A new method is presented for extraction of population firing-rate models forboth thalamocortical and intracortical signal transfer based on stimulus-evokeddata from simultaneous thalamic single-electrode and cortical recordings usinglinear (laminar) multielectrodes in the rat barrel system. Time-dependentpopulation firing rates for granular (layer 4), supragranular (layer 2/3), andinfragranular (layer 5) populations in a barrel column and the thalamicpopulation in the homologous barreloid are extracted from the high-frequencyportion  of the recorded extracellular signals. Theseextracted firing rates are in turn used to identify population firing-ratemodels formulated as integral equations with exponentially decaying couplingkernels, allowing for straightforward transformation to the more commonfiring-rate formulation in terms of differential equations. Optimal modelstructures and model parameters are identified by minimizing the deviationbetween model firing rates and the experimentally extracted population firingrates. For the thalamocortical transfer, the experimental data favor a modelwith fast feedforward excitation from thalamus to the layer-4 laminar populationcombined with a slower inhibitory process due to feedforward and/or recurrentconnections and mixed linear-parabolic activation functions. The extractedfiring rates of the various cortical laminar populations are found to exhibitstrong temporal correlations for the present experimental paradigm, and simplefeedforward population firing-rate models combined with linear or mixedlinear-parabolic activation function are found to provide excellent fits to thedata. The identified thalamocortical and intracortical network models are thusfound to be qualitatively very different. While the thalamocortical circuit isoptimally stimulated by rapid changes in the thalamic firing rate, theintracortical circuits are low-pass and respond most strongly to slowly varyinginputs from the cortical layer-4 population. Many of the salient features of individual cortical neurons appear wellunderstood, and several mathematical models describing their physiologicalproperties have been developed. The present understanding of the highlyinterconnected cortical neural networks is much more limited. Lack of relevantexperimental data has in general prevented the construction and rigorous testingof biologically realistic cortical network models. Here we present a new methodfor extracting such models. In particular we estimate specific mathematicalmodels describing the sensory activation of thalamic and cortical neuronalpopulations in the rat whisker system from joint recordings of extracellularpotentials in thalamus and cortex. The mathematical models are formulated interms of average firing rates of a thalamic population and a set of laminarlyorganized cortical populations, the latter extracted from data from linear(laminar) multielectrodes inserted perpendicularly through cortex. Theidentified models describing the signal processing from thalamus to cortex arefound to be qualitatively very different from the models describing theprocessing between cortical populations; while the thalamocortical circuit isoptimally stimulated by rapid changes in the thalamic firing rate, theintracortical circuits respond most strongly to slowly varying inputs.firing-rate or neuralfield models Following pioneering work in the 1970s by, e.g., Wilson and Cowan specificpopulation firing-rate network models from extracellular recordings, (2) apply themethod to extract network models for thalamocortical and intracortical signalprocessing based on stimulus-evoked data from simultaneous single-electrode andmultielectrode extracellular recordings in the rat somatosensory (barrel) system,and (3) analyze and interpret the identified firing-rate models using techniquesfrom dynamical systems analysis. Our study reveals large differences in the transferfunction between thalamus (VPM) and layer 4 of the barrel column, compared to thatbetween cortical layers, and thus sheds direct light on how whisker stimuli isencoded in population firing-activity in the somatosensory system.We here (1) present a new method for identification of The derivation of biologically realistic, cortical neural-network models hasgenerally been hampered by the lack of relevant experimental data to constrain andtest the models. Single electrodes can generally only measure the firing activity ofindividual neurons, not the joint activity of populations of cells typicallypredicted by population firing-rate models. Kyriazi and Simons laminar population analysis (LPA) Einevoll et al. local field potentials; LFP) andhigh-frequency  parts of suchstimulus-evoked laminar electrode data to estimate (1) the laminar organization ofcortical populations in a barrel column, (2) time-dependent population firing rates,and (3) the LFP signatures following firing in a particular population. These‘postfiring’ population LFP signatures were further used toestimate the synaptic connection patterns between the various populations using bothcurrent source density (CSD) estimation techniques and a newLFP template-fitting technique In the present paper we describe a new method for extraction of populationfiring-rate models for both thalamocortical and intracortical transfer on the basisof data from simultaneous thalamic single-electrode and cortical recordings usinglinear (laminar) multielectrodes in the rat barrel system. With so calledmodels. The models are formulated as nonlinear Volterraintegral equations with exponentially decaying coupling kernels allowing for amapping of the systems to sets of differential equations, the more commonmathematical representation of firing-rate models Here we use the stimulus-evoked time-dependent firing rates for the corticalpopulations estimated using LPA, in combination with single-electrode recordings ofthe firing activity in the homologous barreloid in VPM, to identify populationfiring-rate The population responses were found to increase monotonically both with increasingamplitude and velocity of the whisker flick A first focus is on the estimation of mathematical models for the signal transferbetween thalamus (VPM) and the layer-4 population, the population receiving thedominant thalamic input. For this thalamocortical transfer our experimental datafavors a model with (1) fast feedforward excitation, (2) a slower predominantlyinhibitory process mediated by a combination of recurrent (within layer 4) andfeedforward interactions , and (3) a mixed linear-parabolicactivation function. The identified thalamocortical circuits are seen to have aband-pass property, and in the frequency domain the largest responses for thelayer-4 population is obtained for thalamic firing rates with frequencies aroundtwenty Hz.Very different population firing-rate models are identified for the intracorticalcircuits, i.e., the spread of population activity from layer 4 to supragranular(layer 2/3) and infragranular (layer 5) layers. For the present experimentalparadigm the extracted firing rates of the various cortical laminar populations arefound to exhibit strong temporal correlations and simple feedforward models withlinear or mixed linear-parabolic activation function are found to accountexcellently for the data. The functional properties of the identifiedthalamocortical and intracortical network models are thus qualitatively verydifferent: while the thalamocortical circuit is optimally stimulated by rapidchanges in the thalamic firing rate, the intracortical circuits are low-pass andrespond strongest to slowly varying inputs.Preliminary results from this project were presented earlier in poster format thalamocortical models against the experimentally observedpopulation responses in layer 4 using the experimental thalamic response as drivinginput to the model. The identified thalamocortical models found by minimizing thedeviation between model predictions and experimental population firing rates arefurther analyzed and explored using tools from dynamical system analysis. Finally,we correspondingly examine how the experimentally measured laminar populationresponses in layer 2/3 and layer 5, respectively, can be explained byintracortical network models with the experimental layer-4population responses as input.Here we illustrate our approach by first showing results from one of the sixexperimental data sets considered, and next show the thalamic and cortical laminarpopulation responses extracted from these experimental data. Further, we outline thegeneral form of the neural population models we explore to account for thesepopulation firing. We then go on to test specific candidatemulti-unit activity (MUA) data for one of sixexperiments, labeled ‘experiment 1’, from stimulus onset,i.e., onset of whisker-flick, until 100 ms after. This is the time window ofdata used in the further analysis. Color plots depict the laminar-electroderecordings while the line plots below show the corresponding trial-averagedthalamic recordings. Results for 9 of 27 stimulus conditions are shown,corresponding to three different stimulus rise times In laminar population analysis (LPA)We first focus on the signal transfer between thalamus and the dominant inputlayer of the barrel column, namely layer 4. Specifically we seek a mathematicalmodel predicting the layer-4 population firing rate The stimulus-evoked dynamics of the excitatory and inhibitory neurons in layer 4of the barrel column is complex. The excitatory neurons receive both feedforwardexcitation from thalamic neurons and recurrent excitation from other layer 4excitatory cells full thalamocortical model where all the abovementionedfeedforward and recurrent connections are included, we then haveFor mathematical convenience and conceptual simplicity we choose to formulate thepopulation firing-rate model as Volterra integral equations temporal coupling kernels, and temporal convolution between thetemporal kernel Here the feedforward excitation recurrent excitation The four terms within the large parentheses on the right hand side of Eq. (1) canbe interpreted as four contributions to the input current entering the somas ofneurons in the layer-4 population. The first and second terms correspond toactivation function thatconverts the net input current to population firing rate The function The temporal coupling kernel recurrent thalamocortical modelwhere the feedforward inhibitory term in the full model in Eq. (1) has beenomitted, i.e.,We first consider the so called This model has a special significance in that it maps  in This equation set resembles the model derived using‘semirigorous’ techniques by Pinto et al. in instantaneous excitatory andinhibitory nullclines at five different times  and the model ofPinto et al. On differential form our population-firing rate model is readily availablefor stability analysis. Due to the recurrent excitatory term the recurrentthalamocortical model can in principle have unstable equilibrium points, butthe identified models must clearly exhibit stable background states whenonly the stationary thalamic input (corresponding to the absence ofwhisking) is present. For experiments 1–3 the background state demonstrates that both conditions are fulfilled and that thebackground state is indeed stable. Inspection of Eqs. (6–7)further shows that instability is promoted by an increased weight of therecurrent excitation We further investigated whether the full thalamocortical model in Eq. (1), i.e.,the recurrent model amended with the feedforward inhibition term feedforward model, i.e., amodel with feedforward excitation and inhibition only, could account for thethalamocortical data. This model readsWe then investigated whether a pure For experiments 1–3, which exhibit the largest variation of responses,the fits of the experimental data