ ions fitted particularly well with the Langmuir isotherm, indicating that adsorption took place via the formation of a monolayer.The AOPAN nanofiber mats were produced using the electrospinning technique and chemical modification of the nitrile group. The conversion of the nitrile group in PAN increased along with increased reaction time, temperature and concentrations of hydrochloride hydroxylamine. The conversion was maximized at pH 7. The PAN nanofiber mats became light yellow and brittle above 50% conversion. SEM photos confirm that the AOPAN nanofiber did not show any serious cracks or degradation. The adsorption capacities of copper and iron ions onto the AOPAN nanofiber mats were higher than the PAN nanofiber mats. The adsorption of both Cu


Dissolved inorganic nitrogen (DIN) movement from Australian sugarcane farms is believed to be a major cause of crown-of-thorns starfish outbreaks which have reduced the Great Barrier Reef coral cover by ~21% (1985–2012). We develop a daily model of DIN concentration in runoff based on >200 field monitored runoff events. Runoff DIN concentrations were related to nitrogen fertiliser application rates and decreased after application with time and cumulative rainfall. Runoff after liquid fertiliser applications had higher initial DIN concentrations, though these concentrations diminished more rapidly in comparison to granular fertiliser applications. The model was validated using an independent field dataset and provided reasonable estimates of runoff DIN concentrations based on a number of modelling efficiency score results. The runoff DIN concentration model was combined with a water balance cropping model to investigate temporal aspects of sugarcane fertiliser management. Nitrogen fertiliser application in December (start of wet season) had the highest risk of DIN movement, and this was further exacerbated in years with a climate forecast for ‘wet’ seasonal conditions. The potential utility of a climate forecasting system to predict forthcoming wet months and hence DIN loss risk is demonstrated. Earlier fertiliser application or reducing fertiliser application rates in seasons with a wet climate forecast may markedly reduce runoff DIN loads; however, it is recommended that these findings be tested at a broader scale. Acanthaster planci) and the potential for crown-of-thorns outbreaks  from fertilised agricultural lands has been identified as a major water quality issue internationally , dry tropics  through to sub-tropics . All regions have high inter-annual rainfall variability (average coefficient of variation of 34%) which is in part, influenced by the El Niño-Southern Oscillation Allan  and the Australian sugarcane cropping practices follow a 5- to 6-year cycle. The crop is harvested on a ~12- to 13-month time period. After each harvest, the crop re-establishes from the same rootstock (ratooning) until the third or fourth ratoon whereupon the rootstock is ploughed out. After the final ratoon stage, the land is either left as a bare fallow or a legume such as soybeans or cowpeas is sown. Nitrogen (N) fertiliser is typically applied twice in the plant stage—an initial small amount at planting (e.g. 30 kg N/ha) followed by a top-up ~3 months after planting (e.g. 130 kg N/ha). Fertiliser is often applied only once during each ratoon crop with rates being in the range of 130–200 kg N/ha, depending on the productivity of the region. Fertiliser application generally occurs in the 5-month period from late winter (August) through to early summer (December). These time frames are associated with the cane harvesting and planting schedule which occurs during the same time period. There are a number of factors that can affect the timing of fertiliser applications. These include date of harvesting of the previous crop, crop height for machinery access and weather conditions which can affect tractor access.2, except for at Ayr where catchments were up to 11.6 ha. DIN loads in runoff vary from being 0.1–11% of applied nitrogen fertiliser, with a median loss of 1.3% of applied nitrogen fertiliser (hence having little to no agronomic impact). Understanding the causes of the variability in DIN loads may inform better fertiliser management strategies to minimise DIN losses in runoff. The fate of nitrogen fertiliser in cane farming systems is complex with 11 pathways described by Bristow et al.  were located in the central sugarcane growing region, and a third site  was located in the southern sugarcane growing region. Annual load results for the Victoria Plains site are reported in Table DIN concentrations were measured in surface runoff from three sugarcane experimental trials Fig.  at a padThe form of nitrogen fertiliser (granular or liquid) and application rates varied between sites, as well as between years for a given site Table . All ferThe number of runoff events with DIN concentration measurements varied greatly across sites and between years, with the 2010–2011 season at the central region sites resulting in the greatest number of runoff events with DIN measurements.To validate the proposed granular fertiliser model, an independent dataset from a sugarcane site located in the northern cane growing region was used . SPOTA-1 forecasts are provided on a monthly basis from June through to November each year for the forthcoming seasonal rainfall for December to March. These climate forecasts align to when farmers need to make decisions regarding fertilising their sugarcane crop. Figure r2 = 0.25, p < 0.05). In the simulation study, the October SPOTA-1 forecast QRI anomaly was classified as being in one of three categories: ‘wet’, ‘average’ and ‘dry’ forecast rainfall conditions. This system of classification was achieved by ranking the forecast QRI anomaly for the years 1900–2013, the top third of the rankings—i.e. those forecasting a wet summer—were assigned to the wet group. Simulated seasonal runoff DIN loads from HowLeaky were also accumulated for the same tercile groups. The simulation study examined the impact of granular and liquid fertiliser applied at close to conventional rates of 170 kg N/ha and at 85 kg N/ha  climate forecast system Day et al. Factors investigated with respect to DIN concentrations in surface runoff were as follows: (a) rainfall since application (including irrigation events); (b) time after application; (c) sediment concentration in runoff; and (d) fertiliser N application rate Fig. .Fig. 3DIUpon visual inspection, three of these factors—time after application, rainfall since application and N application rate—had an effect on DIN concentrations in runoff, while suspended sediment did not appear to have any consistent effect. The incorporated soybean crop appeared to have a delayed effect on DIN in runoff when compared to fertilisers Fig. a, b. In As these unusually high DIN concentration events had low runoff volumes, they contributed only a small proportion of the total DIN lost in runoff over a full season. Therefore, these runoff DIN concentration measurements were not included in any further model development .Given that there were multiple nitrogen fertiliser applications in 12 of the 25 seasons Table , runoff As both time and rainfall since application may be correlated, two independent empirical models of DIN concentrations were developed based on these two components and a third empirical model was developed by combining both these components. Given the occurrence of multiple inputs of nitrogen for a number of seasons at the central region sites, a daily time-step model of DIN concentration in runoff was developed. The three models were—(1) time after application and application rate, (2) rainfall since application and application rate and (3) time after application and rainfall since application and application rate.Rainfall has been reported to contain low levels of DIN; hence, we set a lower DIN concentration limit for the runoff models. There have been relatively few reported measurements of naturally occurring background levels of DIN in rainfall for coastal areas in Queensland. In the Townsville region, Probert  measuredThe form of the three models was as follows:time based model.Time and nitrogen input based model. This will now be referred to as the For each model, runoff concentration on the date of fertiliser application was as follows:2.rainfall based model.Rainfall and nitrogen input based model. This will now be referred to as the 3.time and rainfall based model.Time, rainfall and nitrogen input based model. This will now be referred to as the d1DINDIN concentration in runoff water on fertiliser application date (mg/l)rt.DINDIN concentration in runoff water today (mg/l)ryDINDIN concentration in runoff water yesterday (mg/l)DLDaily loss proportion, fitted model coefficientiNNitrogen input from fertiliser or plant residue (kg/ha)RainDaily rainfall and irrigation (mm)k1/Fitted model coefficient to calculate DIN runoff concentration on the day of fertiliser applicationRLDIN concentration loss per mm of rainfall / irrigation, fitted model coefficientk.When there were multiple fertiliser applications in a season, the new concentration was calculated as—DIN concentration from the previous day + Ni × 1/k—divisor of the initial nitrogen fertiliser input; DL—the proportion daily loss of DIN; and RL—the loss of DIN per mm of rainfall. The optimised parameter values and the mean absolute error for each of the models are presented in