, 2006, Giannakopoulos et al , 2003 and Näslund et al , 2000) Th

, 2006, Giannakopoulos et al., 2003 and Näslund et al., 2000). The criticism that follows is Aβ deposition itself does not necessarily predict or cause clinical AD. Such observations, however, can be understood in several other ways. First, there may be a threshold effect that involves the check details density and duration, or even rate of Aβ accumulation that together with the age of onset of the pathological processes determines the onset of the clinical

manifestations of AD. Second, as with other illnesses, there are almost certainly genetic, pathological, epigenetic, and environmental mediators that modulate progression, disease course, and manifestation of illness. For Ixazomib manufacturer example, one proposed mediator involves the concept of “cognitive reserve’ that hypothesizes that factors that enhance neuroplasticity and synaptogenesis, may make an individual more resistant to the clinical manifestations of the underlying

neuropathology, thereby delaying onset of the clinical expression of the illness (Cummings et al., 1998 and Stern et al., 1999). Third, it is also possible that early subtle cognitive impairment of AD that we might now refer to as preclinical stage 3 is often not recognized in elderly people who die and come to autopsy. Some evidence for this is from the Religious Order Study where those who died without cognitive impairment and who had intermediate or high likelihood of AD based on neuropathological

examination scored 0.25 standard deviation lower on episodic memory tests than those without pathology (Bennett et al., 2006), worsening of episodic memory being the earliest and most characteristic cognitive phenotype for AD (Dubois and Albert, 2004). Finally, it has become common to explain the results from failed AD therapeutic trials with presumptive anti-Aβ therapies as evidence that the hypothesis is wrong. This is clearly inaccurate, as to date, such trials were not definitive tests of the cascade hypothesis, but rather expedient ways to test potentially disease-modifying AD therapeutics in the current clinical, regulatory, and fiscal environment. None of the putative anti-Aβ agents that have failed in pivotal phase 3 therapeutic Amisulpride trials were optimal or even optimized agents within their class of anti-Aβ therapeutics: Alzhemed (tramiprosate, homotaurine) was a weak aggregation inhibitor; Flurizan (tarenflurbil, R-flurbiprofen) was a γ-secretase modulator with low potency and poor brain penetration; and semagacestat, a nonselective γ-secretase inhibitor (GSI), had significant mechanism-based toxicity limiting its dosage and efficacy with respect to lowering Aβ production (Golde et al., 2010). None of these drugs showed efficacy against primary endpoints in phase 2 trials but were advanced to phase 3 nonetheless. Other anti-Aβ therapies (e.g.

They also add support

They also add support 3 MA to the concept that neurons use their innate compartmentalization in their day-to-day processing and storage of information received via thousands of synaptic inputs from multiple presynaptic sources. The presence of spatial structure within the input could be used by neurons to selectively enhance the network response to particular patterns through well-understood dendritic boosting mechanisms ( Legenstein and

Maass, 2011 and Ujfalussy and Lengyel, 2011). The level of clustering required for this is quite relaxed: coactivation of <5% of synapses on a given branch can produce regenerative electrical events, and this process can occur within multiple branches ( Losonczy and Magee, 2006 and Branco and Häusser, 2010). In the end, observations that clustered forms of plasticity are engaged by normal neuronal activity and could

be used to produce spatially structured input patterns strengthens the concept that neurons use spatiotemporal input correlations to encode, process, and store particular stimulus features. “
“An incredible amount of computation goes on between light hitting the eye and our interpretation of what we see around us. This process starts at the photoreceptors, where photons are transduced into neural activity that travels through a series of brain regions, each extracting increasingly refined features, such as the selectivity of primary this website visual cortex (V1) for edges at specific orientations. These computations reach their culmination in the collection of visual cortical areas beyond V1, known collectively as “extrastriate” during cortex, where neurons encode high-order visual features such as objects, faces, motion, and foreground/background separation (Orban, 2008). In primates, the multiple extrastriate regions are often interpreted as creating a hierarchy with

two main pathways: the ventrally located “what is it?” stream and the dorsally located “where is it?” stream (Figure 1A). (Felleman and Van Essen, 1991 and Ungerleider and Mishkin, 1982). Neurons in ventral/“what” areas can have specific responses to particular objects, such as a face, in a manner that is invariant to position or viewing angle. In contrast, neurons in the dorsal/“where” areas process motion and represent location of objects or textures, irrespective of their identity. These pathways have also been defined in terms of a perception/action dichotomy—e.g., recognizing an object versus reaching toward it (Goodale and Milner, 1992).