for the feedforward model are poorer than forthe corresponding fits of the recurrent model. While the errors In The fitted activation functions for the recurrent and feedforward models forexperiments 1 to 3 are quite different cf.  and 6. IAnother way to compare the candidate thalamocortical models is to investigatetheir so called ‘sloppiness’  in  cf. , and the−5  for the recurrent model. In contrast, two of seven eigenvalues areless than 2·10−5 for the feedforward model. Thislarger ‘sloppiness’ is in accordance with the poorer fitsobserved for the feedforward model; the functional flexibility inherent in thefeedforward model appears not to be well suited to account for the present datawith 3 different amplitudes and 9 different stimulus rise times. For the fullmodel we find three of eleven eigenvalues to be smaller than10−5. Thus compared to the recurrent model, the addedfeedforward inhibition with two new parameters seems only to add two‘sloppy’ eigenvalues, in line with the observation that theoverall fit is not improved much.In To summarize, our results so far suggest that the model with recurrent inhibitionaccounts slightly better for the present experimental data than the model withfeedforward inhibition, i.e., that the layer-4 interneurons providing theinhibition of the layer-4 excitatory neurons are in turn mainly driven byexcitation from layer-4 neurons. Since the relative strength of recurrenteffects compared to feedforward effects appears to increase with increasingthalamic stimuli transfer functions in frequency space andimpulse-response functions can be explored Our identified thalamocortical models are in general nonlinear due to thenonlinear activation functions transfer functionrecurrent model in Eq. (2) it reduces toFor the thalamocortical models the derivation of the transfer functionamounts to deriving the response to a small sinusoidal modulation Here This transfer function describes how a small modulation of the thalamicpopulation firing rate transfers to the layer-4 population firing rate. Thetransfer function phase of the transfer functionis negative for the smallest frequencies. The negative transfer-functionphase implies that the maximum in the layer-4 responses will precede themaximum of the thalamic input for a small sinusoidal input for thesefrequencies.In The experimental stimulus set with 3 different amplitudes and 9 differentstimulus rise times was found to provide the largest variation in neuronalresponses and thus provide the best test data for distinguishing the twocandidate models. As seen in impulse-responsefunction, i.e., the response to a very brief input signal Another traditional dynamical systems measure is the The biphasic thalamocortical impulse-response observed in Layer 4 is generally thought of as the dominant input layer for sensoryactivation of cortex. The supragranular population of layer-2/3 pyramidalneurons appears to receive a dominant input from the layer-4 population, and theinitial stimulus-evoked response in layer 2/3 appears to largely stem from layer4 neurons which in turn are activated by the thalamic input This form assumes that the interlaminar connections from layer 4 to layer 2/3 arepredominantly provided by the excitatory neurons As before the weight laminar population analysis (LPA)in Einevoll et al. linear activation function. In our test runs, it did not. Forexperiment 1 with linear activation function the error was found to only bereduced from A strong feedforward connection between the layer-4 and layer-2/3 populations isin accordance with previous experimental studies We also investigated to what the extent the extracted layer-5 population firingrate can be accounted for by the same type of firing-rate model with the layer-4population providing the stimulus-evoked input The presently extracted intracortical models have very simple mathematical forms.For example, for the layer-4 to layer-2/3 transfer the model on integral formcan be translated to a simple differential equation using the‘linear-chain trick’ as described in We next investigated the intracortical transfer functions. The linear transferfunction from the layer-4 population to the layer-2/3 and layer-5 populations isfound from Eq. (11) to be given byIn near cf. . For theA main objective of the present paper is the description and application of a newmethod for extraction of population firing-rate models for thalamocortical andintracortical signal transfer on the basis of trial-averaged data from simultaneouscortical recordings with laminar multielectrodes in a rat barrel column andsingle-electrode recordings in the homologous thalamic barreloid. Below we firstdiscuss the results from the model estimation for both the thalamocortical and theintracortical signal transfer, followed by a discussion of the model estimationmethod itself.feedforward thalamocortical model with feedforward excitationand inhibition and (ii) a recurrent model with feedforwardexcitation, recurrent excitation and recurrent inhibition (but no feedforwardinhibition). In reality the inhibitory layer-4 neurons receive excitatory inputsboth from thalamic neurons and other layer-4 neurons, and the inhibition felt bythe excitatory layer-4 neurons will thus be both‘feedforward’ and ‘recurrent’; thedifferent models thus explore what part appears to dominate in the presentexperimental situation.For the thalamocortical signal transfer our investigations clearly identifies amodel with (1) fast feedforward excitation, (2) a slower predominantlyinhibitory process mediated by recurrent (within layer 4) and/or feedforwardinteractions , and (3) a mixed linear-parabolic activationfunction. The relative importance of the feedforward compared to the recurrentconnections is more difficult to determine and has been a subject of significantinterest Our results suggest that the model with recurrent inhibition better accounts forthe present experimental data than the model with feedforward inhibition, i.e.,that the layer-4 interneurons providing the inhibition of the layer-4 excitatoryneurons are in turn mainly driven by excitation from layer-4 neurons. Since therelative strength of recurrent effects compared to feedforward effects appearsto increase with increasing thalamic stimuli recurrent model on integral form in Eq. (2) can be mappedto a set of two differential equations (Eqs. 4–5) structurally similarto the model suggested and investigated by Pinto and coworkers. Thecorrespondence between the behavior of these models is demonstrated by thephase-plane plots in An interesting result from the present investigation is that we find a similarthalamocortical population model as Pinto et al. The presently identified intracortical model for the connection between thelayer-4 and layer-2/3 populations has a very simple mathematical form includingonly a single feedforward term (Eqs. 11–12), but was neverthelessfound to account excellently for the experimental data, cf. As seen in τEf<0.1 ms). The modelsolutions naturally failed to predict the onset of the layer-4 firing correctly,indicating their inadequacy.As a methods test we also investigated to what extent our feedforward model couldaccount for the ‘backwards’ connections, i.e., whether thelayer 4 firing could mathematically be accounted for by the model in Eq. (11)with the extracted layer-2/3 or layer-5 population firing rates as inputrespectively. These connections are expected to be weak A conclusion from our study is that the signal processing in the thalamocorticaland intracortical circuits is very different. The thalamocortical circuit favorsrapid whisker movements in that sharply rising thalamic population firing ratesevokes large cortical responses. For such stimuli the fast excitation in thecircuit dominates the slower, but eventually stronger, inhibition at short timescales thus ensuring a large population firing-rate in the layer-4 populationfor a certain time window. For slower whisker movements the inhibition overtakesthe excitation before a strong cortical response has emerged. This essentialfeature is demonstrated by the phase-plane plots in The intracortical circuits appear very different. Here the extracted modelsperform low-pass filtering, but the time constants are so short, typically1–3 ms, that the cutoff frequency is large: for firing-ratefrequencies up to 50 Hz only modest reductions in the transfer ratio isobserved, cf. trial-averaged data a roughly linear relationship wasobserved for a large range of small and intermediate population firing rates.For large population firing rates the true population firing rate was found togrow superlinearly with the MUA due to increasing cancelation of extracellularpotentials for high firing rates. It is, however, unclear whether or to whatextent such a superlinear relationship can be expected here.A core assumption in our modeling scheme is that the MUA signal is proportionalto the population firing rate A number of factors in our study could affect the magnitude and frequency contentof the recorded electrophysiological response in comparison with awake behavinganimals in a natural environment. Among them are anesthesia conditions and theuse of an artificial single-whisker stimulus in the absence of active whisking.The present study used alpha-chloralose, an anesthetic agent used widely inneurophysiological and hemodynamic studies due to its lesser effects oncardiovascular, respiratory and reflex functions Presently we have assumed the measured MUA to correlate with the excitatorypopulation. Due to their lower neuron numbers the inhibitory populations areexpected to contribute less, although differences in morphology and firing ratesbetween excitatory and inhibitory neurons will also affect their relativecontributions In the current models only the firing rates of the excitatory laminar populationsare modeled explicitly, while the inhibitory neurons are merely considered tomodify the dynamics of, and interaction between, these excitatory populations.An alternative to the single population Volterra firing-rate model for thethalamocortical transformation in Eq. (1) could be the following generalizationincluding an explicit dynamical equation also for the inhibitory firing rate, i.e.,This model explicitly includes thalamic input to both the excitatory andinhibitory populations as well as all possible recurrent connections The analysis of model parameter identifiability revealed that certain linearcombinations of parameters , donot have a measurable effect on the measured signals, and thus cannot beconfidently estimated. This problem can be partly addressed by usingintracellular recordings to measure some of these parameters, e.g., synaptictime constants and firing rates as function of somatic input currents, directlyin the relevant cell types. Model identification could also be aided bytheoretical investigations of the basic structure of population firing-ratemodels Furthermore, intercolumnar signal propagation can be modeled through connectingsingle-column firing-rate models of the present type based on known connectivitybetween neighboring columns or commissural projections Several groups have attempted to derive information about functional connectivitybetween cortical areas based on non-invasive imaging data 2 in air. Ventilationparameters were adjusted to maintain the following blood gas readings:PaCO2 between 35 and 45 mm Hg, PaO2 between 140 and180 mm Hg, and pH between 7.35 and 7.45. Heart rate, blood pressure, and bodytemperature were monitored continuously. Body temperature was maintained at37.0±0.5°C with a homeothermic blanket . The animal was fixed in a stereotaxic frame. An area ofskull overlying the primary somatosensory cortex was exposed and then thinnedwith a dental burr. The thinned skull was removed and the dura matter dissectedto expose the cortical