Table Each model was optimised for each of the 25 seasons by minimising the mean absolute error between predicted and measured daily DIN concentrations. The parameters that were optimised in each model were as follows: rainfall model had a lower mean absolute error than the time model in 19 of the 25 year combinations. Overall the rainfall model had a lower total mean absolute error of 5.9 mg/l compared to the time model with 7.4 mg/l. The time and rainfall model had the lowest total absolute error of 5.7 mg/l. Although the time and rainfall model did not have a much lower absolute error than the rainfall model, the optimised parameter values for k and RL were less variable than the rainfall model. In the time and rainfall model, the optimised parameter k which determines the initial runoff DIN concentration ranged from 23 to 314. As the k value and coefficients DL and RL were optimised at the same time, it was possible that a broad range of parameterisations for k, DL and RL could result in solutions similar to the optimal solution. In general, the k values for granular fertilisers  were larger than for fertilisers applied in a liquid form . Therefore, a further optimisation using the time and rainfall model was undertaken based on the form of fertiliser, with three fertiliser forms considered: (a) liquid, (b) granular and (c) incorporated soybean crop.The k, RL and DL were optimised using Microsoft Excel Solver to achieve the maximum Nash–Sutcliffe efficiency for the granular and liquid nitrogen fertiliser applications  was predicted (granular parameters) accurately; however, the load for the treatment with the higher fertiliser application rate (N farm) Fig.  was undeThe DIN model developed in this study was combined with the calibrated HowLeaky model for Victoria Plains to investigate the interaction between long-term climate conditions and DIN runoff losses. The fertiliser management practices investigated were as follows: (a) application timing (i.e. September–December), (b) nitrogen fertiliser application rate and (c) fertiliser form (granular/liquid), with results shown in Fig. Application timing had only a minor effect on the rate of DIN lost in runoff for the low rate of fertiliser application of 85 kg/ha, especially for the liquid fertiliser form. For application rates close to industry standard recommended rates (i.e. 170 kg/ha), application timing did have a significant effect on DIN loads with the December applications having >3 times the runoff DIN loads compared to September applications. For the December application, the granular fertiliser (applied at 170 kg/ha) was nearly twice the rate of DIN loss when compared to the liquid fertiliser.p < 0.05  after liquid fertiliser applicationReduce N fertiliser rates in forecast wet yearsThe study results suggest that the following strategies may be useful to reduce the risk of runoff DIN loads:The model does not include the effects of below ground fertiliser placement compared to surface application or the impacts of banding of fertilisers on the crop row. Both of these are relatively common practices and indicate the potential for further model development. Additionally the model was developed from cane grown in predominantly rainfall fed conditions and may not be applicable for cane regions which have quite different furrow irrigation practices such as in the north Queensland dry tropics region.The daily empirical runoff DIN concentration model developed in this study can be easily incorporated into basic cropping systems models. The model allows for the effects of several key management practices  to be modelled. The simulation study results highlight the risk of late season fertiliser application and suggest that further investigation regarding the utility of a climate forecast to inform fertiliser management decisions be undertaken.


Oreochromis niloticus, and investigated their inhibition of acute bacterial infections by infecting hybrid tilapia (Oreochromis spp.) with Vibrio vulnificus and evaluating the protective effects of pre-treating, co-treating, and post-treating fish with TP3 and TP4. In vivo experiments showed that co-treatment with V. vulnificus and TP3 (20 μg/fish) or TP4 (20 μg/fish) achieved 95.3% and 88.9% survival rates, respectively, after seven days. When we co-injected TP3 or TP4 and V. vulnificus into tilapia and then re-challenged the fish with V. vulnificus after 28 days, the tilapia exhibited survival rates of 35.6% and 42.2%, respectively. Pre-treatment with TP3 (30 μg/fish) or TP4 (20 μg/fish) for 30 minutes prior to V. vulnificus infection resulted in high survival rates of 28.9% and 37.8%, respectively, while post-treatment with TP3 (20 μg/fish or 30 μg/fish) or TP4 (20 μg/fish) 30 minutes after V. vulnificus infection yielded high survival rates of 33.3% and 48.9%. In summary, pre-treating, co-treating, and post-treating fish with TP3 or TP4 all effectively decreased the number of V. vulnificus bacteria and promoted significantly lower mortality rates in tilapia. The minimum inhibitory concentrations (MICs) of TP3 and TP4 that were effective for treating fish infected with V. vulnificus were 7.8 and 62.5 μg/ml, respectively, whereas the MICs of kanamycin and ampicillin were 31.2 and 3.91 μg/ml. The antimicrobial activity of these peptides was confirmed by transmission electron microscopy (TEM) and scanning electron microscopy (SEM), both of which showed that V. vulnificus disrupted the outer membranes of cells, resulting in the loss of cell shape and integrity. We examined whether TP3 and TP4 increased the membrane permeability of V. vulnificus by measuring the fluorescence resulting from the uptake of 1-N-phenyl-naphthylamine (NPN). Treating fish with TP3 and TP4 under different pH and temperature conditions did not significantly increase MIC values, suggesting that temperature and the acid-base environment do not affect AMP function. In addition, the qPCR results showed that TP3 and TP4 influence the expression of immune-responsive genes, including interleukin (IL)-1β, IL-6, and IL-8. In this study, we demonstrate that TP3 and TP4 show potential for development as drugs to combat fish bacterial infections in aquaculture.To address the growing concern over antibiotic-resistant microbial infections in aquatic animals, we tested several promising alternative agents that have emerged as new drug candidates. Specifically, the tilapia piscidins are a group of peptides that possess antimicrobial, wound-healing, and antitumor functions. In this study, we focused on tilapia piscidin 3 (TP3) and TP4, which are peptides derived from  Oreochromis niloticus) antimicrobial peptide, piscidin, was discovered in 2012 and has been shown to perform a variety of biological functions. Five different tilapia piscidin cDNA clones have been isolated and named tilapia piscidin 1 (TP1), TP2, TP3, TP4, and TP5 [The tilapia  of these proteins have revealed that synthetic TP3 and TP4 peptides possess antimicrobial activity when added at 2.44~19.55 μM [Vibrio vulnificus in fish or described their molecular and biological features.Piscidin genes and peptides have been identified in multiple fish species ,9. The sV. vulnificus infections in fish. Interestingly, TP3 and TP4 have demonstrated in vivo antimicrobial activity against V. vulnificus and Streptococcus agalactiae; for example, electrotransfer of the TP3 or TP4 gene into skeletal muscle resulted in enhanced antibacterial and immunomodulatory activity in O. niloticus [Tilapia is one of the most cultivated fish species worldwide. In Taiwan and throughout the Asia-Pacific region, it is cultured in ponds, cement tanks, and FRP tanks. All tilapia are farmed in crowded conditions to maximize profit. This intensive cultivation has been reported to be an important contributing factor in disease outbreaks . AntibioVibrio sp. [V. vulnificus infections include doxycycline, cephalosporin, fluoroquinolone, and trimethoprim-sulfamethoxazole plus aminoglycosides, but due to the emergence of these newly resistant bacteria, there is an urgent need to develop alternative biocontrol agents, such as AMPs. Recently, we demonstrated a high level of activity in a piscidin against carbapenem-resistant Acinetobacter baumannii and NDM-1-producing Klebsiella pneumonia in a mouse model of systemic septicemia [V. vulnificus in tilapia remains unclear.The piscidins are a large family of AMPs, most of which are highly efficacious against both Gram-positive and Gram-negative bacteria. The excessive use of antibiotic agents in aquaculture and agriculture has led to the appearance of antibiotic-resistant strains of bacteria, including brio sp. . The drupticemia . In addiThe aim of this study was to determine whether a combination treatment consisting of both peptide and non-peptide antibiotics would show improved antimicrobial activity over the use of the peptides alone. We applied the MIC technique to study the patterns of antimicrobial activity exhibited by TP3 and TP4 under different conditions . The antimicrobial activity profiles of TP3 and TP4 have previously been characterized in mammal-specific applications; therefore, our study aims to fill gaps in our understanding of these peptides by extending their use to an aquatic environment.V. vulnificus were cultured in water containing diluted MS-222 (100 mg/ml). The frequency of animal monitoring during the survival study were every 30 minutes to observe the tilapia (Oreochromis spp.) condition. Prior to infection and sampling the fish were anesthetized with MS-222 (100 mg/ml) and didn't induce apparent cause of death for those animals. At all sampling times, fish were euthanized using an overdose of MS-222 before collection of organ samples.All experimental procedures involving animals were performed in accordance with the guidelines of Academia Sinica and approved by the Animal Care and Use Committee of Academia Sinica. We employed standardized procedures to euthanize the fish, which involved the use of buffered tricaine methane sulfonate  to induce loss of consciousness and death. Briefly, a 10 g/L stock solution was first prepared and buffered using with bicarbonate (pH 7.0–7.5); we diluted 1 part stock solution in 39 parts water to make a 250 mg/ml working solution. The fish to be euthanized were placed in a transfer container containing diluted MS-222. It usually took 10–15 minutes for death to occur. The fish were considered dead after 10 minutes without breathing (lack of gill movement), and those that were confirmed dead were stored in a refrigerator. To reduce suffering and distress, the fish infected with V. vulnificus cultures were grown in medium under the culture conditions described in a previous report [H-FIHHIIGGLFSVGKHIHSLIHGH-OH) and TP4 (H-FIHHIIGGLFSAGKAIHRLIRRRRR-OH) from GL Biochemistry  and used a solid-phase method to synthesize the synthetic peptides used in this study. These peptides were then purified to a >95% grade using reverse-phase high-performance liquid chromatography. All synthetic peptides were dissolved in ddH2O for all experiments.The s report . We purcV. vulnificus using a broth microdilution method in accordance with NCCLS guidelines [V. vulnificus, we prepared TP3 or TP4 solutions at MIC concentrations of 0.5×, 1×, and 2× and these solutions with equal volumes of V. vulnificus (1×106 CFU/ml) to each well of a 96-well plate. The plates were incubated at 28°C for 0, 60, 120, 180, 360, 540, 720, or 1440 minutes, and after the incubation period, 50 μL of each bacterial solution were plated on a TCBS plate to obtain viable cell counts. Broth grown in the absence of peptides was used as a negative control. The results were determined using triplicate independent experiments.We determined the MICs of TP3, TP4, kanamycin, and ampicillin against idelines . To measV. vulnificus, we prepared TP3 or TP4 solutions at MIC concentrations of 0.5×, 0.25×, 0.125×, 0.0625×, 0.03125×, and 0.015625×, added them to equal volumes of V. vulnificus (5×103 CFU/ml), and placed the resulting solutions in each well of a 96-well plate. The plates were incubated at 28°C for 720 minutes, and after the incubation period, the concentrations of the bacterial solutions were detected using a spectrometer (600-nm absorbance).We used the co-treatment method to test combinations of TP3 or TP4 with ampicillin or kanamycin to identify synergistic effects. To measure the synergistic efficiency of TP3 or TP4 with ampicillin or kanamycin against To understand the effects of pH on TP3 or TP4, the reagents were dissolved in ddH2O, 1 M HCl or 1 M NaOH to obtain solutions with different pH values. For the temperature-dependent functional study, the TP3 or TP4 was added to a solution in a water bath  and incubated for 60 minutes at different temperatures . To evaluate the effects of TP3 and TP4 on pepsin and trypsin function, each peptide was incubated for 10 or 30 minutes with different concentrations of pepsin or trypsin , and we determined the MIC values after incubating these solutions with cells at 28°C for 720 minutes, according to a previously described MIC experimental protocol .V. vulnificus was cultured in TSB medium for 480 minutes at 28°C, and the adjusted culture (1×106 CFU/ml) was aliquoted into different tubes with or without TP4 or TP3. After incubating the cells for 30 minutes, we added 40 μmol/L 1-N-phenylnaphthylamine (NPN) and continued to incubate the cells. Tubes containing PBS with NPN and bacterial cells with NPN served as controls. The NPN fluorescence intensity was detected using a fluorescence ELISA reader. All experiments were performed in triplicate, and the results are expressed as means with standard errors (SE).We used previously reported methods for the membrane perturbation assay . BrieflyV. vulnificus cells. Vibrio vulnificus cultures were grown for 480 minutes at 28°C, and we then added different concentrations of TP3 or TP4 and incubated the cells for 60 minutes. We then centrifuged the cells at 8000 x g for 5 min and washed and resuspended the cells in pre-fix buffer. The pre-fix buffer for SEM consisted of 2.5% glutaraldehyde in 0.1 M sodium cacodylate. The pre-fix buffer for TEM consisted of 4% paraformaldehyde and 2.5% glutaraldehyde in 0.1 M sodium cacodylate. After pre-fixing the cells in the buffer, we performed the following experimental steps at the ICOB core imaging facilities (http://icob.sinica.edu.tw/pubweb/image-core/) [We used transmission electron microscopy (TEM) and scanning electron microscopy (SEM) to evaluate the membrane integrity of e-core/) .Oreochromis spp.) from a commercial aquaculture company. The fish body lengths were 4.0±0.6 cm, and body weights were 3.1±0.3 g. The tilapia were maintained in a 2000 liter indoor aquarium at the Marine Research Station, Ilan, Taiwan. To study the efficacy with which TP3 and TP4 protect tilapia against V. vulnificus, we injected the bacteria into the abdominal cavities (peritoneum) of the tilapia using a syringe ; control tilapia were injected with PBS-buffered saline. For the first trial in each group, we used 15 tilapia: (a) group 1 was injected with V. vulnificus (2×105 CFU/fish) only; (b) group 2 was injected with PBS only; and (c) group 3 was injected with bacterial cells (2×105 CFU/fish) combined with a mixture containing both TP3 and TP4 peptides  that had been incubated for 60 minutes at 28°C. Next, at 168 hours after the first injection, the tilapia that survived the first co-treatment were again injected with V. vulnificus (2×105 CFU/fish). For this second challenge, we chose tilapia with similar body weights and ages that had not been previously treated with V. vulnificus, TP3 or TP4 for the V. vulnificus-only group (control group), and we recorded the survival rate over seven days. For the third trial, each group contained 15 tilapia, each of which was injected with 20, 30, or 40 μg of TP3 or TP4 followed by V. vulnificus (2×105 CFU/fish) after 0.5, 1, or 2 hours. The survival rate was recorded after seven days. For the fourth trial, each group contained 15 tilapia, each of which was first injected with V. vulnificus (2×105 CFU/fish) and then with 20, 30, or 40 μg of TP3 or TP4 after 0.5, 1, or 2 hours; the survival rate was recorded over seven days. Each experimental group consisted of 15 fish per treatment and three replicates (triplicate groups of 15 fish per treatment). We performed multiple group comparisons by analysis of variance (ANOVA) using SPSS software, and pairwise comparisons of groups were performed using a t-test. Significant differences were indicated as *P<0.05 and **P<0.01.We obtained tilapia . The experiment was conducted in strict accordance with the guidelines of the Animal Care and Use Committee of Academia Sinica and the regulations governing the use of animals in experimentation, and the protocol was approved by the Academia Sinica Animal Research Authority (permit no. 13-12-609). All efforts were made to minimize suffering and stress, both during handling and sampling. Humane endpoints were used, and any fish that showed signs of disease or abnormal behavior  was euthanized by a quick blow to the head followed by dislocation of the cervical vertebra. At all sampling times, fish were almost completely exsanguinated during blood collection and euthanized with an overdose of MS-222 before organ samples were collected.V. vulnificus (2×105 CFU/fish) followed by TP3 or TP4 peptides  0.5 hours later. A second group was first injected with TP3 or TP4 peptides  and then, 0.5 hours later, with V. vulnificus (2×105 CFU/fish). A third group of tilapia was simultaneously injected (co-treated) with V. vulnificus (2×105 CFU/fish) and TP3 or TP4 peptides . Liver samples were obtained from each group of tilapia at 3, 6, 9, 12, 24, and 48 hours after the final treatment and the tissues were homogenized in TSB medium before being spread onto TCBS plates. We incubated the plates at 28°C for 12 hours and then counted the number of bacterial colonies.Three groups of fish were used for these experiments. The first group was first injected with V. vulnificus (2×105 CFU/fish) and one that was only injected with peptides (20 μg/fish). Samples were collected at 3, 6, 12, 24, and 48 hours after treatment to extract RNA, and the levels of tilapia total RNA obtained from the liver and spleen were determined with comparative real-time qRT-PCR analysis of all experimental groups. Real-time qRT-PCR was used to detect the levels of IL-1β (GenBank accession no. DQ061114.1), IL-6 (GenBank accession no. XM_005478656), IL-8 (GenBank accession no. NM001279706), Mcp-8 (GenBank accession no. XM_005478749) and β-defensin (GenBank accession no. KF294753). mRNA was isolated and transcribed into complementary first strands (c) according to previously published methods for real-time comparative qPCR to obtain DNA and detect the relative expression levels of each gene [Total RNA was