Based on these spatial and temporal integration rules, we specula

Based on these spatial and temporal integration rules, we speculate that NMDAR-mediated nonlinearity may play a role in dendritic integration of synaptic input patterns evolving over see more many tens of milliseconds during exploratory behavior. Analyzing the kinetics of voltage responses evoked by synchronous stimulation, we discovered that the decay (quantified as the half-width) showed substantial variability across dendrites. The distribution of the half-width differed from a normal distribution (p < 0.001, n = 280 dendrites, 258 basal, 22 apical, Shapiro-Wilks test) and rather formed a bimodal

distribution with a group of NMDA spikes exhibiting fast decay and another population that decayed more slowly (peaks at ∼55 and ∼85 ms, respectively; Figures 5A and 5B). Accordingly, in all further analysis and experiments, we defined fast spikes as those with half-width <70 ms and slow spikes as those with half-width >70 ms. The kinetics of the NMDA spike in a given dendrite was relatively uniform over a range of peak amplitudes (Figure S3A). The half-width was not dependent on the particular synapses that were stimulated (Figures S3B and S3C). The half-width in basal dendrites was also not related to distance of the input site from the soma (Figure 5C, Spearman R = 0.032, p > 0.05) or morphological

position in the branching arbor (Figure S3D). Somatic holding membrane potential was similar between the groups (Vm, fast: −71.4 ± 0.4 mV, n = 19; slow: −72.2 ± 0.2 mV, n = 27, click here p = 0.063, Mann-Whitney test). Fast and slow NMDA spikes in different branches of the same cell could be observed (Figures 5D, 5E, and S3E), especially when comparing apical and basal branches (Figures 5E and S3E), indicating some degree of dendritic compartmentalization of the underlying mechanism. The half-width of somatic APs was not different between cells where most dendrites expressed fast NMDA spikes versus those expressing mostly slow spikes (Figure S3F), suggesting that dendritic properties are responsible for the variable decay. We found a significant correlation between the half-width and the magnitude

of nonlinearity of the NMDA spike Ketanserin (Figure 5F, Spearman R = 0.514, p < 0.05), and the input-output relationship was slightly shifted to the left in dendrites with slow NMDA spikes compared to that of fast NMDA spikes (Figure 5G, n = 19/27 fast/slow dendrites, p < 0.05 at 4–6 mV expected amplitude, Mann-Whitney test). On the other hand, NMDA spike half-width did not correlate with the strength of the Na+ spike evoked in the same dendrite (basal dendrites, Spearman R = 0.062, p = 0.680, Figure 5H). Observations that the decay of the NMDA spike was voltage dependent (Figure S3G) and correlated with the somatic membrane time constant (n = 18, Spearman R = 0.760, p < 0.05, Figure S3H) suggested that an active voltage-dependent conductance is regulating the decay of NMDA spikes. Several K+ channel types have been described in CA3PCs (Storm, 1990).

FoxOs regulate multiple intracellular signaling pathways and are

FoxOs regulate multiple intracellular signaling pathways and are also required for long-term maintenance of adult neural precursors (Paik et al., 2009 and Renault et al., 2009). In contrast, Prox1 (Lavado et al., 2010), NeuroD (Gao et al., 2009 and Kuwabara et al., 2009), and Krüppel-like factor 9 (Scobie et al., 2009) are sequentially required for maturation and survival of new neurons in the adult hippocampus. In the adult SVZ, Olig2 specifies transient amplifying cell fate whereas Pax6 and Dlx-2 direct neuronal fate (Doetsch et al., 2002) and promote a dopaminergic periglomerular

phenotype in adult mice (Brill et al., 2008 and Hack et al., 2005). Various epigenetic mechanisms play important roles in fine tuning and coordinating gene expression during adult neurogenesis, including DNA methylation, histone modifications, and non-coding RNAs (reviewed by Sun et al., 2011). For example, Methyl-CpG-binding domain protein 1 (Mbd1) suppresses the expression of FGF-2 LDK378 solubility dmso and several miRNAs to control the balance between proliferation and differentiation during adult hippocampal neurogenesis (Liu et al., 2010). Among many histone modifiers, Mll1

