Three-pool Model Research Articles

Applying the Markov chain in natural language processing and three-pool model

This paper delves into the application of Markov chains in Natural Language Processing (NLP), and the Markov Chain Monte Carlo (MCMC) methodology relevant to the three-pool model. The former outlines the basic principles of Markov chains, highlighting their utility in predicting word sequences in language modelling and text generation, despite certain limitations. Also, the former describes mathematical frameworks like n-gram models that enhance prediction accuracy by considering multiple preceding words. It acknowledges challenges in NLP such as oversimplification and emotional depth, as well as computational issues in higher-order models. It concludes by discussing the integration of Markov chains with other models to mitigate these limitations, and their enduring relevance in computational linguistics. The later investigates the MCMC methodology, a seminal development in the field of statistical inference, which is especially useful when analysing complicated systems when traditional statistical techniques are inadequate. Moreover, this later explores the fundamental concepts of MCMC, clarifies how it is inherently related to Markov chains, presents the three-pool model that is commonly applied to models of physical, chemical, or ecological systems, and discusses how MCMC can be used to analyse these models.

Optimizing duration of incubation experiments for understanding soil carbon decomposition

Laboratory incubation is a commonly used method to measure the decomposition of soil organic carbon (SOC). While incubation experiments are conducted across a wide range of durations that may vary from hours to years, no method is available to determine an optimal duration of the incubation experiment so that SOC decomposition can be best understood. Here we presented a novel approach to determine the optimal duration called OPtimal Incubation Duration (OPID). The OPID approach quantifies information gained from an ongoing incubation experiment and determines the time point when SOC decomposition rates can be well quantified. Statistically, the OPID approach is based on a progressive data assimilation algorithm that iteratively assimilates data from an ongoing incubation experiment into a three-pool first-order SOC decomposition model. Using a published incubation data set under different temperatures as a case study, we first generated synthetic daily data, and then fed the data into the three-pool model iteratively to observe the changes of model performance. We found that the accuracy of model projections increased with incubation period and exhibited a trade-off between initial model performance and the time towards accurate projection among different temperatures of incubation. The optimal incubation duration was 347, 212, and 126 days under incubation temperatures of 15 °C, 25 °C and 35 °C, respectively. Comparing the parameters with which from the synthetic daily data, if the incubation period was shorter than the optimal durations, then the decomposition rate of the fast-turnover pool was underestimated and those of the slow pools were overestimated. Sensitivity analysis indicated that optimal incubation duration was negatively correlated with proportion of slow-turnover carbon pools, turnover rates, and initial carbon content, respectively. Our study suggested that long-term incubation experiments are necessary for capturing the dynamics of slow-turnover carbon pools. However, the additional data may not be helpful for model performance if the incubation duration is longer than the optimum. Our study provides a tool for soil scientists to design more effective incubation experiments.DA: data assimilation; PDA: progressive data assimilation; Cum CO2: cumulative CO2 emission from soil; opt: optimal duration;

Particulate and mineral-associated organic carbon turnover revealed by modelling their long-term dynamics

Particulate (POC) and mineral-associated organic carbon (MOC) are measurable carbon pools with distinct function. Their turnover properties have been rarely assessed because of their contrasting stabilization and destabilization processes and the difficulty of in situ monitoring. In this study we used two carbon models (a three-pool and a four-pool model) driven by measured POC, MOC and a more resistant charred organic carbon (COC) pool to obtain insights into the turnover of POC and MOC and to predict long-term soil organic carbon (SOC) dynamics. The models were constrained by measurements of POC, MOC and COC at 159 long-term trials (average trial duration is 22 years) across Australian agricultural regions. Results showed that POC-, MOC- and COC-constrained models, particularly the three-pool model, have less parameter collinearity and predict less uncertainties in most model parameters as well as in SOC dynamics and its vulnerability, compared with the models constrained by total SOC alone. The three-pool model estimated an average decay rate of 0.46 and 0.044 yr−1 for POC and MOC, respectively, across the trials. The four-pool model provided additional insights that on average a large fraction of MOC (28% on average across the trials) is physically protected against decomposition, and the remaining fraction is labile with an average decay rate of 0.068 yr−1. The existence of protected MOC results in prolonged overall residence time of MOC. Additionally, we found that the turnover of POC and MOC are distinctly influenced by climate and soil properties with involvement of non-linear relationships. These results shed new lights on the dynamics of measurable functional SOC pools and demonstrate that models constrained by these pools can provide more accurate predictions of model parameters thereby more accurate projections of SOC dynamics compared to models constrained by total SOC only.