isolated from the tilapia by peptide treatment before, concurrent with and after infection as described above. The groups included one that was only injected with ach gene . The priOreochromis hybrids, Tilapia spp., with a mean body length of 32.33±1.5 cm and a mean body weight of 1117±78.2 g) after intravenous administration of a single dose of 0.2 mg/kg of peptide. The TP3 and TP4 concentrations in serum samples were determined at 10, 30, 60, 120, 180, 240, 300, and 360 minutes for TP3 and at 10, 60, 120, 180, 240, 300, and 360 minutes after dosing for TP4. At each sample collection time point, we anesthetized three fish and collected their blood. The blood was centrifuged to obtain fish serum, which was assessed by liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) at Mission Biotech .The peptide half-life of TP3 and TP4 were investigated in male tilapia  of TP3 or TP4 against V. vulnificus, so we further examined the bactericidal effects of TP3 and TP4 against V. vulnificus by determining their time-kill curves. TP3 and TP4 exhibited dose-dependent bactericidal effects, which were defined as a ≥3 lg decrease in the initial inoculum . The results showed that treatment with 8 μg/ml TP4 increased fluorescence, while 60 μg/ml TP3 was required to increase fluorescence, indicating that TP4 permeabilized bacterial cell membranes more effectively than TP3  for 0.5, 1, or 2 hours before injecting the fish with 20 μg, 30 μg, or 40 μg of TP3 or TP4 to evaluate mortality. When the fish were pre-treated with an injection of V. vulnificus (2x104 CFU/fish) followed by an injection of TP3 (20 μg/fish) after 0.5, 1, or 2 hours, the survival rates were 33.3%, 20%, and 0%, respectively, at the end of the seven-day experimental period (V. vulnificus (2x104 CFU/fish) and then TP3 (30 μg/fish) resulted in survival rates of 33.3%, 15.5%, and 4.5% after 0.5, 1, or 2 hours, respectively, at the end of the seven-day experimental period (V. vulnificus (2x104 CFU/fish) followed by an injection of TP3 (40 μg/fish) after 0.5, 1, or 2 hours, the survival rates were 24.4%, 8.9%, and 0%, respectively, at the end of the seven-day experimental period (V. vulnificus (2x104 CFU/fish) and then injected the fish with TP4 at 20 μg/fish, 30 μg/fish, or 40 μg/fish after 0.5, 1, or 2 hours. Pre-treating the fish in this way resulted in survival rates of 48.9%, 22.2%, and 4%, respectively, at the end of the seven-day experimental period (V. vulnificus (2x104 CFU/fish) followed by an injection of TP4 at a dose of 30 μg/fish after 0.5, 1, or 2 hours, the survival rates were 40%, 20%, and 0%, respectively, at the end of the seven-day experimental period (V. vulnificus (2x104 CFU/fish) followed by an injection of TP4 (30 μg/fish) after 0.5, 1, or 2 hours, the survival rates were 2.2%, 4.4%, and 6.7%, respectively, at the end of the seven-day experimental period , higher survival rates of 13.3%, 2.2%, and 2.2% were achieved after 0.5, 1, or 2 hours, respectively, than those observed in fish injected with V. vulnificus alone. The survival rates were evaluated after 7 days  injected groups 12 hours after treatment . The half-life of the injected TP3 peptide was 120–180 minutes, and that of TP4 was 60 minutes, indicating that TP3 or TP4 may be active in the early stages of infection, so more bacteria were eliminated with higher doses of TP3  or TP4  in solutV. vulnificus is currently developing resistance to many clinically important antibiotics. Because V. vulnificus infections progress rapidly, several therapeutic methods are currently available to treat V. vulnificus infections in humans, such as a combination of tetracycline and cephalosporin or monotherapy with fluoroquinolone, as recommended by the CDC [Vibrio vulnificus bacteria are etiological agents that reside in warm water and cause vibriosis in tilapia, eels and other teleosts in fish farms. Recently, the detection of antimicrobial resistance in Vibrio isolates in aquaculture environments has suggested that resistant Vibrio strains may pervade the food chain. They may therefore eventually reach humans and present a risk to public health [Interest in TP3 and TP4 has grown significantly in recent years because the functions of these factors in bacterial infection therapies have been demonstrated . Current the CDC . Vibrio c health .in vivo conditions, including exposure to different pH, temperature, and protease-rich environments. Recently, we reported on the use of TP4 against Helicobacter pylori infections in vivo and in vitro [V. vulnificus across a range of different pH values, and an important result was that TP3 and TP4 were observed in the buffered sample at pH 7 (control), confirming that the research results for the pH control from the previous study remain valid. At pH 4, pH 10, and pH 12, the TP3 and TP4 peptides assumed an entirely unknown structure that could not be predicted, which may have caused them to lose cationic features that resulted in an increase in MIC values. The unbuffered PGLa samples were significantly acidic and at the edge of the acceptable pH window [V. vulnificus. These results indicate that TP3 and TP4 can remain stable throughout the fish fodder manufacturing process, thereby ensuring the antimicrobial activity of the product. Another study showed that an antimicrobial protein derived from Bacillus subtilis FB123, named BSAMP, was highly thermostable after treatment at 100°C; its antimicrobial activity did not change [in vitro aggregation of the acidic phospholipid dimyristoylphosphatidylserine or interactions that result in a reduction to their cationic charges [To understand how TP3 and TP4 could potentially be used as alternatives to conventional antibiotics, we studied their biochemical stability under different stimulated in vitro . The resH window . These rt change . The app charges .V. vulnificus by promoting vesicular budding, blebbing, and shrinking. We previously reported that the antimicrobial activity of TP4 is correlated with the induction of membrane micelle formation, which leads to membrane depolarization and the extravasation of cellular constituents [V. vulnificus infections. We compared the results to those obtained using a commonly applied V. vulnificus antibiotic treatment regimen (ampicillin and kanamycin). The greatest benefit of integrating the use of TP3 or TP4 with antibiotics is the decrease in the required therapeutic dosage. Lower doses reduce potential side effects, which is an important factor during drug development. We observed significant improvements in MIC values when we used TP3 and TP4 against V. vulnificus, but the synergy between TP3/4 and antibiotics resulted in dramatic decreases in the MICs of both TP3 (from 31.2 to 62.5 μg/ml) and TP4 (from 3.91 to 7.81 μg/ml) against V. vulnificus. In addition, when combined with TP3 or TP4, the antibiotics induced a two-fold decrease in MIC values. The observation that both ampicillin and kanamycin interacted synergistically with TP3 or TP4 suggests the involvement of different mechanisms between these peptides and the applied antibiotics [V. vulnificus CFUs recovered after approximately 6 and 9 hours, respectively, which may due to antimicrobial peptide (AMP) degradation by the bacteria. Because the 1xMIC only presented the AMP minimum inhibitory concentration, bacterial growth and recovery will occur after exhaustion of the AMP molecules. However, this must be verified for both TP3 and TP4 in future experiments.Here, we used NPN uptake assays and SEM to demonstrate that TP3 or TP4 can disrupt membranes at low MIC values. Based on the SEM results, we propose that TP3 or TP4 destabilize the cell membranes of tituents . We deviibiotics ,27. One ibiotics . When weV. vulnificus. Septic shock was induced by intraperitoneal administration of V. vulnificus using experimental methods that have been described in several animal models [V. vulnificus and reduced the number of its bacterial colonies in tilapia. Here, we provide both in vitro and in vivo experimental confirmation that TP3 and TP4 possess potent antimicrobial activity against V. vulnificus and that TP3 and TP4 permeated V. vulnificus membranes and balanced the host immune response in a tilapia model of V. vulnificus infection. Treating the fish with TP3 and TP4 resulted in 100% bacterial clearance of V. vulnificus from the tilapia after 48 hours. Treatment with TP4 has also been previously reported to reduce bacterial (Helicobacter pylori) loads in mice [in vivo, such as using liposome-packaged peptides, nanoparticles, or D-form peptides [V. vulnificus growth either in vitro or in vivo, and they were consistent with previously published data for other peptide treatments such as epinecidin-1 [V. vulnificus-infected tilapia.Prophylactic or post-treatment administration of TP3 or TP4 protected tilapia against serious sepsis when they were infected with l models ,30. The  in mice . There apeptides ,32, but ecidin-1 . Taken tV. vulnificus infection after administration of TP3 or TP4 via different treatment methods, we analyzed the qPCR experimental results, which are presented in the supporting information. These results indicated that the TP2, TP3, TP4 or β-defensin antimicrobial peptides were down-regulated in the liver in response to either TP3 or TP4 treatment alone or in co-treatment groups 3 hours after treatment. These results suggest that immunomodulation of antimicrobial peptide (AMP)-responsive genes by TP3 or TP4 