surface. A barrier of dental acrylic was built around theborder of the exposure and filled with saline.All experimental procedures were approved by the Massachusetts General HospitalSubcommittee on Research Animal Care. Male Sprague-Dawley rats were used in the experiments. Glycopyrrolate  was administered 10 minutes before the initiation of anesthesia.Rats were anesthetized with 1.5% halothane in oxygen for surgery.Following surgery (see below), halothane was discontinued, and anesthesia wasmaintained with 50 mg/kg intravenous bolus of alpha-chloralose followed bycontinuous intravenous infusion at 40 mg/kg/h. During surgery a tracheotomy wasperformed, cannulas were inserted in the femoral artery and vein. All incisionswere infiltrated with 2% lidocaine. Following tracheotomy, rats weremechanically ventilated with 30% OMapping with a single metal microelectrode  wasdone to determine the positioning of the linear (laminar) multielectrode arrayin barrel cortex. The optimal position was identified by listening to an audiomonitor while stimulating different whiskers. Following the mapping procedure,the electrode was withdrawn, and the laminar electrode was slowly introduced atthe same location perpendicular to the cortical surface. Contact no. 1 waspositioned at the cortical surface using visual control with saline covering theexposed cortex around the laminar electrode. The linear multielectrode had 23contacts with diameter 0.04 mm spaced at 0.1 mm The thalamic recordings were performed using single metal microelectrodes . The ventral posteriomedial thalamic nucleus (VPM)was targeted using stereotactic coordinates . VPM (rather than POm) was chosenbecause it provides the dominant input to cortical layer 4 Single whiskers were deflected upward by a wire loop coupled to acomputer-controlled piezoelectric stimulator. The stimulus sequence wasoptimized using the approach described by Dale rectified along the time axis toprovide the multi-unit activity (MUA). This non-negative high-frequency‘envelope’ reflects firing of action potentials The recorded laminar-electrode potential was amplified and analogically filteredonline into two signals: a low-frequency part and a high-frequency part trial-averaged data were obtained byaveraging over all 40 trials for each stimulus type.Sample traces of the laminar-electrode MUA (prior to rectification) for a singletrial can be seen in Six experiments recorded from a total of three rats were considered. Inexperiments 1–3 the stimulus condition with 3 amplitudes and 9rise-times was used, while the 27-amplitude stimulus condition was used inexperiments 4–6. Experiments 1, 2, 4 and 5 were from a single rat,while experiments 3 and 6 were from two other rats. About ten (out of 6480)trials were removed due to artifacts in the laminar-electrode MUA. Inexperiments 3 and 6, the laminar-electrode MUA signal from contact no. 9 waserratic; for this channel the arithmetic mean of the MUA signals from theneighboring contacts (contacts no. 8 and 10) was therefore used instead. Thetrial-averaged MUA data used for the estimation of cortical population firingrates is denoted The MUA recorded by the single thalamic electrode was used as a measure of thepopulation firing rate of thalamic neurons in a barreloid in VPM projecting ontothe homologous barrel. An estimate of the trial-averaged thalamic firing rate laminar population analysis(LPA), for analysis of laminar-electrode data. Using this method,laminarly organized neuronal populations can be identified and the timedependence of the population firing rates estimated. The laminar-electrode MUAdata The estimation of population firing rates of laminar cortical populations fromlaminar-electrode MUA is less straightforward. However, Einevoll et al. Pettersen et al. The resulting filtered estimatesWe assume that The population firing-rate models are formulated as nonlinear Volterra integralequations The quantity In our model the net input current As illustrated in The model parameters were estimated by fitting model estimates of the populationfiring rates Here the sums over t = 0.5 ms is thetime step. As a result, the recurrent synaptic connections can be considered tohave a fixed time delay of 0.5 ms. The convolutions with the exponentialcoupling kernels were approximated using MATLAB's FILTER command. Noexplicit delays were considered for the recurrent terms, but for the feedforwardterms delays corresponding to multiples of the time step (0.5 ms) were allowedfor.The numerical calculations were done using MATLAB. In the numerical evaluation ofthe thalamocortical model (Eq. 1) the experimentally extracted thalamic firingrate A three-step optimization procedure was used. In the first step the full modelwas considered and a preliminary optimization was performed doing a stochasticsearch starting from several sets of random initial parameter values sloppiness, and can be quantified by an eigenvalue analysis ofthe Hessian matrix composed of the partial 2nd derivatives of the model errorfunction evaluated for the estimated optimal (minimum error) parametercombination In the optimization procedure we take advantage of linear correlations in theensembles of fitted model parameters. Principal component analysis (PCA) of thecovariance matrices The spectrum of these eigenvalues can be related to the shape of an ellipsoidalconstant-error surface in a high-dimensional parameter space. The length of eachprincipal axis of this constant-error surface is inversely proportional to thesquare root of the corresponding eigenvalue The full thalamocortical model on integral form in Eq. (1) can be mapped to aset of two differential equations by means of the ‘linear chaintrick’ Since the temporal coupling kernels all are given as exponentially decayingfunctions, differentiation of the expression for Here we have used that the delay constants On differential form the stability of the thalamocortical model can bedirectly assessed. For the situation with a stationary input The Jacobian of this autonomous equation system is given byFor the situation where the equilibrium point corresponds to These expressions can be directly generalized to the case where thebackground equilibrium state is on the parabolic part of the activationfunction by replacing Our thalamocortical models are in general nonlinear due to the nonlinearactivation function With these expressions the convolutions in Eq. (1) can be rewritten asWe now assume the perturbations in the input Algebraic rearrangement of this expression gives linear inhibitory activation function,i.e., An alternative to the one-population Volterra model in Eq. (1) could be ageneralization to a two-population Volterra model where both excitatory andinhibitory population firing rates are modeled explicitly. For thethalamocortical transformation this translates into including both an excitatoryand an inhibitory layer-4 population, cf. Eqs. (14–15). With certainassumptions, however, this two-population model reduces to the one-populationmodel in Eq. (1): with a Then a term-by-term comparison shows that this expression has identical form asEq. (1) provided the identifications


In daily life, we are exposed to different sound inputs simultaneously. During neural encoding in the auditory pathway, neural activities elicited by these different sounds interact with each other. In the present study, we investigated neural interactions elicited by masker and amplitude-modulated test stimulus in primary and non-primary human auditory cortex during ipsi-lateral and contra-lateral masking by means of magnetoencephalography (MEG).We observed significant decrements of auditory evoked responses and a significant inter-hemispheric difference for the N1m response during both ipsi- and contra-lateral masking.The decrements of auditory evoked neural activities during simultaneous masking can be explained by neural interactions evoked by masker and test stimulus in peripheral and central auditory systems. The inter-hemispheric differences of N1m decrements during ipsi- and contra-lateral masking reflect a basic hemispheric specialization contributing to the processing of complex auditory stimuli such as speech signals in noisy environments. In most day to day situations, we are exposed to many different sound inputs simultaneously. During encoding and perception, these concurring sound inputs interact with each other. A well known phenomenon in this regard is the elevation of the hearing threshold for a test sound in presence of a competing sound. This phenomenon, called 'simultaneous masking' , can be In the case of ipsi-lateral masking, interactions already take place at the cochlear level, thus this type of masking is often referred to as 'peripheral masking' . The traDuring contra-lateral simultaneous masking, signal and masker are presented to opposite ears; therefore, interactions can only take place in the central auditory pathway. Thus, this type of masking is referred to as 'central masking' . The thrBoth spectral and temporal features of test stimuli and maskers might play an important role for simultaneous masking effects. In a psychoacoustical experiment, Fletcher  presenteRecent neuroimaging techniques revealed functional hemispheric asymmetries of spectral and temporal neural processing. A left hemispheric dominance for temporal processing and a right hemispheric dominance for spectral processing were observed by means of positron emission tomography  and funThe goals of the present study were: (1) to investigate interactions between auditory neurons characterized by similar or different receptive fields during both ipsi- and contra-lateral masking, and (2) to investigate the hemispheric differences in neural activities in human auditory cortex during both ipsi- and contra-lateral masking by means of MEG. The results of this study were expected to yield new information about underlying neural mechanisms and hemispheric differences for the processing of complex sound stimuli during simultaneous masking.An example of individual magnetic field waveforms (30 Hz low-pass filtered) for the no masking condition Figure  demonstrThe goodness of fit of the equivalent current dipoles (ECDs) for N1m and ASSR in the control condition was above 90% for all participants. The grand averaged ECD source locations Figure  in y-z-pThe grand averaged source strength waveforms elicited by TS presented to left and right ears for each masking condition across all subjects are shown in Figures The means of the normalized N1m and ASSR source strength decrements obtained in the ipsi-lateral condition are displayed in Figure A repeated measures ANOVA applied to normalized ASSR source strength decrements during ipsi-lateral masking resulted in a significant main effect for TS-TYPE  = 14.3, p < 0.01) and STIMULATION-SIDE  = 11.3, p < 0.01); however, neither a significant main effect for HEMISPHERE nor an interaction was found. These findings indicate that similar N1m and ASSR decrement patterns were obtained for TS-TYPE. However, contrary to the N1m decrement pattern, ASSR decrements did not show a significant hemispheric difference, but a significant difference for STIMULATION-SIDE. This result means that the ipsi-lateral masking effect on the ASSR was stronger when stimulus and masker were presented to the left ear, and this stimulation-side difference was not hemisphere specific.The means of the normalized N1m and ASSR source strength decrements across subjects for the contra-lateral masking condition are presented in Figure The normalized ASSR decrement during contra-lateral masking was significantly different from zero (no masking effect) in all conditions Figure . This meThe means of the threshold shifts obtained during ipsi- and contra-lateral masking are displayed in Figure By using a complex stimulus design and