Simulating the Interplay between the Uptake of Inorganic Phosphate and the Cell Phosphate Metabolism under Phosphorus Feast and Famine Conditions in Chlorella vulgaris.

Using a mathematical simulation approach, we studied the dynamics of the green microalga Chlorella vulgaris phosphate metabolism response to shortage and subsequent replenishing of inorganic phosphate in the medium. A three-pool interaction model was used to describe the phosphate uptake from the medium, its incorporation into the cell organic compounds, its storage in the form of polyphosphates, and culture growth. The model comprises a system of ordinary differential equations. The distribution of phosphorous between cell pools was examined for three different stages of the experiment: growth in phosphate-rich medium, incubation in phosphate-free medium, and phosphate addition to the phosphorus-starving culture. Mathematical modeling offers two possible scenarios for the appearance of the peak of polyphosphates (PolyP). The first scenario explains the accumulation of PolyP by activation of the processes of its synthesis, and the decline in PolyP is due to its redistribution between dividing cells during growth. The second scenario includes a hysteretic mechanism for the regulation of PolyP hydrolysis, depending on the intracellular content of inorganic phosphate. The new model of the dynamics of P pools in the cell allows one to better understand the phenomena taking place during P starvation and re-feeding of the P-starved microalgal cultures with inorganic phosphate such as transient PolyP accumulation. Biotechnological implications of the observed dynamics of the polyphosphate pool of the microalgal cell are considered. An approach enhancing the microalgae-based wastewater treatment method based on these scenarios is proposed.

Conversion to bioenergy crops alters the amount and age of microbially-respired soil carbon

Bioenergy cropping systems have the potential to supply plant biomass as lignocellulosic feedstock for biofuels and bioproducts that will reduce reliance on fossil energy. Identifying the effects of alternative bioenergy cropping systems on soil carbon (C) is necessary to assess the sustainability of renewable fuels. We measured the response of soil organic carbon (SOC) pools to four bioenergy cropping systems using soils collected at the establishment of the field trials and after five years in two soils of contrasting texture: a fine-textured silt loam (Mollisol) in south central Wisconsin and a coarse-textured sandy loam (Alfisol) in southwestern Michigan, USA. Crop management followed region-specific practices with no till with the intention of reducing soil C losses from cultivation. Cropping systems included an annual monoculture (continuous corn), two perennial monocultures (switchgrass and hybrid poplar), and a perennial polyculture (restored native prairie). Using a 365-d laboratory soil incubation and a three-pool model, we estimated sizes and turnover times of SOC in surface (0–10 cm) and deeper soils (25–50 cm). After five years, all soils had less bioavailable C as measured by microbial respiration. To determine potential differences in soil C turnover under annual and perennial monocultures, we measured radiocarbon abundance (14C) of bulk soils and respired CO2 under corn and switchgrass. Respired-CO2 was more depleted in 14C over time, indicating preferential respiration of relatively “old C” after five years. Decreased microbial respiration rates after five years of bioenergy cropping systems offer the potential for the eventual reduction of soil C losses after conversion to no till. However, the 14C-CO2 data suggest that previously-protected C pools may become depleted over time, especially with continued removal of plant inputs. Results show that conversion of conventional field-crop agriculture to bioenergy cropping systems may not provide belowground C benefits in the short term, as indicated by reductions in the size of the active pool. Reduced total soil respiration over the length of the study, as well as system-specific differences in soil respiration (monoculture annuals < monoculture perennial < polyculture perennials), suggest C loss may decline in perennial polyculture systems as they age. SOM pools responded differently to bioenergy crop management on soils with contrasting texture, highlighting the importance of geography in predicting belowground consequences of intensified agricultural production.

Determinants of carbon release from the active layer and permafrost deposits on the Tibetan Plateau.

The sign and magnitude of permafrost carbon (C)-climate feedback are highly uncertain due to the limited understanding of the decomposability of thawing permafrost and relevant mechanistic controls over C release. Here, by combining aerobic incubation with biomarker analysis and a three-pool model, we reveal that C quality (represented by a higher amount of fast cycling C but a lower amount of recalcitrant C compounds) and normalized CO2–C release in permafrost deposits were similar or even higher than those in the active layer, demonstrating a high vulnerability of C in Tibetan upland permafrost. We also illustrate that C quality exerts the most control over CO2–C release from the active layer, whereas soil microbial abundance is more directly associated with CO2–C release after permafrost thaw. Taken together, our findings highlight the importance of incorporating microbial properties into Earth System Models when predicting permafrost C dynamics under a changing environment.