in the early stages of infection did not enhance AMP gene expression, and this may be a consequence of the TP3 (or TP4) co-treatment with V. vulnificus, in which TP3 (or TP4) destroyed the V. vulnificus membrane and reduced the disease severity after bacterial infection. These results reveal a similar function in tilapia  as found through parallel observations in zebrafish [V. vulnificus VvpE stimulates IL-1β production via hypomethylation of the IL-1β promoter and NF-κB activation in the intestinal epithelial cells [V. vulnificus infection requires further investigation. Tilapia infected with V. vulnificus exhibit severe inflammatory responses characterized by the regulation of proinflammatory cytokines such as mast cell protease 8 (MCP-8), increasing the inflammation caused by sepsis. Mast cell proteases are major components of the secretory granules of mature mast cells, but whether MCP-8 regulates the responses to V. vulnificus infection, as well as the actual mechanism by which V. vulnificus initiates production of these MCP-8-modulated proinflammatory cytokines, remain unclear. We suspect that TP3 (or TP4) may affect tilapia MCP-8 gene expression after V. vulnificus infection and the mast cell protease-dependent proteolysis in tilapia defense responses to invading pathogens [To better understand the responses of tilapia to ebrafish . In partebrafish . The V. al cells , but wheathogens ,37.Overall, TP3 and TP4 are interesting therapeutic candidates that could influence immune-related gene expression in fish. It is now well established that TP3 and TP4 act as antimicrobial and immunomodulatory factors by disrupting membrane structures. A few AMPs, such as Pexiganan (MSI-78), Iseganan (IB-367) and Omiganan , have advanced to phase III trials that will provide new opportunities for treating these types of infections . New typS1 FigV. vulnificus. Data were recorded after 3 hours, 6 hours, 12 hours, 24 hours, 48 hours, 4 days, 5 days, 6 days and 7 days.(a) We monitored bacterial numbers and (b) survival rates after tilapia were infected with different amounts of (PDF)Click here for additional data file.S2 Fig(a) The survival rates of tilapia injected with TP3 at a dose of 0.1 μg/fish, 1 μg/fish, or 10 μg/fish. (b) The percentage of tilapia surviving after injection with TP4 at 0.1 μg/fish, 1 μg/fish, or 10 μg/fish. (c) The percentage of tilapia surviving after injection with TP3 at 20 μg/fish, 30 μg/fish, 40 μg/fish, or 50 μg/fish. (d) The percentage of tilapia surviving after injection with TP4 at 20 μg/fish, 30 μg/fish, 40 μg/fish, or 50 μg/fish. The control group (control) was injected with PBS alone.(PDF)Click here for additional data file.S3 FigVibrio, injected with V. vulnificus alone; TP4, injected with TP4 alone; TP3, injected with TP3 alone; co, co-treatment with AMP and V. vulnificus; pre, prior treatment with AMP followed by infection with V. vulnificus; post, infection with V. vulnificus followed by treatment with AMP.(a) TP3-treated livers, (b) TP3-treated spleens, (c) TP4-treated livers, and (d) TP4-treated spleens. Comparative RT-PCR analysis of the mRNA gene expression levels of immune-related genes. The evaluated genes are shown in (PDF)Click here for additional data file.S4 Fig(a) Pharmacokinetic curve for tilapia after injection of a single dose  of TP3 and (b) TP4. Serum concentrations were determined by intravenous sampling at each time point, and piscidin concentrations were determined by liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS).(PDF)Click here for additional data file.


Marlieke de Kraker and colleagues reflect on the need for better global estimates for the burden of antimicrobial resistance. A recent high profile report estimates that, by 2050, 10 million people will die every year due to antimicrobial resistance (AMR) unless a global response to the problem of AMR is mounted.There is undoubtedly a large clinical and public health burden associated with AMR, but it is challenging to quantify the associated excess morbidity and mortality.When estimates of the burden of AMR are provided, they should be accompanied by clear acknowledgment of the associated uncertainties regarding the incidence of infections, the prevalence of resistance, and the attributable mortality.Predictions always require assumptions, but modeling future scenarios using unreliable contemporary estimates is of questionable utility.Current global estimates of the burden of AMR are not very informative; we need detailed, reliable data to be able to improve AMR control measures, preferably based on comprehensive, population-based surveillance data from low-, middle-, and high-income countries.In 2014, Lord Jim O’Neill and his team published a review commissioned by the United Kingdom government entitled, “Antimicrobial Resistance: Tackling a crisis for the health and wealth of nations” (the AMR Review) . HoweverThe first international AMR burden estimates stem from the European Centre for Disease Prevention and Control (ECDC) report “The bacterial challenge: Time to react”  in 2009.Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus) for European countries are derived from the European Antimicrobial Resistance Surveillance network (EARS-Net). However, this is not a population-based surveillance network; EARS-Net only records invasive infections diagnosed in hospitals and for a variable proportion of the total number of hospitals in each country. Tertiary care hospitals are much more likely to participate in this program than smaller hospitals  were selected. The models in both the ECDC report and AMR Review multiplied the national number of bloodstream infections (BSIs) by the national resistance proportions as reported by EARS-Net and the WHO, for European and non-European countries, respectively.The second step to determine the burden of AMR is to estimate the number of infections caused by pathogens that are resistant to the antibiotic (or antibiotic class) of interest. For the AMR Review , third-gA general problem with utilizing resistance proportion data from AMR surveillance networks is variability in the frequency of blood culture sampling. Blood culturing habits can greatly influence the estimated proportion of resistance. Consider the two following scenarios. If few patients are cultured—for example, the very ill or those failing standard empiric therapy—resistant strains will be over-represented, resulting in a high resistance proportion. At the other extreme, if all patients are cultured, this will dilute the number of resistant pathogens identified, and the estimated resistance proportion will be lower. In the same scenarios, resistance rates  will still be correct . TherefoE. coli and K. pneumoniae, and MRSA, the ECDC based these ratios on data from two studies: a multicenter study in Brooklyn  [Like most laboratory-based infection surveillance networks for health care–associated infections, EARS-Net  only incia BSIs)  and a siia BSIs) , with daUsing the three problematic calculation steps discussed above, the (inter)national number of resistant BSIs, LRTIs, SSIs, and UTIs was estimated for 2007 (ECDC) and 2012 (AMR Review), respectively. The next step in estimating the burden of AMR is to multiply estimates of the absolute number of resistant infections by a certain “per-infection” burden measure. The AMR Review  report bAlthough the ECDC report  only proAlthough the results from these burden reports are often cited, none of these burden estimates themselves have been published in peer-reviewed literature. The question is whether they would endure scientific scrutiny. KPMG  states tClearly, there is a need for more reliable AMR burden estimates, including uncertainty boundaries, and more careful modeling of future scenarios, including sensitivity analyses. The key prerequisite for that is more comprehensive antimicrobial resistance surveillance data, especially for low- and middle-income countries and especially for community-acquired infections. The next step would be to provide AMR-related morbidity and mortality data through these population-based surveillance networks. Demographic data would further enable age- and gender-specific estimates, making detailed results available upon which the most effective AMR control measures can be built. Until these types of data are available, global AMR burden estimates are not reliable and will not be able to inform meaningful action. At a minimum, these estimates should be reported with more transparency and be interpreted with caution.In September 2016, the UN convened a General Assembly in New York to summon strong political commitment in addressing AMR. Although it is too early to evaluate any true advancement, countries reaffirmed their commitment to develop national action plans on AMR based on the WHO Global Action Plan on Antimicrobial Resistance (2015). This plan has five objectives, of which the first two focus on awareness and understanding of AMR through surveillance and research. At the same time, a group of (inter)national organizations have joined forces to form the Conscience of Antimicrobial Resistance Action (CARA) to hold the UN and other governmental bodies to the commitments they have made. Hopefully, these renewed national commitments and the positive influence from CARA will result in invigorated initiatives for accurate, population-based AMR surveillance, including burden of disease monitoring on a global scale.