by combining 40 Hz amplitude-modulated test stimuli of different spectral characteristics (PB and SB) with a comb-filtered noise (CFN) masker, in this study we were able to simultaneously examine both ASSR (primary auditory cortex origin) and N1m (non-primary auditory cortex origin). The results offer new insights into auditory neural interactions and hemispheric differences during simultaneous masking. These interactions depended on: (1) the frequency components of the stimuli, (2) level of the auditory system , and (3) the hemisphere. There were two main findings. First, we observed that N1m and ASSR decrements during both ipsi- and contra-lateral masking depended on spectral differences between masker and test stimulus. Second, we obtained an inter-hemispheric difference for N1m response during both ipsi- and contra-lateral masking.In case of ipsi-lateral masking, both peripheral and central auditory pathways contribute to the masking effect. By contrast, in the case of contra-lateral masking, only neural interactions in the central auditory pathway contribute to the masking effect. Consequently, stronger masking effects should be expected for ipsi-lateral masking. Our MEG and behavioral results indeed confirm this hypothesis: significantly stronger masking effects on N1m and ASSR were found for ipsi-lateral compared to contra-lateral masking. During ipsi-lateral masking, displacements of the basilar membrane interact due to simultaneous presentation of TS and CFN, and such interactions along the basilar membrane are primarily responsible for N1m and ASSR decrements. However, overlapping basilar membrane displacements cannot explain the N1m and ASSR decrements observed during contra-lateral masking as masker and test sounds were presented to different ears. Therefore, we assume that these decrements were caused by neural interactions in the central auditory pathway. The significant ASSR decrements during contra-lateral masking imply that inhibitory neural interactions had already taken place in primary auditory cortex. However, it is possible that the central masking effects occurred at lower level, as anatomical studies in cat have shown that the superior olivary complex is the primary binaural interfering station .N1m and ASSR decrements were more pronounced for PB compared to SB during both ipsi- and contra-lateral masking. In case of ipsi-lateral masking, these different decrements between PB and SB could be explained by the critical band concept suggested by Fletcher . Those pDuring contra-lateral masking, binaural interactions between auditory neurons activated by left and right ear stimulations contributed to the significant N1m decrements. Our results showed significantly different N1m decrements between PB and SB. This result indicates that inhibitory neural interactions also depended on the frequency similarities between masker and test stimulus during contra-lateral masking. In accordance with previous psychoacoustical work , our MEGNormalized N1m decrements were significantly smaller in the left hemisphere during both ipsi- and contra-lateral masking. This result indicated that the left hemisphere might play a dominant role for sound processing in noisy environments. Recent neuroimaging studies ,16 suggeThe hemispheric difference in auditory neural activities might be also explained by the 'asymmetric sampling in time' concept as suggested by Poeppel . The autA previous MEG study  demonstrWe observed N1m decrements during contra-lateral masking, whereas in another MEG study  this effASSR decrements were significantly different between ears during ipsi-lateral masking: decrements were more pronounced for left compared to right ear stimulation. The less pronounced ASSR decrements during ipsi-lateral masking might reflect the so-called 'right ear advantage' suggested by a previous study . The autIn the present study, we have observed smaller N1m decrements in the left hemisphere during both ipsi- and contra-lateral masking. This suggests left hemispheric dominance for auditory processing in noisy environments. As test stimuli, we used amplitude-modulated sounds characterized by 'fine structure' and 'envelope' at the same time. These sounds are similar to speech signals, but do not carry speech information . TherefoTen subjects  with no history of otological or neurological disorders participated in the present study. All subjects were strongly right-handed (assessed via "Edinburgh Handedness Inventory" ). They hTo investigate neural interactions between similar and different frequencies, we used a comb-filtered noise (CFN) derived from white noise by applying multiple band-pass filters with widths of a quarter of an octave as masker Figure  and two Three experimental conditions were applied: contra-lateral masking, ipsi-lateral masking, and no masking control condition Figure . Two sesBoth CFN and TS were presented at 45 dB SL (sensation level) in order to avoid interaural cross talk. The intensities of stimuli and masker were individually adjusted at the beginning of each experimental session. TS were prepared as sound files and presented via STIM software  using ER30 transducers , plastic tubes of 2.5 m length and silicon ear pieces fitting to the subject's ears. The CFN was played from a CD player and superimposed on the TS.Auditory evoked magnetic fields were recorded with a helmet-shaped 151-channel whole cortex neurogradiometer  in a quiet, magnetically shielded room. The subjects were seated comfortably and watched a silent movie of their choice during the MEG measurement in order to keep them in a stable alert state. The magnetic field signals were 200 Hz low-pass filtered online and sampled at a rate of 625 Hz.Epochs of magnetic field data starting 300 ms before the onset of the TS and ending 200 ms after the offset of the TS  were averaged after artifact rejection (threshold: 3.0 picotesla). After 30 Hz low-pass filtering and baseline correction based on the 300 ms pre-stimulus interval, spatiotemporal equivalent current dipoles  were estimated for the averaged magnetic field distribution of the N1m response in the control condition. A 10 ms time window prior to the maximal global field power, measured as root mean square across all sensors around 100 ms after TS onset, was used for estimation of the transient N1m source. ECD locations and orientations in each hemisphere were determined in a head based Cartesian coordinate system with the origin set to the midpoint of the medial-lateral axis (y-axis) between the entrances of the left and right ear-canals: the posterior-anterior axis (x-axis) ran between nasion and the origin; the inferior-superior axis (z-axis) ran through the origin perpendicularly to the x-y-plane.The source analysis resulted in two estimates for the N1m sources in the right and left hemispheres. Based on the ECD coordinates and orientations obtained in the control condition, the method of source space projection was applied to the averaged magnetic field of each condition. This method combines the magnetic field waveforms obtained from each sensor weighted by the sensitivity of each sensor for a source at the specified location into a single waveform of the dipole moment. ASSR was analyzed in a similar way. The model of ECD was applied to the averaged magnetic field data (band-pass filtered between 30 and 50 Hz) within the 300 ms time interval starting 200 ms after TS onset until the end of the stimulus. N1m and ASSR source strength decrements observed in ipsi- or the contra-lateral masking conditions were normalized with respect to the source strength obtained in the control condition for each hemisphere of each subject /source strength unmasked). Those normalized decrements are then interpreted as masking effects between 0 (no masking) and 1 (complete extinction). In order to evaluate the normalized N1m and ASSR decrements, repeated measures analyses of variance (ANOVAs) were performed to evaluate three factors (STIMULUS-SIDE × TS-TYPE × HEMISPHERE) for ipsi- and contra-lateral masking independently. The source locations of N1m and ASSR were analyzed by paired t-test with respect to each axis in each hemisphere. P values smaller than 0.05 were accepted as significant.In addition, we carried out psychoacoustical measurements to assess the threshold shifts during ipsi- and contra-lateral masking. Ten right-handed subjects  with no history of otological or neurological disorders participated in the behavioral study. All measurements were performed in an acoustically shielded room. As the sound signals used for the MEG measurements were low-pass filtered due to the transfer characteristic of the sound delivery system, we used the CFN and the TS recorded at the earpiece in the magnetically shielded room for the behavioral measurements in order to make behavioral measurement and MEG measurement comparable. Thus, the sound signals used for MEG and behavioral measurements had identical amplitude spectra Figure . The TS HO conceived of the study, HO and CP designed the experimental setup. HO acquired the data and drafted the manuscript. All authors participated the data evaluation and interpretation and approved the final version of the manuscript.


Microarray analysis provides a powerful approach to identify gene expression alterations following transplantation. In patients the heterogeneity of graft specimens, co-morbidity, co-medications and the challenges in sample collection and preparation complicate conclusions regarding the underlying mechanisms of graft injury, rejection and immune regulation.We used a rat kidney transplantation model with strict transplant and sample preparation procedures to analyze genome wide changes in gene expression four days after syngeneic and allogeneic transplantation. Both interventions were associated with substantial changes in gene expression. After allogeneic transplantation, genes and pathways related to transport and metabolism were predominantly down-regulated consistent with rejection-mediated graft injury and dysfunction. Up-regulated genes were primarily related to the acute immune response including antigen presentation, T-cell receptor signaling, apoptosis, interferon signaling and complement cascades. We observed a cytokine and chemokine expression profile consistent with activation of a Th1-cell response. A novel finding was up-regulation of several regulatory and protective genes after allogeneic transplantation, specifically IL10, Bcl2a1, C4bpa, Ctla4, HO-1 and the SOCS family.Our data indicate that in parallel with the predicted activation of immune response and tissue injury pathways, there is simultaneous activation of pathways for counter regulatory and protective mechanisms that would balance and limit the ongoing inflammatory/immune responses. The pathophysiological mechanisms behind and the clinical consequences of alterations in expression of these gene classes in acute rejection, injury and dysfunction vs. protection and immunoregulation, prompt further analyses and open new aspects for therapeutic approaches. Microarray analyses have been used to link changes at the level of gene expression to different kidney diseases to obtain markers for diagnosis and prognosis. Microarray analyses of human patients have been used to analyze post-transplant events -6. A recThere are a number of limitations inherent in clinical studies of gene expression in transplantation. Patients typically represent major differences in gender, age, co-morbidities, clinical histories, immunosuppressive regimes, race/ethnicities, and genetics and it is always difficult to collect samples at specific times relative to the procedures. These differences significantly influence gene expression and that operant variability compromises the results obtained by microarray analysis as well