(mixed-lineage leukemia 1), a TrxG member that encodes an H3K4 methyltransferase, is specifically required for neuronal differentiation in the adult SVZ, at least partially through its direct target Dlx2 (Lim et al., 2009). Bmi-1, a member of the PcG complex, is required for neural precursor maintenance in the adult SVZ through the cell-cycle inhibitor p16 (Molofsky et al., 2003). Through silencing Sox2 expression, HDAC2 is required for maturation selleck compound and survival of newborn neurons in the adult

brain, but not embryonic neurogenesis (Jawerka et al., 2010). In addition, several micoRNAs (miR124, 137, and 184) have been shown to fine tune the amount and timing of adult neurogenesis (reviewed by Sun et al., 2011). A number of neurological disease risk genes have been shown to regulate adult neurogenesis. In the adult SGZ, expression of human presenillin (PS) variants linked to early-onset familial Alzheimer’s disease in microglia impairs proliferation and neuronal fate commitment (Choi et al., 2008), whereas deletion of PS1 in forebrain excitatory neurons affects enrichment-induced hippocampal Mephenoxalone neurogenesis (Feng et al., 2001). PS1 mutants also exhibit impaired self-renewal and differentiation of adult SVZ precursors involving notch signaling (Veeraraghavalu et al., 2010). Deletion of doublecortin (DCX; a gene mutated in most cases of double cortex syndrome) in newborn neurons causes severe morphologic defects and delayed migration along the RMS (Koizumi et al., 2006). In mice deficient in fragile X mental retardation protein (Fmrp; a gene responsible for fragile X syndrome), both proliferation and glial fate commitment of neural precursors are increased in the adult SGZ, through regulation of the Wnt/GSK3β/β-catenin/neurogenin1 signaling cascade (Luo et al.

The protrusion of microtubules is essential for neurite formation

The protrusion of microtubules is essential for neurite formation as low levels of the microtubule-destabilizing drug nocodazole attenuated the neurite-restoring effects of cytochalasin D and latrunculin see more B ( Figure S5). Instead, manipulations that were targeted either to stimulate

integrin signaling or to bundle actin filaments, which restore neurite formation in Mena/VASP/EVL KO neurons ( Dent et al., 2007), did not enable neurite formation in AC KO neurons ( Figure S6). We conclude that the drastic F-actin disorganization in AC KO neurons obstructs intracellular space and misdirects microtubule growth patterns. Furthermore, a pharmacological depolymerizing activity bypasses the need for AC proteins, allowing microtubules to coalesce and to radially protrude to generate neurites. Although in some instances the function of ADF and Cofilin are overlapping (Hotulainen et al., 2005), ADF depolymerizes actin filaments better than Cofilin, whereas Cofilin severs filaments better than ADF (Bernstein and Bamburg, 2010). Therefore, we determined the individual contributions of ADF and Cofilin to neuritogenesis. First, we examined the development of neurons with either monoallele ADF

selleck compound expression (NesCre+/−, ADF+/−, cofilinflox/flox) or monoallele cofilin expression (NesCre+/−, ADF−/−, cofilinflox/+). ADF monoallele expression resulted in defective neuritogenesis with a significant increase in the percentage of cells in stage 1 ( Figures S7A and S7B). In contrast, cofilin monoallele expression conferred wild-type-like neuronal development, with the majority of neurons in stage 2 or stage 3 ( Figures S7C and S7D). Consistently, reintroduction

of ADF into AC KO neurons only partially restored neurite already formation in AC KO neurons, whereas Cofilin reintroduction almost completely reversed the neuritogenesis defect, resulting in cells with wild-type morphology in cell culture ( Figures 7A and 7B). Moreover, Cofilin re-expression restored normal neuronal development in AC KO cortical slices ( Figures 7C, 7D, and S7E). Analysis of the F-actin organization revealed that both ADF and Cofilin restored the gross organization of actin architecture. The percentage of cells extending filopodia increased 2-fold in ADF or Cofilin-transfected AC KO neurons ( Figures 7E and 7F). However, kymograph analysis of live-cell imaging of AC KO neurons cotransfected with Lifeact-GFP revealed that only Cofilin expression increased actin retrograde flow to 4.0 ± 1.0 μm/min, nearly a complete rescue, while ADF only partially increased actin retrograde flow to 2.9 ± 1.2 μm/min, a 65% rescue ( Figures 7E and 7G). Thus, while ADF and Cofilin are equally adept at stimulating filopodia formation, Cofilin has a higher propensity for driving actin retrograde flow and neuritogenesis.