Erratum: A Three-Pool Model Dissecting Readily Releasable Pool Replenishment at the Calyx of Held.

Scientific Reports 5: Article number: 9517; published online: 31 March 2015; updated: 25 August 2016 In the original version of this Article, there were errors in Affiliation 1 which was incorrectly listed as ‘State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Physiology and Biophysics, School of Life Sciences, Fudan University, Shanghai, P.

Reduction of hexavalent chromium by fasted and fed human gastric fluid. II. Ex vivo gastric reduction modeling

To extend previous models of hexavalent chromium [Cr(VI)] reduction by gastric fluid (GF), ex vivo experiments were conducted to address data gaps and limitations identified with respect to (1) GF dilution in the model; (2) reduction of Cr(VI) in fed human GF samples; (3) the number of Cr(VI) reduction pools present in human GF under fed, fasted, and proton pump inhibitor (PPI)-use conditions; and (4) an appropriate form for the pH-dependence of Cr(VI) reduction rate constants. Rates and capacities of Cr(VI) reduction were characterized in gastric contents from fed and fasted volunteers, and from fasted pre-operative patients treated with PPIs. Reduction capacities were first estimated over a 4-h reduction period. Once reduction capacity was established, a dual-spike approach was used in speciated isotope dilution mass spectrometry analyses to characterize the concentration-dependence of the 2nd order reduction rate constants. These data, when combined with previously collected data, were well described by a three-pool model (pool 1 = fast reaction with low capacity; pool 2 = slow reaction with higher capacity; pool 3 = very slow reaction with higher capacity) using pH-dependent rate constants characterized by a piecewise, log-linear relationship. These data indicate that human gastric samples, like those collected from rats and mice, contain multiple pools of reducing agents, and low concentrations of Cr(VI) (<0.7 mg/L) are reduced more rapidly than high concentrations. The data and revised modeling results herein provide improved characterization of Cr(VI) gastric reduction kinetics, critical for Cr(VI) pharmacokinetic modeling and human health risk assessment.

Multicomponent T2 analysis of articular cartilage with synovial fluid partial volume correction.

To investigate the use of a three-pool model to account for the confounding effects of synovial fluid on multicomponent T2 analysis of articular cartilage using Multicomponent Driven Equilibrium Single Shot Observation of T1 and T2 (mcDESPOT). mcDESPOT was performed on the knee of eight asymptomatic volunteers and eight patients with osteoarthritis at 3.0T with multicomponent T2 maps created using the two-pool model and a three-pool model containing a nonexchanging synovial fluid water pool. The fraction of the fast-relaxing water component (FF ) and the T2 relaxation times for the fast-relaxing (T2F ) and slow-relaxing (T2S ) water components were measured in the superficial and deep layers of patellar cartilage using the two-pool and three-pool models in asymptomatic volunteers and patients with osteoarthritis and were compared using Wilcoxon signed rank tests. Within the superficial layer of patellar cartilage, FF was 22.5% and 25.6% for asymptomatic volunteers and 21.3% and 22.8% for patients with osteoarthritis when using the two-pool and three-pool models, respectively, while T2S was 73.9 msec and 62.0 msec for asymptomatic volunteers and 72.0 msec and 63.1 msec for patients with osteoarthritis when using the two-pool and three-pool models, respectively. For both asymptomatic volunteers and patients with osteoarthritis, the two-pool model provided significantly (P < 0.05) lower FF and higher T2S than the three-pool model, likely due to the effects of synovial fluid partial volume averaging. The effects of partial volume averaging between superficial cartilage and synovial fluid may result in biased multicomponent T2 measurements that can be corrected using an mcDESPOT three-pool model containing a nonexchanging synovial fluid water pool.

Resistance exercise training and circulatory responses to feeding and skeletal muscle protein anabolism in older men.