as the confidence to identify the principal underlying immune mechanisms. The use of experimental transplantation models in rats or mice is an opportunity to mitigate these variables and work in a controlled system. Several studies have made use of experimental transplantation to study changes in gene expression related to acute rejection after murine heart, kidney and lung transplantation -13. WhilIn previous studies ,17, we sThe global experiment structure was inspected utilizing different methods intended to validate whether the groups were homogeneous and whether the within-group variance was smaller than the between-group variance. Furthermore, group distances could be roughly estimated. The correlations within the "acute group" , "syngeneic group"  and "control group"  showed a homogenous correlation of 0.97–0.99 Fig. . The corSignificantly regulated and differentially expressed genes were identified using class comparisons as implemented in BRB ArrayTools for all the possible group comparisons . Genes with a parametric p value < 0.001 were classified as significantly differentially expressed Fig. . Thus, 3Genes with protective or regulatory properties up-regulated after allogeneic transplantation like HO-1 (22 fold), Bcl2a1 (59 fold), C4bpa (219 fold), IL10 (120 fold) or members of a gene family that were highly induced like TIMP1 18 fold), MMP7 (15 fold), TAP1/2 (24/14 fold) were analyzed by real time PCR Fig.  and 2D.  fold, MMThe genes analyzed by real time PCR were not identified to be differently expressed after syngeneic transplantation compared to control. However, the real time PCR results showed up-regulated expression of MMP7 (~21-fold) and C4bp (~13-fold) after syngeneic transplantation.A selection of transcripts determined to be up-regulated as a function of acute rejection is shown in Table T-cells and macrophages release factors like cytokines for differentiation and proliferation and chemokines for recruitment of other immunologically active cells. Thus, the expression pattern of cytokines and chemokines like Cxcl9, Xcl1, Cxcl10 or Ccl3 shown in Table To identify activated or suppressed functions, the lists of significantly up- or down-regulated genes after syngeneic transplantation and allogeneic transplantation were analyzed to identify over-represented GO-terms. The third GO-level gives the best compromise between specificity and list coverage . After sDecreased expression of metabolism-related genes after syngeneic transplantation suggests the suppression of BP-related genes. Increased expression of genes related to "cell proliferation" and "cell cycle" within the BP category, "extra cellular matrix" and "collagen" within the CC category and "collagen binding" within the MF category reveal the activation of tissue injury recovery mechanisms related to the transplant surgery itself.After allogeneic transplantation, 58 GO-terms were significantly enriched in the up-regulated and 29 in the down-regulated genes on GO-level 3. Without the application of any filter, 250 GO-terms were enriched in the up- and 119 in the down-regulated set of genes. Table The functional annotation with DAVID identified pathways related to the Kyoto Encyclopedia of Genes and Genomes (KEGG)  that werPathways with enrichment of down- or up-regulated genes after allogeneic transplantation are listed in Table To illustrate the pathways activated by acute rejection related to the immune response, we used IPA to map networks of up- and down-regulated genes after allogeneic transplantation to functional pathways for antigen-presentation Fig. , TCR-sigThe recognition of allogeneic MHC by the T-cell's cognate antigen receptor (TCR) will induce activation signals and transcriptional activity Fig. . The genFig. Several genes in the list of up-regulated genes after allogeneic transplantation might serve as novel markers for acute rejection Table . One canThe MHC antigens are the main barrier for an acceptance of the graft by the host organism and antigen presentation is essential for the activation of T-cells. T-cells are activated when the TCR recognizes allo-MHC class I molecules in the case of CD8+ and MHC class II molecules in the case of CD4+ T-cells . Host T-Our data also indicates that T-cell cytotoxicity is the main immunological pathway activated in response to acute rejection in allogeneic transplantation. The cytotoxic molecules are perforin/granzyme for CD8+ T-cells and the Fas/Fas-ligand system for CD4+ T-cells ,32. In tThe induction of tolerance to the graft would be the treatment of choice after transplantation. Increased expression of protective genes like metallothionein-1 or α2β- crystallin were reported with a mouse cardiac transplant model ,37. In tThe complement system is part of the innate immune response. The expression profile we demonstrate in allogeneic transplants for a number of complement components indicates the activation of the complement cascade by acute rejection Fig. . Its majRecently regulatory T-cells have been recognized as a promising tool for the induction of tolerance . In thesWe have used a well-defined rat kidney transplantation model to demonstrate global changes in gene expression levels after syngeneic and allogeneic transplantation with the emphasis on early acute rejection in the allogeneic transplants. Using DNA microarrays and real time PCR analysis, we were able to identify major immune effector-related pathways that are activated after allogeneic transplantation and clearly linked by multiple lines of published evidence to acute rejection mechanisms of tissue injury. That we also found a list of genes that are equally highly differentially expressed in acute rejection but not presently linked in the literature represents opportunities for additional studies and discovery. In parallel, we have also identified a number of up-regulated genes that are linked to tissue protective and immune counter-regulation mechanisms. These observations fit with the evolving view of immunity as a balance between effector and regulatory mechanisms.Male Lewis-Brown-Norway (LBN) and Lewis (LEW) rats  with free access to standard rat chow  and tap water were used. Experiments were approved by a governmental committee on animal welfare and were performed in accordance with national animal protection guidelines. Renal transplantation was performed as published before ,53. For On day four after transplantation, the transplanted kidneys were removed and total RNA was isolated using RNeasy-kit  incubated with 10 U DNase I  to digest genomic DNA. RNA quality was measured using the Agilent 2100 BioAnalyzer . Total RNA was used to prepare biotinylated target RNA. Briefly, 10 μg of total RNA was used to generate first-strand cDNA by using a T7-linked oligo (dT) primer. After second strand synthesis, in vitro transcription was performed with biotinylated UTP and CTP .Target cDNAs generated from each sample were then processed as per manufacturer's recommendation using an Affymetrix GeneChip instrument system. Labeled samples were hybridized to the Rat Genome 230 2.0 Array. Arrays were washed and stained with streptavidin-phycoerythrin before being scanned on an Affymetrix GeneChip scanner. Data were analyzed using Affymetrix GCOS array analysis software. The data discussed in this publication have been deposited in NCBIs Gene Expression Omnibus  and are Experiment reports were inspected to assure equal experiment quality. GeneData Refiner  was used to check quality and import experiments with detection and masking of outliers . The array defects, assessment using 3'/5' ratios of housekeeping controls, glyseraldehyde-3-phosphate dehydrogenase (GAPDH) and β-Actin, and condensation of intensities to signal values using the "Affymetrix Statistical (MAS5)" method. In GeneData Analyst normalization onto arithmetic mean 400 was performed. Correlation coefficients of all pair wise scatter plots were calculated and summarized in a colored matrix. Clustering was done using the Euclidean distance measure and the complete linkage method. Correlation coefficients and clustering enable a visualization and assessment of the experiment structure based on global expression behavior. Identification of significantly different expressed genes between the control, allogeneic and syngeneic groups were identified using class comparison with the BRB ArrayTools developed by Dr. Richard Simon and Amy Peng . The typ® Systems, Redwood City, CA, USA).Up- and down-regulated genes in the allogeneic and syngeneic groups compared to control group were separately analyzed to identify enrichment of different functional pathways and gene ontology (GO) terms  using thExpression profiles for selected genes were analyzed by real time PCR. Total RNA (10 μg) isolated from the same samples was used for cDNA synthesis with the High Capacity cDNA Reverse Transcription Kit. Real time PCR was performed using SYBR Green PCR Master Mix or TaqMan Universal PCR Master Mix on an ABI PRISM 7700 Sequence Detection System. Specific primer pairs or TaqMan Gene expression assays were used. The PCR efficiency of the primers pairs was tested in dilution series with a cDNA from the allogeneic transplanted group. A list with the corresponding primer sequences or TaqMan assay IDs is provided with this manuscript . Relative gene expression values were evaluated with the 2ng genes .BE performed the experimental design, data analysis and drafted the manuscript, ME performed data analysis, SK contributed to data acquisition, analysis and drafting the manuscript, DL interpretation of data, CM contributed in data analysis, GG suggested the study, helped with interpretation and drafting of the manuscript, DS data analysis and drafting the manuscript, ES coordinated the study and contributed materials and resources. All authors read and approved the final manuscript.Gene lists from the class comparison between the groups analyzed with BRB ArrayTools.Click here for fileOverrepresented gene ontology annotations in the gene lists up or down regulated after allogeneic transplantation compared to control or after syngeneic transplantation compared to control.Click here for fileTable with the sequences of the primers and IDs of the TaqMan assays used for real time PCR analysis.Click here for file


The Fas receptor (APO-1/CD95) is capable of inducing apoptosis of lymphoid cells and is expressed in some non-Hodgkin's lymphomas (NHLs). Fas expression is up-regulated at the surface of normal B cells upon triggering of the CD40 receptor. In this report, we investigated the sensitivity of NHLs to Fas-mediated apoptosis induced by anti-Fas monoclonal antibodies (MAbs) and its possible modulation by CD40 ligation in 18 NHL biopsy samples of various histological subtypes. Flow cytometric analysis showed that the fraction of Fas-expressing lymphoma cells was highly variable from sample to sample . The frequency of apoptotic cells was not significantly increased upon treatment with an anti-Fas MAb compared with control MAb in the 18 NHL cases analysed. The sensitivity of lymphoma cells to Fas-mediated apoptosis was correlated neither with the histological subtypes nor with the level of Fas expression. Activation of neoplastic B cells by CD40 ligation resulted in significant increases in Fas expression and Fas-induced apoptosis among the five B-NHL cases tested. The overall increase in apoptotic rates was moderate and remained lower in tumour samples than in control CD40-activated normal tonsil B cells. Altogether, our results indicate that the sensitivity to Fas-induced apoptosis is null or weak in NHL cells, irrespective of their histological subtype, and that it can be increased to a moderate and variable degree by CD40 ligation on neoplastic B cells. This may be an impediment to the development of Fas-based therapies for NHLs.