While an extensive literature supports the notion that mesocorticolimbic dopamine plays a role in negative reinforcement, recent evidence suggests that dopamine exclusively encodes the value of positive reinforcement. In the present study, we employed a behavioral economics approach to investigate whether dopamine plays a role in the valuation of negative reinforcement. Using rats as subjects, we first applied fast-scan cyclic voltammetry (FSCV) to determine that dopamine concentration decreases with the number of lever presses required to avoid electrical footshock . Analysis of the rate of decay of avoidance demand curves, which depict an inverse relationship between avoidance and increasing price, allows for inference of the worth an animal places on avoidance outcomes. Rapidly decaying demand curves indicate increased price sensitivity, or low worth placed on avoidance outcomes, while slow rates of decay indicate reduced price sensitivity, or greater worth placed on avoidance outcomes. We therefore used optogenetics to assess how inducing dopamine release causally modifies the demand to avoid electrical footshock in an economic setting. Increasing release at an avoidance predictive cue made animals more sensitive to price, consistent with a negative reward prediction error . Increasing release at avoidance made animals less sensitive to price, consistent with a positive reward prediction error . These data demonstrate that transient dopamine release events represent the value of avoidance outcomes and can predictably modify the demand to avoid. We also found that increasing dopamine at an avoidance predictive cue decreased avoidance, consistent with a negative prediction error. In contrast, increasing release at successful avoidance increased avoidance, consistent with a positive prediction error. These data demonstrate that transient dopamine release events represent the value of avoidance outcomes and capably modify avoidance.Dopamine is thought to play a crucial role in reward learning and directing actions toward beneficial outcomes. While the avoidance of harmful stimuli is similarly pertinent to an organism’s survival, the role of dopamine in avoidance remains controversial. Using Dopamine release events within the mesocorticolimbic pathway actively guide behavior in positive reinforcement, where behavior is strengthened by the occurrence of a rewarding event . A growiAn extensive body of literature suggests that dopamine also plays a role in avoiding harm . Dopamine terminal lesions  and dopaTo investigate the role of dopamine in the valuation of avoidance, we used a behavioral economics task in which rats were presented with an avoidance predictive cue and provided the opportunity to avoid the onset of electrical footshock by responding on a lever. We then increased the price of avoidance by increasing the number of lever presses required to avoid footshock at fixed intervals over the course of a session. To measure changes in price sensitivity, we generated demand curves to model avoidance as a function of price. The rate at which these demand curves decay depicts price sensitivity and allows for inference of the worth an animal places on an outcome.If, as in reward seeking ; 2017, dAs hypothesized, dopamine scaled inversely with cost; however, both dopamine and avoidance were concurrently attenuated at session onset. Augmenting dopamine release at an avoidance predictive cue rendered animals more sensitive to avoidance costs. We attribute this finding to a negative reward prediction error, whereby the animal perceives they received a worse value than anticipated when they receive the same amplitude of electrical footshock. Increasing release at successful avoidance made animal less sensitive to avoidance costs. We attribute this finding to a positive reward prediction error, whereby the animal perceives they received a better value than anticipated despite still receiving footshock in other trials. From these data, we conclude that dopamine release events represent the value of avoidance and casually modify the demand to avoid.ad libitum. Surgeries were conducted at 300–350 g using Kopf stereotaxic equipment with rats anesthetized at 5% isoflurane and maintained at 2 ± 1%. For FSCV, rats were implanted with a microdialysis guide cannula (BASi) targeted at the nucleus accumbens (NAcc) core  of the right hemisphere and a contralateral Ag/AgCl reference electrode. For optogenetic surgeries, rats were unilaterally transfected with 4 µl of a Cre-dependent virus (rAAV2/EF1a-DIO-hChR2(H134R)-EYFP; UNC Vector Core) targeted at the ventral tegmental area (VTA). A total of 1-µl viral aliquots were infused at four areas surrounding the VTA  at a rate of 50 nl/min. A fiber optic cannula  was then implanted unilaterally, directed at the VTA . These methods were used for both the transgenic rats as well as wild-type (WT) counterparts, which served as controls in optogenetic experiments. After surgery, rats were given >3 d to recover during which time each received a daily 3-ml intraperitoneal injection of a 1% carprofen solution to reduce inflammation and postoperative pain. All animal procedures were performed in accordance with the University of Colorado Denver animal care committee's regulations.Male Long–Evans rats provided by Charles River Laboratories as well as Transgenic rats (LE-Tg(TH-Cre)3.1Deis) expressing Cre-recombinase under the tyrosine hydroxylase (TH) promotor (TH::Cre±) supplied by Rat Resource and Research Center were used as subjects. Rats were singly housed and maintained on a 12/12 h light/dark cycle with the dark cycle beginning at 10 A.M. All experiments were conducted during the dark (active) cycle with food, water, and crinkle paper enrichment provided Rats were maintained on a daily training schedule (7 d/week) within operant boxes (Med-Associates) outfitted with footshock grid floors. Rats were first trained to escape electrical footshock with each daily escape-only session lasting 15 min. At the onset of each session, both an active and inactive lever were extended, a cue light placed above the active lever was illuminated and 0.5-mA electrical current  was applied to the grid floor of the operant chamber. A response on the active lever terminated the ongoing foot shock and allowed the rat to escape into a 30-s safety period accompanied by a tone, while a response on the inactive lever had no effect. This safety signal played for the entirety of the safety period, the end of which coincided with the onset of the next escape trial. In this initial training task, escape behavior was shaped by a researcher who could simulate a lever response using a wireless keyboard, thereby reinforcing a series of behaviors that would lead to the acquisition of operant escape. The experimenter first shaped the animal to the quadrant of the operant box containing the extended lever. They then reinforced rearing behavior in front of the lever before finally requiring the rat to respond on the lever to self-terminate electrical footshock. This training persisted until the animal demonstrated an association between lever response and shock termination through consistent and researcher-independent escape .Following the acquisition of escape behavior animals were moved into a daily 1-hr avoidance task in which reinforcement was maintained under a fixed ratio1 (FR1) schedule of reinforcement. This task added the potential for an avoidance outcome. Each session was initiated by the extension of both an active an inactive lever and the illumination of a cue light placed directly above the active lever. In each trial, rats were given 1s from cue presentation to respond on the active lever to successfully avoid footshock. If rats failed to respond, recurrent footshock  was applied until a lever response was made to escape further shock. Responses made on the inactive lever had no effect on behavioral outcome. Rats remained on this task until they consistently performed  ≥50% avoidance.After successful acquisition of 50% avoidance under an FR1 schedule, rats moved into a behavioral economics-based shock avoidance task. Here, the unit-price (response requirement/mA shock avoided) increased throughout each session by increasing the response requirement to both avoid or escape footshock. Within this task, the unit-price epoch duration increased in length to allow 20 avoidance opportunities and provide sufficient time to meet increasing response requirements as well as to account for safety period duration following avoidance or escape responses. B. Once aUnit-price was additionally manipulated through changes in the mA of shock received. Within this task, the response requirement was held constant at an FR2 and rats were given 2 s to respond before the onset of a 0.5-s footshock across six unit-prices A, upper.We further attempted to address order effect confounds within the ascending response requirement task by randomizing the presentation of five unit-prices within a