Sarcopenia, the age-related loss of muscle mass, contributes to frailty and the loss of independence in older adults. It is well known that ageing results in a decreased sensitivity of skeletal muscle to the anabolic effects of dietary protein, and one explanation for this may be the age-related reduction in muscle leg blood flow and microvascular blood volume (MBV). Low MBV could compromise the postprandial transport of key amino acids and insulin to skeletal muscle where they are known to stimulate muscle protein synthesis (MPS) and arrest rates of muscle protein breakdown (MPB), respectively. As a result, strategies that enhance MBV in older adults may augment the delivery of amino acids and insulin to skeletal muscle following a meal and thus serve as a viable means to combat sarcopenia.

A three-pool model dissecting readily releasable pool replenishment at the calyx of held.

Although vesicle replenishment is critical in maintaining exo-endocytosis recycling, the underlying mechanisms are not well understood. Previous studies have shown that both rapid and slow endocytosis recycle into a very large recycling pool instead of within the readily releasable pool (RRP), and the time course of RRP replenishment is slowed down by more intense stimulation. This finding contradicts the calcium/calmodulin-dependence of RRP replenishment. Here we address this issue and report a three-pool model for RRP replenishment at a central synapse. Both rapid and slow endocytosis provide vesicles to a large reserve pool (RP) ~42.3 times the RRP size. When moving from the RP to the RRP, vesicles entered an intermediate pool (IP) ~2.7 times the RRP size with slow RP-IP kinetics and fast IP-RRP kinetics, which was responsible for the well-established slow and rapid components of RRP replenishment. Depletion of the IP caused the slower RRP replenishment observed after intense stimulation. These results establish, for the first time, a realistic cycling model with all parameters measured, revealing the contribution of each cycling step in synaptic transmission. The results call for modification of the current view of the vesicle recycling steps and their roles.

Removal of cerebrospinal fluid partial volume effects in quantitative magnetization transfer imaging using a three-pool model with nonexchanging water component.

Parameters of the two-pool model describing magnetization transfer (MT) in macromolecule-rich tissues may be significantly biased in partial volume (PV) voxels containing cerebrospinal fluid (CSF). The purpose of this study was to develop a quantitative MT (qMT) method that provides indices insensitive to CSF PV averaging. We propose a three-pool MT model, in which PV macro-compartment is modeled as an additional nonexchanging water pool. We demonstrate the feasibility of model parameter estimation from several MT-weighted spoiled gradient echo datasets. We validated the three-pool model in numerical, phantom, and in vivo studies. PV averaging with the free water compartment reduces all qMT parameters, most significantly affecting macromolecular proton fraction (MPF) and cross-relaxation rate. Monte-Carlo simulations confirmed stability of the three-pool model fit. Unlike the standard two-pool model, the three-pool model qMT parameters were not affected by PV averaging in simulations and phantom studies. The three-pool model fit allowed CSF PV correction in brain PV voxels and resulted in good correlation with standard two-pool model parameters in non-PV voxels. Quantitative MT imaging based on a three-pool model with a non-exchanging water component yields a set of CSF-insensitive qMT parameters, which may improve MPF-based assessment of myelination in structures strongly affected by CSF PV averaging such as brain gray matter.

Oscillatory behavior of two nonlinear microbial models of soil carbon decomposition

Abstract. A number of nonlinear models have recently been proposed for simulating soil carbon decomposition. Their predictions of soil carbon responses to fresh litter input and warming differ significantly from conventional linear models. Using both stability analysis and numerical simulations, we showed that two of those nonlinear models (a two-pool model and a three-pool model) exhibit damped oscillatory responses to small perturbations. Stability analysis showed the frequency of oscillation is proportional to √(&amp;amp;varepsilon;−1−1) Ks/Vs in the two-pool model, and to √(&amp;amp;varepsilon;−1−1) Kl/Vl in the three-pool model, where &amp;amp;varepsilon; is microbial growth efficiency, Ks and Kl are the half saturation constants of soil and litter carbon, respectively, and /Vs and /Vl are the maximal rates of carbon decomposition per unit of microbial biomass for soil and litter carbon, respectively. For both models, the oscillation has a period of between 5 and 15 years depending on other parameter values, and has smaller amplitude at soil temperatures between 0 and 15 °C. In addition, the equilibrium pool sizes of litter or soil carbon are insensitive to carbon inputs in the nonlinear model, but are proportional to carbon input in the conventional linear model. Under warming, the microbial biomass and litter carbon pools simulated by the nonlinear models can increase or decrease, depending whether &amp;amp;varepsilon; varies with temperature. In contrast, the conventional linear models always simulate a decrease in both microbial and litter carbon pools with warming. Based on the evidence available, we concluded that the oscillatory behavior and insensitivity of soil carbon to carbon input are notable features in these nonlinear models that are somewhat unrealistic. We recommend that a better model for capturing the soil carbon dynamics over decadal to centennial timescales would combine the sensitivity of the conventional models to carbon influx with the flexible response to warming of the nonlinear model.