Arabidopsis thaliana genes is circadian-regulated.Transcript abundance of roughly a third of expressed  As nonmotile organisms, plants must rapidly adapt to ever-changing environmental conditions, including those caused by daily light/dark cycles. One important mechanism for anticipating and preparing for such predictable changes is the circadian clock. Nearly all organisms have circadian oscillators that, when they are in phase with the Earth's rotation, provide a competitive advantage. In order to understand how circadian clocks benefit plants, it is necessary to identify the pathways and processes that are clock controlled.Arabidopsis thaliana in order to better estimate the fraction of the plant transcriptome that is circadian regulated. Analyzing the promoters of clock-controlled genes, we identified circadian clock regulatory elements correlated with phase-specific transcript accumulation. We have also identified several physiological pathways enriched for clock-regulated changes in transcript abundance, suggesting they may be modulated by the circadian clock.We have integrated information from multiple circadian microarray experiments performed on A. thaliana genes is circadian regulated. We found four promoter elements, enriched in the promoters of genes with four discrete phases, which may contribute to the time-of-day specific changes in the transcript abundance of these genes. Clock-regulated genes are over-represented among all of the classical plant hormone and multiple stress response pathways, suggesting that all of these pathways are influenced by the circadian clock. Further exploration of the links between the clock and these pathways will lead to a better understanding of how the circadian clock affects plant growth and leads to improved fitness.Our analysis suggests that transcript abundance of roughly one-third of expressed  Harsh environmental extremes often accompany the daily light-dark cycle. In nearly every organism studied an endogenous time keeping mechanism has evolved that enables anticipation of these predictable changes . This isArabidopsis [Although this advantage has been demonstrated for both phytoplankton and higher plants, the mechanistic link between the circadian clock and increased fitness remains unclear. Understanding how clocks confer an adaptive advantage requires a thorough knowledge of circadian-regulated pathways and processes. Fortunately, several microarray experiments have been performed to identify the circadian transcriptome of the model plant system bidopsis -8. TheseCCA1 expression, the myb-related transcription factor CCA1 represses TOC1 expression upon binding to a circadian clock regulatory element (CCRE) in the TOC1 promoter [This raises another major question in circadian biology; how does the central clock mechanism control the vast array of circadian outputs and phase them to the appropriate time of day? Although the circadian clocks of higher plants, animals, and fungi consist of interlocking transcriptional feedback loops, the individual components vary -11. In ppromoter ,13. Thispromoter . The EE promoter ,8,14,15.Arabidopsis is circadian regulated; we use data from multiple circadian microarray experiments to discover known and potential circadian clock regulatory elements; and we identify new circadian-enriched pathways that may help to explain the physiological importance of the clock. These findings may help explain how clock outputs are regulated so that they occur at the appropriate time of day, a central function of the circadian clock [Here we suggest that the abundance of as many as one-third of expressed transcripts in an clock . In addian clock . These fArabidopsis have yielded varying estimates of the fraction and identity of genes that are clock regulated. We recently found that the abundance of 10.4% ('Covington dataset') of expressed transcripts is circadian regulated in light-grown Arabidopsis seedlings [Rhythmic control of gene expression is an important function of the circadian system; however, genome-wide microarray studies performed on eedlings . To evaleedlings . Our anaStudies using very similar entrainment and growth conditions have resulted in reports that expression of 5.5% ('Harmer dataset') to 15.4% ('Edwards dataset') of genes is circadian regulated  Figure . Many faWe next compared the degree of circadian regulation found in the Harmer and Covington datasets when the same analytical techniques are used. Comparing only genes found on both of the array platforms used in these experiments, the degree of circadian regulation in the Harmer and Covington datasets is quite similar Figure . When thP = 1.7 × 10-106) between the relative amplitude of rhythmic genes identified by both datasets (0.21) and that of rhythmic genes identified only by the Covington dataset (0.12). This, together with our analysis of the Harmer dataset, suggested that identification of clock-regulated genes might be limited by technical issues and would benefit from increased sample numbers.We suspected that genes identified as circadian regulated in both the Covington and Edwards microarray studies have high amplitude rhythms, whereas genes with low amplitude rhythms tended to be identified in only one of the studies. As predicted, we found a strikingly significant difference ; by appending the Edwards series after the Covington series to generate a 4-hour resolution time course over four days ('CCEE' dataset); and by appending the Covington series after the Edwards series to generate a different 4-day time course .All three time courses were analyzed in accordance with the parameters used in the original Edwards analysis . In eachArabidopsis seedlings and the same platform as the Covington and Edwards datasets [Two additional circadian microarray experiments ('Michael datasets') were recently performed using datasets . SubjectDrosophila [Drosophila datasets was only 24%, with an average overlap of 11%. The extensive overlap of cycling genes found between the C+E intersection and each of the individual datasets  suggests that a major limitation for detecting clock-regulated genes in circadian microarray experiments is not laboratory dependent or biological variation, but rather technical issues that can be alleviated by increasing the number of time points. This can be accomplished by increasing the duration of the time course, the sampling frequency during the time course, or the degree of biological replication of samples. The first two approaches provide more biological information and thus appear to be preferable to the third. In order to minimize developmental effects and the damping of rhythms that often occurs during free running conditions, we recommend circadian time courses with increased sampling frequency rather than increased duration.A recent comparison of five independent microarray studies to identify circadian-regulated genes in osophila  demonstrGiven the impressive overlap between the genes designated as clock regulated when the Covington and Edwards datasets are either appended end-to-end or interwoven Figure , it appeArabidopsis genome [Arabidopsis genome.Co-expressed genes have been shown to occur in clusters throughout the s genome ,20. Simis genome ,22. To dCombining the results from all three cluster discovery methods, we found only 18 unique circadian clusters. These represent only 63 of the 3,975 circadian-regulated genes identified in the C+E intersection  confers dawn-phased expression and the protein box element  confers midnight-phased expression on a luciferase reporter gene ,14. TherThe putative CCREs that we identified are related to motifs recently found by others to be enriched in the promoters of circadian genes ,8,14,15.Despite using different analytical strategies and gene lists, we and Michael and coworkers  found maIt will next be critical to test whether the GATA and G-box motifs do confer different day-phased rhythms of transcript accumulation and to determine whether different combinations of the four known CCREs in the promoters of circadian genes are sufficient to confer every phase of circadian transcript accumulation. Identification of the transcription factors that bind to these CCREs will provide insight into the circuitry of the circadian clock and the regulatory network between the clock and its outputs.To begin to define this regulatory network, we next wished to identify transcription factors found to be clock regulated in the C+E intersection. Only 732 of the 1,690 genes with the GOslim annotation  'transcrTCP genes causes phenotypes often found in clock mutants, such as late flowering and elongated hypocotyls [Links to the circadian clock were previously described for the first three families ,26-32 bupocotyls , suggestIn order to understand the physiological relevance of the circadian system and how a functional clock can confer a competitive advantage , we mustCLA1 (CLOROPLASTOS ALTERADOS 1), which encodes the enzyme that carries out the first and rate-limiting step of the MEP pathway [As in other studies, we identified an enrichment of clock regulation among genes functioning in many metabolic and physiological pathways -8. We no pathway . It has  pathway ,48. Beca pathway , the extP value for circadian enrichment = 1.7 × 10-3) of the genes involved in the conversion of GGDP and tyrosine into the various tocopherols and tocotrienols that together comprise the antioxidant vitamin E are clock regulated, six with a morning phase of peak transcript abundance  of circadian regulation among genes encoding enzymes that are involved in the synthesis of carotenoids from GGDP, with most showing a peak phase of transcript abundance at around subjective dawn , encoding the first and rate-limiting enzyme in carotenoid biosynthesis [NPQ1 (a gene encoding violaxanthin deepoxidase) has peak transcript levels at subjective dusk  and ABA2 (ABA DEFICIENT 2) accumulate during the subjective morning . This morning phase distribution coincides with the phase of accumulation of CLA1, PSY, NCED3, and other circadian-regulated transcripts that are involved in the production of the ABA precursor violaxanthin or ABA itself , a gene that is involved in the production of ethylene, has previously been shown to be circadian regulated with peak accumulation during the subjective day, the same time as peak ethylene emission; however, plants with a T-DNA insertion within the ACS8 coding region do not exhibit altered ethylene rhythms [ACS8 (data not shown). It is possible that all three enzymes act together to generate circadian ethylene emission.The gaseous hormone ethylene plays well-known roles in fruit ripening and the triple response during seedling emergence; in addition, it is involved in organ senescence and abscission and responses to both abiotic and biotic stresses . Product rhythms . Under t rhythms . IntriguEIN3 (ETHYLENE INSENSITVE 3) and EIL1 (EIN3-LIKE 1), have a similar day-phased pattern of transcript accumulation as the ACC-induced genes  than do cold-responsive genes . The average circadian transcript abundance profile of heat-responsive genes peaks just before subjective dawn, whereas cold-responsive genes reach peak transcript levels 12 hours later, near subjective dusk . Semi-quantitative PCR was conducted as previously described [The gene selection procedure involved randomly choosing genes with varying degrees of robust rhythmic expression. We chose three genes from the top third highest amplitude cyclers  and three from the lowest third amplitude cyclers . For each time point, circadian transcript levels were normalized by dividing by transcript levels of the control gene escribed .Arabidopsis Genome Arrays  [Arabidopsis ATH1 Genome Array) [The Harmer dataset was composed of technical replicates using Affymetrix CA, USA) . We rande Array) . BecauseBoth the Edwards and Covington datasets were originally analyzed with the same circadian detection algorithm, namely COSOPT. However, the Edwards analysis did not use the initial sampling density weighted linear regression detrending, resulting in an increased number of genes identified as circadian . To compGroups of adjacent expressed genes in a sliding window  were evaluated based on the proportion displaying circadian expression patterns, the mean pMMC-β value (a measure of circadian rhythmicity), or the mean combinatorial pair-wise Pearson correlation coefficient. Threshold values were empirically derived via an approach based on a method originally proposed for quantitative trait mapping . Specifiin silico testing of 6-mer and 8-mer nucleotide sequences.We employed four different strategies to identify potential motifs of interest: a trio of established motif discovery tools . For both the Covington and Edwards datasets, a potential motif must be over-represented in circadian genes versus all expressed genes; over-represented in at least one phase-specific subset of circadian genes versus all circadian genes; and under-represented in at least one phase-specific subset of circadian genes vs. all circadian genes. Over-representation and under-representation was determined using a previously described permutation testing approach . SubsequArabidopsis Information Resource [Using annotations for the circadian-regulated genes found in the C+E intersection , we searched for functionally-related gene groups enriched for circadian patterns of transcript accumulation. Genes were grouped according to annotations based on MapMan bins , Gene OnResource  gene famABA: abscisic acid; ACC: 1-aminocyclopropane-1-carboxylic acid; CBS: CCA1-binding site; CCA1: circadian clock associated 1; CCRE: circadian clock regulatory element; EE: evening element; GA: gibberellic acid; GGDP: geranylgeranyl diphosphate; ME: morning element; MEP: methyl erythritol phosphate; MJ: methyl jasmonate; PBX: protein box element; ROS: reactive oxygen species; RT-PCR: reverse transcription polymerase chain reaction; SA: salicylic acid; TCP: teosinte branched1/cycloidia/PCF; TOC1: timing of CAB expression 1.MFC, SAK, and SLH developed the experimental design. MFC conducted the experiments. MFC, SLH, JNM, and MS analyzed the data. MFC and SLH drafted the manuscript. All authors read and approved the final manuscript.The following additional data are available with the online version of this paper. Additional data file A table listing the normalized circadian expression data for the combined Covington and Edwards dataset CCEE.Click here for fileA table summarizing the expressed and circadian genes identified using different circadian microarray datasets.Click here for file


Pichia pastoris shake flask cultures with the example of production of stable human type II collagen. Production of recombinant proteins in P. pastoris is usually performed by controlling gene expression with the strong AOX1 promoter, which is induced by addition of methanol. Optimization of processes using the AOX1 promoter in P. pastoris is generally done in bioreactors by fed-batch fermentation with a controlled continuous addition of methanol for avoiding methanol toxification and carbon/energy starvation. The development of feeding protocols and the study of AOX1-controlled recombinant protein production have been largely made in shake flasks, although shake flasks have very limited possibilities for measurement and control.Here we describe a new technical solution for optimization of 2 monitoring we demonstrate that the widely used pulse feeding of methanol results in long phases of methanol exhaustion and consequently low expression of AOX1 controlled genes. Furthermore, we provide a solution to apply the fed-batch strategy in shake flasks. The presented solution applies a wireless feeding unit which can be flexibly positioned and allows the use of computer-controlled feeding profiles.By applying on-line pOBy using the human collagen II as an example we show that a quasi-continuous feeding profile, being the simplest way of a fed-batch fermentation, results in a higher production level of human collagen II. Moreover, the product has a higher proteolytic stability compared to control cultures due to the increased expression of human collagen prolyl 4-hydroxylase as monitored by mRNA and protein levels.The recommended standard protocol for methanol addition in shake flasks using pulse feeding is non-optimal and leads to repeated long phases of methanol starvation. The problem can be solved by applying the fed-batch technology. The presented wireless feeding unit, together with an on-line monitoring system offers a flexible, simple, and low-cost solution for initial optimization of the production in shake flasks which can be performed in parallel. By this way the fed-batch strategy can be applied from the early screening steps also in laboratories which do not have access to high-cost and complicated bioreactor systems. Pichia pastoris is a favored yeast species as a host for heterologous protein production  needed for the collagen polypeptide chain(s) needs the parallel expression of two different genes coding for collagen prolyl 4-hydroxylase (C-P4H), an enzyme required for the thermal stability of collagens  glutarate with (Pro-Pro-Gly)10 as the peptide substrate [C-P4H activity was analyzed from ubstrate . The totMR and MB performed the shake flask experiments. MK and AV developed the wireless feeding system and the computer control program. MB designed the mRNA probes and primers and performed together with MK the mRNA analyses. MR, AN and ERH performed the protein analyses. JM and ERH contributed with their experiences in the collagen production process. MR wrote the initial manuscript, which was read and approved by all authors. PN initiated and practically supervised the scientific work.