single session , upper. Within all tasks, the cue was defined as the presentation of a lever and the illumination of a light above the lever which was also accompanied by white noise. Both an escape or avoidance response resulted in the retraction of the lever, the dimming of the light, termination of the white noise, as well as the beginning of the 30-s safety tone and illumination of a secondary house light for the duration of the safety period.n = 7) were performed during the economics-based task. For these recordings, glass carbon-fiber electrodes were lowered into the NAcc using micromanipulators  and locked into place at a depth where transient dopamine release events were apparent. Electrodes were first cycled at 60 Hz in vivo for 30–40 min before being reduced to 10 Hz for data collection. An initial wave form  was applied which allowed for the detection of dopamine via FSCVs taken every 100 ms. To extract the dopamine component, principle component regression (PCR) was applied to the raw voltammetric data as previously described . Specifically, DA and pH were resolved from the FSCV recordings using recording-specific training sets (n = 7/anylate) to produce pH background-subtracted (10 consecutive scans) dopamine concentration files. To increase the validity of calibration factors for dopamine assessment, we applied a recently developed computational model  designed to calculate calibration factors for individual electrodes by applying known constants to background current values from each in vivo recording. By replicating Roberts et al. (2013), using 10 electrodes, we obtained a set of empirical values using multiple linear regression analysis. Our lab-specific coefficients are: α = 4.71e−5, β = 17.185, γ = 8.324, δ = −0.656. Using these coefficients, we can calculate calibration factors for individual electrodes used in vivo by simply entering the observed total background current and the switching potential used for each individual recording. For additional information see the supplemental information of FSCV recordings . Voltammograms which contained excessive electrical noise were excluded from this analysis.We used different approaches to analyze dopamine concentration at the avoidance predictive cue versus throughout the safety period. The concentration of dopamine at the presentation of the cue preceding avoidance was defined as the peak concentration ±0.5 s surrounding the event. Avoidance predictive cue-associated dopamine concentrations from individual trials were aggregated, split according to avoidance or escape outcome, and averaged across all animals per unit-price for analysis A,C. VoltAs previously described , dopaminThe pattern of dopamine release during the safety period was distinct as this period is not transient; rather, each safety period lasted 30 s in duration. Thus, to more accurately assess dopamine transient activity during the safety period, rather than analyzing mean dopamine concentration at the onset of the 30-s safety signal we performed an analysis of the amplitude of individual transient events throughout this period. A custom MATLAB program previously described by y-axis against unit-price on the x-axis.Demand curves depict the relationship between the consumption of a commodity (in this case avoidance) and changing unit-price. Because demand decreases or decays with increasing price, the desirability of a given commodity may be inferred based on the relative rate of decay of a demand curve. More rapidly decaying demand curves indicate lower demand, or heightened sensitivity to increasing price, while more gradually decaying demand curves indicated greater demand for a given commodity, or reduced sensitivity to increasing price. to generate demand curves depicting avoidance as a function of increasing price. In order to generate demand curves depicting avoidance as a function of increasing price, the avoidance responding observed within the task was fit to an exponentially decaying model though a custom MATLAB script using nonlinear least squares. Within this analysis, total avoidance per unit-price epoch was graphed on the Analysis revealed that exclusion of unit-price 2 resp/mA, at which attenuated avoidance responding was observed, generated lower ulations .n = 10) as well as the WT control group (n = 10) were given 30 d following surgery before optogenetic stimulation. Both groups received intracranial blue light (473 nm) delivered at 10 pulses, 20 Hz, 0.5-s duration from a laser (opto-engine) controlled by a custom Arduino system (Ng-Evans). Laser output was determined through the Stanford brain transmission calculator to produce a 1mm cone of light of 1 mW/mm2 within the brain tissue with a 15-mW output from the ferrule cannula tip and was designed to encompass exclusively the VTA dopamine cell bodies. Stimulation was unilaterally applied to the right hemisphere in all animals. These stimulation parameters have previously been used within the lab and have demonstrated successful augmentation of dopamine within the NAcc  protein, both the transgenic TH-Cre group  were placed in locomotor chambers and their movement was tracked using Med-Associates Activity Software. Rats first acclimated to the chambers over the course of 1 h before immediately moving into either a 1-h “stimulation” paradigm wherein they received optogenetic stimulation every 30 s, paralleling the frequency of stimulation animals receive within the economic based avoidance task, or a “baseline” paradigm wherein rats attached to a mock fiber optic patch cable received no stimulation. These conditions were counterbalanced against each other and total distance moved every 5 min was analyzed for both conditions  water for 15 min followed by 1-min submersions in 70% ethanol, 50% ethanol, and two washes in DI water. Tissue was then soaked in Crysal Violet for 1 min, after which it was bathed in two 1-min washes in DI water followed by 15-s washes in 50%, 70%, 95%, and 100% ethanol. This was followed by a ≥8-min wash in Histo-Clear. Once complete, slides were mounted with Paramount and imaged to confirm lesion placement  and price. Demand curves usually show a negative gradient , where consumption decreases with increasing price. The rate at which the negative slope decays can be used to make inferences regarding the value individuals place on the commodity being consumed. When demand curves decay at a faster rate they are said to be more elastic. Price elasticity of demand is defined as the change in the quantity of the commodity being consumed in response to an increase in price. In the present study, the number of successful avoidance responses at each price represents the quantity of the demanded commodity. We measure the elasticity of demand by computing the variable α, which represents the cost at which the elasticity of demand is exactly −1, meaning consumption drops by one percentage in response to a one percentage increase in price. A higher α-value indicates the demand for the good is more elastic, suggesting the value of the commodity is diminished. In contrast, a lower α-value indicates the demand for the good is relatively inelastic, suggesting the value of the commodity is enhanced.To assess the role of mesocorticolimbic dopamine release events in the valuation of avoidance, we used a behavioral economic-based shock avoidance task. Our approach both builds on previous within session designs that characterized the demand for sucrose and cocaine  as well Within the selected ascending response requirement task, a compound cue signaled the opportunity to respond on a lever in order avoid an unchanging electrical footshock . Failure to meet the response requirement within a set timeframe resulted in recurrent footshock until the full response requirement was met. This outcome is defined as escape. Successfully meeting the response requirement within a set timeframe resulted in a safety period signaled by a tone without the occurrence of footshock. This outcome is defined as avoidance. Following either avoidance or escape, a tone accompanied by house light illumination signaled a 30-s safety period A. The enWhile data were primarily analyzed in terms of successful avoidance outcomes at each unit-price, note that the additional delay required to meet increasing response requirements adds a conceptually important opportunity cost  = 9.87, p < 0.001; Tukey post hoc: start of training vs end of training p < 0.001; This task allowed us to generate within session demand curves by plotting total avoidance responses per epoch against unit-price. Unique demand curves emerged over the course of acquisition of the economic task, with an attenuation of avoidance at 2 resp/mA becoming apparent in experienced animals A. The raTo evaluate the role of NAcc dopamine during the valuation of avoidance, we employed FSCV to measure transient changes in dopamine concentration time locked ±0.5 s) to associative cues in the behavioral economics-based task. We exclusively analyzed