Microstructural origins of gadolinium-enhanced susceptibility contrast and anisotropy.

MR histology based on magnetic susceptibility can be used to visualize diamagnetic myelin (and its deterioration) in the central nervous system and is facilitated by the application of high magnetic field strengths and paramagnetic contrast agents. Characterizing the effect of these tools will aid in assessing white matter myelin content and microstructure. Image data from six gadolinium-perfused mouse brain specimens were acquired at 2.0, 7.0, and 9.4 Tesla. Magnetic susceptibility contrast was analyzed for its dependence on field strength, gadolinium concentration, and white matter fiber orientation. A model for this contrast is presented based on the three-pool model for white matter. The specimen data illustrate that white-gray matter susceptibility contrast is field strength independent. White-gray matter contrast improves significantly as a function of gadolinium contrast agent in the tissue, i.e., white matter appears increasingly more diamagnetic relative to gray matter. The simulated data from the model suggest that susceptibility anisotropy of white matter fiber bundles increases nonlinearly as a function of gadolinium concentration due to contrast agent compartmentalization into the extracellular white matter water pool. Using contrast agents in MR histology facilitates white-gray matter susceptibility contrast modulation and the probing of white matter microstructure and orientation.

Quantitative Bayesian model‐based analysis of amide proton transfer MRI

Amide Proton Transfer (APT) reports on contrast derived from the exchange of protons between amide groups and water. Commonly, APT contrast is quantified by asymmetry analysis, providing an ensemble contrast of both amide proton concentration and exchange rate. An alternative is to sample the off-resonant spectrum and fit an exchange model, permitting the APT effect to be quantified, correcting automatically for confounding effects of spillover, field inhomogeneity, and magnetization transfer. Additionally, it should permit amide concentration and exchange rate to be independently quantified. Here, a Bayesian method is applied to this problem allowing pertinent prior information to be specified. A three-pool model was used incorporating water protons, amide protons, and magnetization transfer effect. The method is demonstrated in simulations, creatine phantoms with varying pH and in vivo (n = 7). The Bayesian model-based approach was able to quantify the APT effect accurately (root-mean-square error < 2%) even when subject to confounding field variation and magnetization transfer effect, unlike traditional asymmetry analysis. The in vivo results gave approximate APT concentration (relative to water) and exchange rate values of 3 × 10(-3) and 15 s(-1) . A degree of correlation was observed between these parameter making the latter difficult to quantify with absolute accuracy, suggesting that more optimal sampling strategies might be required.

Comparison of kinetic models for analysis of pyruvate‐to‐lactate exchange by hyperpolarized 13C NMR

The activity of specific enzyme-catalyzed reactions may be detected in vivo by (13) C NMR of hyperpolarized (HP) substrates. The signals from HP substrates and products, acquired over time, have been fitted to a number of different mathematical models to determine fluxes, but these models have not been critically compared. In this study, two-pool and three-pool first-order models were constructed to measure flux through lactate dehydrogenase in isolated glioblastoma cells by NMR detection of lactate and pyruvate following the addition of HP [1-(13) C]pyruvate. Mass spectrometry (MS) was used to independently monitor (13) C enrichment in intra- and extracellular lactate. Six models were evaluated using time-dependent pyruvate C2 and lactate C1 HP NMR data acquired by the use of selective excitation pulses, plus (13) C enrichment data from intracellular and extracellular lactate measured by MS. A three-pool bidirectional model provided the most accurate description of pyruvate metabolism in these cells. With computed values for T(1) of pyruvate and lactate, as well as the effect of pulsing, the initial flux through lactate dehydrogenase was well determined by both the two-pool bidirectional and unidirectional models when only HP data were available. The three-pool model was necessary to fit the combined data from both MS and HP, but the simpler two-pool exchange model was sufficient to determine the (13) C lactate concentration when the lactate appearance was measured only by HP.