Another important issue is that receptors can exist in a triheter

Another important issue is that receptors can exist in a triheteromeric form that contains both a GluN2A and a GluN2B subunit (Hatton and Paoletti, 2005 and Rauner and Köhr, 2011), where the role of each subunit cannot be established using currently available pharmacological tools. Additional problems in relating function to GluN2 subunit composition include their different spatiotemporal expression profiles. For example, in younger neurons, GluN2B is predominant and as such

may mediate excitotoxicity Selleck Sirolimus simply because most NMDARs are GluN2B-containing. Moreover, GluN2B- and GluN2A-containing NMDARs may be enriched at extrasynaptic and synaptic sites, respectively (Groc et al., 2006, Martel et al., 2009 and Tovar and Westbrook, 1999, but see Harris and Pettit, 2007 and Thomas et al., 2006). Since receptor location may be a determinant of excitotoxicity irrespective of subunit composition (Hardingham and Bading, 2010), a location-dependent effect may be misinterpreted as a subunit-specific effect. We have eschewed pharmacocentric approaches in favor of molecular genetics to determine whether equivalent levels of Ca2+ influx through GluN2A- and GluN2B-containing NMDARs differentially affect neuronal viability. We hypothesized that any differences would be due to their large CTDs because this is the primary area of sequence divergence, as well as being the part of GluN2 known to bind intracellular

signaling/scaffolding proteins (Ryan et al., 2008). By studying signaling from wild-type and chimeric GluN2A/2B subunits, using both acutely expressed subunits Afatinib as well as a mouse knockin model, we find that the presence of the CTD2B in an NMDAR renders Ca2+ influx through this receptor more toxic than the presence of CTD2A. This difference is observed in vivo as well as in vitro and is attributable in part to enhanced physical/functional coupling of CTD2B to the PSD-95/nNOS signaling cassette, which suppresses prosurvival CREB-mediated

gene expression, rendering neurons vulnerable to excitotoxic cell death. We wanted to investigate whether the subtype of GluN2 CTD influences the excitotoxicity of a given amount of NMDAR-mediated ion flux. We created constructs encoding and chimeric receptors based on GluN2B and GluN2A but with their respective CTDs replaced (denoted as CTR) with each other’s (GluN2B2A(CTR) and GluN2A2B(CTR), respectively, Figure 1A). In rat hippocampal neurons, we first expressed either wild-type GluN2BWT or GluN2B2A(CTR), at a developmental stage where endogenous NMDARs are overwhelmingly GluN2B-containing (Martel et al., 2009). Expression of GluN2BWT or GluN2B2A(CTR) both enhanced whole-cell currents to a similar level (Figure 1B) and did not differentially affect the proportion of extrasynaptic NMDARs (Figure 1C), as assessed by the “quantal block” method of irreversibly blocking synaptically located NMDARs (Papadia et al., 2008).

(Figure 1D) However, mEPSC amplitudes of the remaining synapses

(Figure 1D). However, mEPSC amplitudes of the remaining synapses were normal in these mice (Figure 1E). These data suggest that PSD-95 is important for new synapse formation after EO, but in the absence of PSD-95, remaining synapses are still able to add glutamate receptors and be potentiated. To identify

the dendritic location of the EO-dependent synaptic plasticity, we examined the pattern of retinal and cortical afferent arborization on the dendrites of DOV neurons by anterograde labeling of retinal and VC afferents in eGFP mice at P29-30 when the number of high expressing cells was greatest (Figure 2A and Figure S2). VC axons were most dense in the deeper portion of the sSC, whereas contralateral retinal axons preferentially occupied more superficial positions (Figures 2B–2D). All eGFP-labeled DOV neurons were reproducibly located in the transition PARP phosphorylation zone between the two projections, and electrical stimulation of retinal and cortical axons where they enter together in the brachium of the

sSC could evoke unitary postsynaptic responses in these neurons (data not shown). We identified the potential locus of contact of retinal and cortical axons onto these neurons, by analyzing the colocalization of each afferent population and the eGFP-labeled Doxorubicin in vivo dendritic arbor (Figures 2E–2G). The degree of chance overlap was estimated by rotation of the images containing the particular afferent label 90° in the plane of section with respect to the images containing the GFP label (Supplemental Experimental Procedures). The mean size and number of overlapped pixel clusters in rotated images was significantly smaller than control

images. This is demonstrated in Figure 2E (arrowhead), where a portion of a labeled retinal axon is observed to course alongside a length of eGFP dendrite. DOV dendrites are highly branched with a variable dendritic branching structure and did not conform to standard definitions of secondary or tertiary branches used in traditional classification schemes for pyramidal neurons. To examine the relationship of these afferent projections to dendritic structure we subdivided the arbor regions ADP ribosylation factor by caliber at each branch point with successively thinner segments ranked from 1 to 4. Three-dimensional neurolucida reconstructions of two neurons, including the labeled neuron in Figure 2, illustrate the distribution of ranked segments (Figure 2H) (see Supplemental Experimental Procedures for classification details). Dendrite caliber rank is a significant factor affecting the distribution of potential contact points for both retinal (F statistic = 11.58, n = 43, p < 0.05) and cortical (F = 3.57, n = 37, p < 0.0001) axons (Figure 2I, significance between calibers assessed with Games-Howell post hoc).