To identify factors associated with developing severe respiratory syncytial virus (RSV) pneumonia and their commonality with all-cause lower respiratory tract infection (LRTI), in order to isolate those risk factors specifically associated with RSV-LRTI and identify targets for control.A birth cohort of rural Kenyan children was intensively monitored for acute respiratory infection (ARI) over three RSV epidemics. RSV was diagnosed by immunofluorescence of nasal washings collected at each ARI episode. Cox regression was used to determine the relative risk of disease for a range of co-factors.z-score ≤−2, RR 1.7 95%CI 1.1–2.8), crowding  and number of siblings under 6 years . Moderate and severe stunting (z-score ≤−1), crowding and a sibling aged over 5 years sleeping in the same room as the index child were associated with increased risk of all-cause LRTI, whereas higher educational level of the primary caretaker was associated with protection.A total of 469 children provided 937 years of follow-up, and experienced 857 all-cause LRTI, 362 RSV-ARI and 92 RSV-LRTI episodes. Factors associated with RSV-LRTI, but not RSV-ARI, were severe stunting  and contact intensity  which are distinguishable in their association with RSV severe disease in infant and young child. These factors are broadly in common with those associated with all-cause LRTI. The results support targeted strategies for prevention. Pneumonia is the leading cause of morbidity and mortality in the developing world . Among tPneumonia has multiple aetiologies, and the risk factors for RSV-associated disease may be common to all pneumonias, specific to viral pneumonias or may be agent-specific. Past studies report a number of possible risk factors for increased viral disease severity, most of which are common to RSV. These may be environmental  was usData were double entered onto FileMaker (FileMaker Pro 5.5 v1) with internal consistency checks, and analysed using Stata . Longitudinal data on infection history were combined with cross-sectional data from the risk factor survey. Observation time included days from date of recruitment until the last study visit, or until lost to follow-up, excluding days absent from the district. Each child had multiple record visit data over the follow-up period. Certain variables were reassigned at intervals of 3 months  or at each epidemic period .2 saturation <90% by Oximetry), the latter group only if confirmed by the clinician’s own diagnosis of LRTI or bronchiolitis. The outcome variables were: (i) all-cause LRTI, (ii) RSV-ARI and (iii) RSV-LRTI  and a diagnosis of LRTI was assigned to children with acute cough or difficulty in breathing in association with any one or more of the following (i) raised respiratory rate for age , (ii) lower chest wall indrawing or (iii) inability to feed, reduced conscious level or hypoxia  only those with the strongest univariate association were included. Significant variables were included in the multivariate models using a non-automated forward stepwise regression starting from the variable with the highest test statistic. Variables that no longer showed significance (P ≥ 0.05) were removed. For highly correlated variables (r ≥ 0.8) only the variable remaining significant in the multivariate model was included. The Cox shared frailty model was used with the all-cause LRTI outcome because of significant multiple failures per individual . The standard Cox model with adjusted standard errors adjusting for clustering within individual was used for RSV-ARI and RSV-LRTI. Analysis time was calendar time, eliminating the potential confounding effect of seasonality in RSV and all-cause LRTI. Time-varying covariate(s) were specified through multiple observations per subject, ensuring risk sets at each failure were associated with the correct value of the risk factor. The results are reported as relative risks (hazard ratios) with 95% confidence intervals.Univariate analysis was performed to describe the study population and identify risk factors for inclusion in multivariate analysis. Predictors were considered for inclusion in the multiple regression models using the log-rank test of equality of survival distribution across strata  or a univariate Cox proportional hazard regression for the continuous variables. Predictors were considered for inclusion if the test had a The birth cohort was monitored over four calendar years until each child had lived through three epidemics of RSV infection. From the 469 children under surveillance at the time of the risk factor survey, 29 979 separate visits (observations) for the detection of all-cause LRTI, RSV-ARI and RSV-LRTI were made. The observations per child were between 23 and 104 with a mean and median of 71. There were 362 episodes of clinical RSV-ARI detected among 940 person-years of observation; 283 single infections and 79 children were identified as being symptomatically infected by RSV more than once . There were 857 episodes of all-cause LRTI; 128 (37%) children had only one episode of LRTI, 216 (63%) had two or more episodes. Of the all-cause LRTI episodes, 92 were associated with RSV; 86 (93%) children had a single episode of RSV-LRTI, with 6 children having two episodes. Population characteristics for the cohort are detailed in Factors significantly associated with the risk of acquiring RSV-ARI and RSV-LRTI or all-cause LRTI by univariate analysis are presented in Results from the multivariate regression are shown in z-score ≤ −2) was also an independent predictor of RSV-LRTI.Significant predictors of the risk of infection were included in the RSV-LRTI multivariate analysis as the baseline. Additional variables linked to RSV-LRTI from the univariate analysis were then fitted, and independent predictors reported in column 2 of z-score of ≤ −1, crowding (number of children in the home), and contact pattern (number of siblings over 6 years of age sleeping the same room as cohort child). Current age was also an independent predictor of all-cause LRTI associated with protection in those 6–11 months and increased risk in those 12–17 months. A multiple birth (triplets) was the strongest independent predictor of LRTI, although rare in the cohort  as opposed to total ARI, namely, growth stunting and household crowding.z-scores (The data show that stunting (mild to moderate and severe), an indication of long-term malnutrition, was a more important factor for RSV-LTRI and all-cause LRTI than acute (short-term) malnutrition (wasting). This risk has previously been reported in a study involving Kenyan children . It is tz-scores , give thThe second important predictor of disease was crowding, as measured by number of children, and siblings under 6 years of age, which was associated with increased risk of RSV-LRTI and all-cause LRTI. The underlying mechanism may be increased contact intensity, resulting in an increase in size and/or duration of the exposure inoculum resulting from proximity of contact (intimacy of contact) . The assSeveral factors related to intensity (family size) and pattern of contact  between other children in the home and the cohort child were investigated. An association between the number of siblings sleeping in the same room as the cohort child and increased risk of all-cause LRTI was observed . SeveralOther factors significantly associated with individual outcomes in the multivariate analysis included house and toilet type which relates to SES, exposure to tobacco and environmental smoke from cooking fuel (borderline significance) which have previously been reported , only 3.3% of households have this many occupants. In contrast, having 1–2 siblings under 6 years is of lower risk (RR 2) but 56.5% of the population fall into this category.A possible limitation of this study is that diagnosis of RSV infection on the basis of antigen detection alone has lower sensitivity compared with the use of assay combinations  and household size (high contact intensity and sibling numbers) as significant risk factors for severe RSV disease, and that these are broadly common to all-cause LRTI. These data not only reinforce previously suspected associations but also, through careful study design, provide more specific evidence for the relationship with disease progression. These data have implications for our understanding of RSV transmission and control. The notion of differences in the risk of acquiring disease according to contact age and intensity suggests the importance of these factors in transmission and control particularly in relation to who acquires infection from whom. In the light of this, vaccination programmes targeted to school children, who constitute the siblings within households, may show promise by providing indirect protection to the infant. Additional benefits would be achieved from education of mothers on reducing the intensity of contacts between siblings and the naïve young infant who is at most risk of severe disease. Furthermore, an increased risk of pneumonia in those with chronic poor nutritional status reinforces the need for community-based interventions directed towards improved diet, supplementation (vitamin supplements or fortified milk) and parental education (promoting breastfeeding), already acknowledged to have significant positive benefits on all outcomes.