Understanding quantitative pulsed CEST in the presence of MT

Phantom experiments in agar and ammonium chloride were performed to evaluate a three-pool model of magnetization transfer and chemical exchange saturation transfer (CEST) in a pulsed saturation transfer experiment. The utility of the pulsed CEST method was demonstrated by varying the pH of the phantoms and observing the effect upon the CEST spectra both with and without the solid agar (the magnetization transfer pool), while fitting the spectra to the Bloch equation model with exchange. Pulsed CEST could be used to robustly quantify parameters related to CEST, including the exchange rate constant describing proton exchange with free water and the concentration of exchanging protons. Furthermore, the exchange rate constant and the CEST pool offset frequency of the ammonium chloride remained unchanged in the presence of a magnetization transfer pool. The logarithm of the fitted exchange rate constant was linearly related to pH: this relationship was maintained in the presence of magnetization transfer.

Optimizing pulsed‐chemical exchange saturation transfer imaging sequences

Chemical exchange saturation transfer (CEST) provides a new imaging contrast mechanism sensitive to labile proton exchange. Pulsed-CEST imaging is better suited to the hardware constraints on clinical imaging systems when compared with traditional continuous wave-CEST imaging methods. However, designing optimum pulsed-CEST imaging sequences entails complicated and time-consuming numerical integrations. In this work, a simplified and computationally efficient technique is provided to optimize the pulsed-CEST imaging sequence. An analysis was performed of the optimal average irradiation power and the optimal irradiation flip angle as a function of the acquisition parameters and sample properties in both a two-pool model and a three-pool model of endogenous amine exchange. Key simulated and experimental results based on a creatine/agar tissue phantom show that (1) the average irradiation power is a more meaningful sequence metric than is the average irradiation field amplitude, (2) the optimal average powers for continuous wave and pulsed-CEST imaging are approximately equal to each other for a relevant range of solute frequency offsets, exchange rates, and concentrations, (3) an irradiation flip angle of 180° is optimal or near optimal, independent of the other acquisition parameters and the sample properties, and (4) higher duty cycles yield higher CEST contrast.

In vivo multi-slice mapping of myelin water content using T2* decay

Quantitative assessment of the myelin water content in the brain can substantially improve our understanding of white matter diseases such as multiple sclerosis. In this study, in vivo myelin water content was estimated using T2* relaxation with multi-slice acquisitions in magnetic resonance imaging (MRI). The main advantages of using T2* relaxation are (1) a low specific absorption rate (SAR), which is especially beneficial for imaging at high field strengths, (2) a short first-echo time (∼2ms) and short echo spacing (∼1ms), which allows for the acquisition of multiple sampling points during the fast decay of the myelin water signal, and (3) fast multi-slice acquisitions. High-resolution and multi-slice myelin water fraction (MWF) maps were obtained in a clinically acceptable scan time at 3T. Five healthy adults were scanned with a multi-gradient-echo sequence to acquire T2* signal decay data. Images with a dimension of 256×256 at eight slice locations were acquired in 8.5min with a signal-to-noise ratio (SNR) of 94.8 in the first-echo images. The SNR was further increased by using an anisotropic diffusion filter. Local field gradients (LFG) were estimated from the acquired multi-slice data, and the LFG-induced signal decays were corrected with a first-order approximation of LFG using the sinc function. The corrected T2* signal decays were analyzed with a three-pool model to quantify MWF. Our results demonstrate the feasibility of in vivo multi-slice mapping of MWF using multi-compartmental analysis of the T2* signal decay.

Synaptic vesicle pools: an update

During the last few decades synaptic vesicles have been assigned to a variety of functional and morphological classes or “pools”. We have argued in the past (Rizzoli and Betz, 2005) that synaptic activity in several preparations is accounted for by the function of three vesicle pools: the readily releasable pool (docked at active zones and ready to go upon stimulation), the recycling pool (scattered throughout the nerve terminals and recycling upon moderate stimulation), and finally the reserve pool (occupying most of the vesicle clusters and only recycling upon strong stimulation). We discuss here the advancements in the vesicle pool field which took place in the ensuing years, focusing on the behavior of different pools under both strong stimulation and physiological activity. Several new findings have enhanced the three-pool model, with, for example, the disparity between recycling and reserve vesicles being underlined by the observation that the former are mobile, while the latter are “fixed”. Finally, a number of altogether new concepts have also evolved such as the current controversy on the identity of the spontaneously recycling vesicle pool.