Careful analysis revealed a clear principle underlying the fine-s

Careful analysis revealed a clear principle underlying the fine-scale organization of these inputs: synapses that are located near each other on the same dendritic branch exhibit a higher degree of temporal correlation than synaptic pairs on different dendrites. By blocking action potential firing or N-methyl-D-aspartate (NMDA) receptor activation in slices for several days we showed that this clustering of synaptic inputs is activity-dependent. Thus, by quantifying and comparing a large population of functional synaptic inputs across the dendritic arborization

(the “synaptome”; DeFelipe, 2010) of developing pyramidal neurons, we revealed that developing synapses are Lumacaftor chemical structure functionally clustered on developing dendrites and that clustering requires spontaneous activity. To monitor the spatiotemporal patterns of spontaneous synaptic activation in developing neurons we performed simultaneous patch-clamp recordings and calcium imaging of hippocampal CA3 pyramidal neurons in organotypic slices from neonatal rats (postnatal [P] 0–2, days in vitro [DIV] 2–4). Patch-clamp recordings in voltage-clamp mode

revealed spontaneously occurring synaptic currents, most likely representing unitary synaptic events (1.8 ± 0.62 Hz; mean ± standard deviation [SD] per cell), as well as bursts of synaptic inputs, previously described as giant depolarizing potentials (GDPs; Ben-Ari et al., 1989 and Bonifazi et al., 2009). We determined selleck inhibitor the occurrence of bursts using an adapted version of the Rank Surprise method (Gourévitch and Eggermont, 2007; for details see Experimental Procedures). Bursts of synaptic inputs occurred at a rate of 15.02 ± 2.06 min−1, which is in the range measured in previous in vitro and in vivo recordings (Ben-Ari et al., 1989 and Leinekugel et al., 2002). In fact, the distribution of burst interevent intervals (Figure S1 available online) was virtually identical to that previously described in the hippocampus of developing rats in vivo (P4–6; Leinekugel et al., these 2002), demonstrating that not only the general connectivity

(Frotscher et al., 1990 and Stoppini et al., 1991), but also fundamental functional parameters are maintained in the hippocampal slice culture preparation. Calcium imaging in apical dendrites within stratum radiatum and stratum pyramidale (<200 μm from the soma) revealed spontaneous local calcium transients that occurred at an average rate of 68 ± 43.8 min−1 mm−1 dendrite ( Figure 1A). The majority of local calcium transients were observed in dendritic shafts and not in spines, because there are only very few spines present on dendrites of CA3 pyramidal neurons during this developmental period. Global calcium transients, which can also occur spontaneously in developing CA3 pyramidal neurons and depend on action potential firing, were not observed, since the membrane potential was clamped at −55 mV, the resting membrane potential of neonatal CA3 pyramidal neurons ( Safiulina et al., 2006 and Sipilä et al., 2006).

Data were filtered at 9–15 kHz and sampled at 50 kHz with a Digid

Data were filtered at 9–15 kHz and sampled at 50 kHz with a Digidata 1440 interface controlled by pClamp Software (Molecular Devices, Union City, CA). Electrode resistance in the bath ranged from 2 to 5 MΩ and series resistance ranged from 8 to 20 MΩ. Only cells with an input resistance <300 MΩ were selected to exclude recordings from newly generated granule cells (Liu et al., 1996 and Schmidt-Hieber et al., 2004). The internal solution contained [in mM] 130 K-gluconate,