Morphological cytogenetic analysis demonstrated a colcemid-like effect of FAA on cytokinesis by causing accumulation of condensed C-metaphases of a sustained mitotic block. The cell cycle effect was blocked by the antioxidants ADPC and ascorbate, the superoxide scavenger Tiron, and the sphingosine kinase inhibitor L-cycloserine, but not by inhibitors of nitric oxide synthase. Based on these data, we propose that FAA may induce cell cycle arrest by stimulating the activity of acidic sphingomyelinase leading to the generation of reactive oxygen species. © 1999 Cancer Research CampaignFlavone acetic acid (FAA) is a synthetic flavonoid that demonstrated extraordinary anti-tumour properties in murine models but was not effective in clinical trials. In an effort to better understand the molecular mechanisms by which FAA asserts its tumouricidal activities, we have examined the effect of FAA on the cell cycle. We observed FAA-mediated G2/M cell cycle arrest in mammary carcinoma cells at a concentration previously demonstrated to have anti-tumour effects in rodent models. The cell cycle arrest was accompanied by an increase in the P34


Developing rational targeted cancer drugs requires the implementation of pharmacodynamic (PD), preferably non-invasive, biomarkers to aid response assessment and patient follow-up. Magnetic resonance spectroscopy (MRS) allows the non-invasive study of tumour metabolism. We describe the MRS-detectable PD biomarkers resulting from the action of targeted therapeutics, and discuss their biological significance and future translation into clinical use. The increased understanding of the molecular mechanisms underlying oncogenesis has led to contemporary drug discovery programmes being aimed predominantly at signal transduction pathways and molecules that drive cancer initiation and progression . The speMany new agents aimed at blocking particular oncogenic targets are now being used in the clinic, with some having already gained regulatory approval for treatment of certain types of cancers. One example is imatinib mesylate , which was the first mechanism-based drug targeting an oncogenic molecule to gain FDA approval. Imatinib blocks many protein kinases, including fusion proteins BCR-ABL and KIT, and has been approved for the treatment of chronic myelogenous leukaemia and gastrointestinal stromal tumours.For the clinical development and evaluation of targeted therapies, and because of the cytostatic mode of action of many of these agents, the methods currently used for assessing tumour response, such as volumetric measurements, may not be adequate. Therefore novel functional pharmacodynamic (PD) biomarkers are required for early stage hypothesis testing to report on target inhibition, assess treatment efficacy and ultimately aid in patient management   . MetabolIn vivo MRS – It can be used to measure the metabolite content of tumours in living animals or patients, repeatedly and non-invasively. Subjects are placed in the bore of the magnet with the tumour positioned in the centre of a surface coil. Localised spectra are acquired and analysed to determine precise chemical shifts and peak integrals. The in vivo results are often expressed as ratios of one metabolite to another.in vivo MRS and the metabolite levels are often expressed as ratios.High-resolution magic-angle spinning spectroscopy (HR-MAS) – It can be used to examine intact cells or small tissue samples . It is invasive but only requires minimal sample preparation. It provides better spectral resolution than In vitro MRS – It provides a far superior spectral resolution to either HR-MAS or in vivo MRS but is invasive and more time consuming in sample preparation than HR-MAS. Cell or tumour samples are first extracted by perchloric acid or methanol/chloroform dual-phase methods, in which water-soluble metabolites and/or lipid metabolites can be obtained. A reference compound with a known concentration is added to the extracts for metabolite quantitation and chemical shift calibration. The metabolite levels are expressed as concentrations.The most common MRS methodologies used to study tumour metabolism are briefly described below , glycolytic intermediates such as glucose, glutamine/glutamate and lactate, in addition to choline-containing compounds such as phosphocholine (PC) and glycerophosphocholine (GPC). 31P-MRS, on the other hand, has particular value for studies concerned with tissue bioenergetics, pH and membrane turnover, as it can detect the presence of bioenergetic metabolites such as nucleotide triphosphates (NTPs), PCr and inorganic phosphate (Pi), in addition to membrane phospholipid metabolites including phosphomonoesters (PMEs), which comprise PC and phosphoethanolamine (PE), and phosphodiesters (PDEs), which comprise GPC and glycerophosphoethanolamine (GPE). 13C-MRS is used to monitor the uptake and metabolism of 13C-enriched metabolites and serves as a tool for monitoring the fate of the label, as it is incorporated into other metabolic intermediates such as glutamine and lactate in the case of 13C-labelled glucose.in vivo31P- and 1H-MRS, which are characteristic metabolic features of cancer  are observed in tumours by Several studies have investigated MRS as an imaging tool for detecting PD biomarkers of the action of novel therapies targeted at aberrant signal transduction pathways. Because only a handful of these agents have so far gained FDA approval, and the fact that most are still in pre-clinical development or early-phase clinical testing, most of the MRS studies performed to date have been concerned with pre-clinical cancer models, including cells and tumour xenografts. However, the technology has been demonstrated in a range of diagnostic and response assessment clinical studies  inhibitor, MN58b .In vivo, MN58b treatment induced tumour growth inhibition, which was associated with significant decreases in PMEs (31P MRS) and tCho (1H MRS). Ex vivo31P-and 1H-MRS analyses of MN58b-treated tumour extracts showed a significant reduction in PC when compared with controls, confirming that the decreases in PMEs and tCho observed in vivo were because of a decrease in PC (Treatment with a ChoK inhibitor should result in a reduction of PC synthesis and this hypothesis was tested in colon (HT29) and breast (MDA-MB-231) cancer cells and tumours treated with MN58b. Decreased PC and tCho levels were found in both cell lines after MN58b treatment and correlated with inhibition of ChoK activity and cell proliferation. In vivo and in vitro1H and 31P MRS were used to study HT29 cancer cells and tumours following treatment with LAQ824. Significant increases in PC were seen in HT29 cells after LAQ824 (Another example is the study that was performed using histone deacetylase (HDAC) inhibitors LAQ824 and SAHA. r LAQ824  and SAHAIn vivo, a significant increase in PME/total phosphorus signal (TotP) was found in LAQ824-treated HT29 xenografts, which correlated with tumour response. A dramatic fall in tumour bioenergetics was also observed, where decreases in intracellular pH, β-NTP/TotP and β-NTP/Pi, and an increase in Pi/TotP, were found , fatty acid synthase (FASN) and BCR-ABL. In contrast, inhibition of heat shock protein 90 (HSP90) or HDAC was associated with an elevation in PC and PME levels.A consistent decrease in PC, PME and tCho levels was observed after inhibition of many molecular targets, including phosphoinositide-3 kinase (PI3K), hypoxia-inducible factor 1ex vivo and in vivo MRS. Elevated choline levels may be indicative of membrane turnover (Phosphocholine is a precursor and a breakdown product of phosphatidylcholine (PtdCho), the major phospholipid component of cell membranes. Phosphocholine can be produced by phosphorylation of choline through ChoK, or from PtdCho hydrolysis directly through PtdCho-specific phospholipase C (PLC) or indirectly through PLD . Aberranturnover , increasturnover  or activAs discussed in de novo membrane synthesis required to produce increased cell volume  the cellular consequences induced in a particular tumour model ; and (2) the balance of interplay between the multiple molecular processes being modulated. Consequently, treatment with these broad-spectrum inhibitors may not necessarily mirror the changes associated with the collective downregulation of downstream signalling pathways using single agents.ex vivo31P-MRS after inhibition with LAQ824 and PX-478. In contrast, an increase in GPC was detected on exposure to 17-AAG, LY294002 and phenylbutyrate in cell culture, as well as ex vivo following treatment with FK866.As shown in Glycerophosphocholine and GPE are released from membrane phospholipids by phospholipase A2 (PLA2) and lysophospholipase. In the case of phenylbutyrate, the rise in GPC levels was associated with mobile lipid accumulation and postulated to occur as a result of PLA2 activation  using PET technology  have also been applied  with in vivo PD changes in tumour phospholipid metabolites. Owing to the nature of the trial (phase I) and the small size of the patient population that was analysed, no firm conclusions could be drawn regarding potential metabolic biomarkers of drug action. However, the study showed the feasibility of the approach in assessing biomarkers of response in future trials (1H-decoupled 31P-MRS at a number of centres (in vivo31P spectrum, thus allowing changes within individual peaks to be monitored. It remains to be seen whether this methodology could be useful for detecting metabolic biomarkers associated with response to treatment with targeted therapeutics.One example of such research is the clinical study that was performed at our Institution using 31P-MRS have highlighted the requirement for lesions to be relatively close to a surface coil for an adequate signal-to-noise ratio to be attained. As this may not always be possible, 1H-MRS, which is now well established clinically, also provides an alternative means for evaluating tumour metabolism.These and earlier clinical studies using Advances in instrumentation and in the magnetic field strength available on clinical scanners, together with the new fast metabolic imaging techniques using nuclear hyperpolarisation, are helping to increase the sensitivity of MRS and facilitate its clinical implementation. Developing quality assurance protocols and standardising data acquisition methodologies are important aspects that will help evaluate and integrate findings from multiple centres, thereby reducing effort and keeping duplication to a minimum (Magnetic resonance spectroscopy is showing promise as a non-invasive imaging tool for detecting metabolic biomarkers that are associated with the action of novel targeted therapeutics in pre-clinical models of cancer, and which are consistent with the observed molecular and cellular effects induced by the drugs. Technological advances and strategies for improved data acquisition protocols are helping the clinical implementation of MRS, which will be required for assessing whether the metabolic PD biomarkers observed could be translated into robust radiological tools for use in patient studies with targeted therapies.