dopamine concentration within the second through fourth unit-price because, 100% of animals maintained responding in this range and a concurrent attenuation in behavior and dopamine concentration was observed at the first price point. We independently address these attenuated responses later in the manuscript. The nA changes in current were converted to nM concentration by using PCR and lab-specific computational factors . Dopamine concentration files were arranged around one of two events: (1) avoidance predictive cue and (2) safety associated cue. Dopamine at the avoidance predictive cue was quantified and analyzed as a group mean because the mean data were representative of individual trials cf. C vs 5A,B s to assF = 29.507, p < 0.001; Tukey post hoc: unit-price 4 vs 6 p < 0.001, 4 vs 10 p < 0.001; F = 3.916, p = 0.049; Tukey post hoc: unit-price 4 vs 10 p = 0.040; F = 2.14; p = 0.14; In successful avoidance trials we found that dopamine concentration at the avoidance predictive cue scaled inversely to unit-price [one-way repeated measures (RM) ANOVA: F = 3.50, p = 0.037; Tukey post hoc: unit-price 2 vs 10 p = 0.029; F = 0.902; p = 0.460; We further analyzed the amplitude of dopamine transient events during the 30-s safety period following both avoidance and escape outcomes. Unlike dopamine concentration transients time locked to cue presentation, averaged safety period color plots (bottom) and corresponding concentration traces (top) following avoidance A and escC representing unit-price. Notably, α is inversely related to avoidance performance, with lower α values signifying higher avoidance while larger α values reflect lower avoidance (2 ((n1=n2=272) = 20155.0, p < 0.001; R2 values  = 17.88, p < 0.001; Tukey post hoc: baseline-1 vs cue p = 0.017, baseline-2 vs avoid p = 0.017, cue vs avoid p = 0.003, baseline-1 vs baseline-2 p = 0.072; 2(3) = 1.08, p = 0.78; F = 0.824, p = 0.49; Cre escape F = 2.87, p = 0.055; Friedman RM ANOVA on ranks: WT avoidance: X2(3) = 1.2, p = 0.75; WT escape: X2(3) = 2.0, p = 0.56). As in reward seeking  while stimulation at successful avoidance significantly decreased α (increased demand to avoid). Cue associated baseline and avoidance associated baseline were not significantly different  = 3.76, p = 0.022; Tukey post hoc: baseline-1 vs cue p = 0.28, baseline-2 vs avoid p = 0.042). Conversely, the WT group demonstrated no change in attenuated avoidance in response to optical stimulation  = 1.00, p = 0.41; We additionally sought to analyze the attenuation of avoidance at 2 resp/mA A. Dopamit test: t(7) = 1.59, p = 0.15; t test: t(7) = −0.363, p = 0.727), suggesting changes in overall activity played a minimal role in our demand profiles. On completion of the voltammetric experiments, animals were sacrificed and electric lesions at the depth of the recording site confirmed electrode placement within the NAcc ; however, dopamine only decreased with price at the safety associated cue following successful avoidance. We interpret these distinct outcome-specific responses to suggest that dopamine concentration before the behavioral action was predictive of value, whereas dopamine concentration following action was reflective of the outcomes value.We next sought to assess the causal role of dopamine in the valuation of avoidance within an economic framework. A central principle of economics is that as the price of a commodity increases, its demand decreases. This principle is commonly demonstrated using demand curves, in which consumption of a commodity is plotted against price. According to the law of demand, consumption typically decreases with increasing price. The resulting negative gradient represents the elasticity of demand, or how sensitive consumption of the commodity is to increasing price. In the present study, consumption is defined as the number of successful avoidance responses at each price (responses/mA). If avoidance became more sensitive to price, the resulting demand curve would decay at a faster rate; if avoidance became less sensitive to price, the resulting demand curve would decay at a slower rate. We can then make inferences regarding the value of avoidance by measuring the rate of decay. We compute the rate at which demand curves decay by solving for the variable α, which represents the cost at which the elasticity of demand is exactly −1. At this point, consumption drops by one percentage in response to a one percentage increase in price. A higher α-value indicates the demand for the good is more elastic, suggesting the value of the commodity is diminished. In contrast, a lower α-value indicates the demand for the good is relatively inelastic, suggesting the value of the commodity is enhanced. In accordance with our previous work assessing the role of dopamine in the valuation of a sugar reward , we predOptically stimulating dopamine cell bodies in the VTA at an avoidance predictive cue rendered animals more sensitive to price , consistent with a negative reward prediction error. We infer that heightened release at cue presentation signaled a beneficial outcome, a prediction that was then violated by the occurrence of footshock outcomes of the same amplitude. Optically increasing release at successful avoidance made animals less sensitive to price , consistent with a positive reward prediction error. We infer that heightened release at successful avoidance signaled the outcome was better than predicted, indicating a good value worth seeking. Our data build on the notion that transient dopamine release events can represent subjective value  and furtThe mesocorticolimbic pathway originates from dopamine neurons in the VTA and projects to motivational circuitry throughout the brain, most prominently the NAcc of the basal ganglia. The NAcc is thought to integrate transient dopamine signals with an array of converging neural input to generate goal directed actions via the basal ganglia . Both thIt is important to note that there are distinct forms of avoidance and dopamine may play unique roles in each. For example, if transient dopamine release events are significant for action generation, then dopamine release should be suppressed in passive avoidance, a situation where animals must inhibit action to avoid a negative outcome . UnsignaIn contrast to active avoidance, transient dopamine release is suppressed by unavoidable aversive events and their associative stimuli. Using FSCV, the Roitman group has demonstrated that a variety of aversive stimuli transiently decrease accumbal dopamine concentration . SimilarDopamine responses in active avoidance further depend on the behavioral history of the subject and the behavioral context in which avoidance is assessed. Notably, our observations here are discrepant from a previous FSCV characterization of dopamine in signaled active avoidance , which oDopamine responses at the avoidance predictive cue depend on the behavioral outcome (avoidance vs escape). We observed distinct responses to avoidance associative cues depending on whether animals avoided or escaped footshock. During successful avoidance, cue-evoked dopamine concentration scaled with changing price, resulting from both an increase in effort and opportunity costs, and corresponded to the avoidance outcome. During escape outcomes, cue-evoked dopamine concentration scaled with price irrespective of behavior. We interpret the distinct responses at the avoidance predictive cue to suggest that dopamine is continually representing avoidance value but is being simultaneously attenuated with behavior at session onset. We surmise this concurrent attenuation at session onset results from afferent inhibitory input, possibly from the lateral habenula via the rostromedial tegmentum .Dopamine responses during the safety period also depend on the behavioral outcome. We observed dopamine concentration scaled with price during the signaled safety period when animals successfully avoided footshock, but not following escape. The distinct dopamine responses observed during the safety period may be relevant in the context of avoidance learning. Successfully avoiding an aversive event was the optimal outcome under our experimental conditions. Thus, dopamine might exclusively convey value during the safety period after optimal outcomes, thereby promoting their recurrence. While entering safety after escape is a beneficial outcome as well, dopamine may fail to represent the value of this less optimal outcome. Rather, we reason that dopamine generally represents the safety signal proceeding escape as a positive relief from pain .Avoidance outcomes produce unique behavioral and neurochemical responses when compared to rewarding outcomes , suggestIn conclusion, we demonstrate that accumbal transient dopamine release events scale proportionally to the value of avoidance outcomes and capably modify the valuation of active avoidance. Our data refute the notion that mesocorticolimbic dopamine is exclusively involved in positive reinforcement  and, rat