20 KCl, 10 HEPES-acid, 0.16 EGTA, 2 Mg-ATP, 2 Na2-ATP, and 200 μM Alexa 488 or 594 (Invitrogen) (pH 7.2), osmolality 295 mOsm. Voltages were corrected for the calculated liquid-junction potential of +14.5 mV. Dendritic recording electrodes were see more made from thick walled borosilicate glass capillaries (GB200-8F, Science Products) on a horizontal puller (P-97, Sutter Instruments) and used without further modifications. Dual-whole cell recordings were performed from the soma (2–5 MΩ electrode resistance) and dendrites (20–30 MΩ electrode resistance) using a BVC-700 amplifier (Dagan Corporation). The series resistance

of the dendritic recordings was 100.7 ± 5.2 MΩ (60–135 MΩ, not correlated with distance, Pearson’s r = 0.31, p = 0.15). Dendritic input resistance was 374 ± 45 MΩ (correlated with distance, Pearson’s r = 0. 64, p = 0.003, control recordings see Supplemental Experimental Procedures). Drug application was carried out either via a local application via www.selleckchem.com/products/pf-06463922.html a glass microelectrode or via bath application. In addition, in some experiments, dual dendritic and somatic patch-clamp recordings were obtained and EPSPs were evoked both by current injection and sucrose puff application. Electrical two-pathway stimulation was performed with two theta-glass pipettes filled with ACSF, positioned near the same granule cell in the middle and outer molecular layers, and connected to two stimulus isolators (AM-Systems) operating in bipolar constant current mode. Two-photon excitation fluorescence Resminostat microscopy

was combined with IR-SCG using an ultrafast Ti:Sa laser (950 nm, Chameleon Ultra, Coherent) coupled to a microscope (BX-51, Olympus) equipped with a galvanometer-based scanning system (Ultima, Prairie Technologies). IR-SCG images were generated by spatially filtering the forward scattered infrared laser light with an oblique illumination field stop in the condenser and subsequent detection with a substage photomultiplier tube. An enhanced frequency of unitary EPSPs was evoked by local application of high-osmolar external solution, consisting of normal ACSF with 300 mOsm sucrose and 1 μM TTX added. Two-photon glutamate uncaging at dendrites of dentate granule cells was performed using a microscope equipped with a galvanometer-based scanning system (Prairie Technologies) to photorelease MNI-caged-L-glutamate (Biozol; 12 mM applied via a patch pipette above slice) at multiple dendritic spines.

In order to avoid any possible food effects on the absorption par

In order to avoid any possible food effects on the absorption parameters, only studies for which the formulations were this website administrated in fasted conditions were considered. The main pharmacokinetic parameter of interest was the AUC. Whenever reported, the relative bioavailability between the IR and CR formulation, in terms of the AUC ratio (CR/IR) and its 90% confidence interval was employed. Otherwise it was calculated employing an approximation of the Fieller’s inhibitors Theorem (Fieller,

1954 and Motulsky, 2010) using the reported AUCs, only when both CR and IR formulations were investigated in the same set of subjects. The detailed calculation method is described in the Supplementary Material. For the analysis of the impact of the controlled release formulations on fa, FG and systemic exposure, a

series of simulations were conducted employing the Advanced Dissolution HDAC inhibitor Absorption and Metabolism (ADAM) model within the Simcyp® population-based simulator ( Jamei et al., 2009b) Version 12 Release 2 (Simcyp Limited, Sheffield, UK). The ADAM model is a PBPK absorption model that integrates the drug physicochemical and biopharmaceutical properties (e.g. release profile, solubility, permeability, particle size, affinity for metabolic enzymes, etc.) and the human physiology (e.g. gastric empting, intestinal transit times, GI fluid volumes, metabolic enzyme abundances, blood flows, bile secretion, etc.) and their variability ( Jamei et al., 2009b and Jamei et al., 2009c). Within the ADAM model the anatomy of the human GI tract is represented by nine consecutive segments (stomach, duodenum, jejunum 1 and 2, ileum 1–4, and colon). Each segment is described as a smooth cylinder with the anatomical and physiological characteristics of each segment accounted for, i.e., fluid

dynamics, pH, bile salt concentration, surface area, blood flows, gut wall mass and volume, etc. Drug transit throughout the segments is modelled as first order unidirectional process, from the stomach to the colon. In each segment the amount of drug is distributed between four different states: drug in formulation, drug released (undissolved), drug dissolved, and drug degraded in the lumen. The dissolution rate can either be inputted from an in vitro dissolution profile and/or estimated from a built-in diffusion Adenosine layer model (DLM), it is assumed that only dissolved drug can be absorbed. Drug absorption into the gut wall is modelled as a first order process depending on the drug’s intestinal permeability and the segment’s physiological characteristics. When required, Michaelis–Menten kinetics can be used to model carrier mediated intestinal uptake and/or efflux. The intestinal regional distribution pattern of a given transporter is incorporated and is expressed relative to the abundance in the jejunum ( Jamei et al., 2009c and Mouly and Paine, 2003).