Intracellular water specific MR of microbead-adherent cells: HeLa cell intracellular water diffusion

Can Single Cell Respiration be Measured by Scanning Electrochemical Microscopy (SECM)?

Ultramicroelectrode (UME), or, equivalently, microelectrode, probes are increasingly used for single-cell measurements of cellular properties and processes, including physiological activity, such as metabolic fluxes and respiration rates. Major challenges for the sensitivity of such measurements include: (i) the relative magnitude of cellular and UME fluxes (manifested in the current); and (ii) issues around the stability of the UME response over time. To explore the extent to which these factors impact the precision of electrochemical cellular measurements, we undertake a systematic analysis of measurement conditions and experimental parameters for determining single cell respiration rates via the oxygen consumption rate (OCR) in single HeLa cells. Using scanning electrochemical microscopy (SECM), with a platinum UME as the probe, we employ a self-referencing measurement protocol, rarely employed in SECM, whereby the UME is repeatedly approached from bulk solution to a cell, and a short pulse to oxygen reduction reaction (ORR) potential is performed near the cell and in bulk solution. This approach enables the periodic tracking of the bulk UME response to which the near-cell response is repeatedly compared (referenced) and also ensures that the ORR near the cell is performed only briefly, minimizing the effect of the electrochemical process on the cell. SECM experiments are combined with a finite element method (FEM) modeling framework to simulate oxygen diffusion and the UME response. Taking a realistic range of single cell OCR to be 1 × 10-18 to 1 × 10-16 mol s-1, results from the combination of FEM simulations and self-referencing SECM measurements show that these OCR values are at, or below, the present detection sensitivity of the technique. We provide a set of model-based suggestions for improving these measurements in the future but highlight that extraordinary improvements in the stability and precision of SECM measurements will be required if single cell OCR measurements are to be realized.

Non-destructive classification of unlabeled cells: Combining an automated benchtop magnetic resonance scanner and artificial intelligence

In order to treat degenerative diseases, the importance of advanced therapy medicinal products has increased in recent years. The newly developed treatment strategies require a rethinking of the appropriate analytical methods. Current standards are missing the complete and sterile analysis of the product of interest to make the drug manufacturing effort worthwhile. They only consider partial areas of the sample or product while also irreversibly damaging the investigated specimen. Two-dimensional T1 / T2 MR relaxometry meets these requirements and is therefore a promising in-process control during the manufacturing and classification process of cell-based treatments. In this study a tabletop MR scanner was used to perform two-dimensional MR relaxometry. Throughput was increased by developing an automation platform based on a low-cost robotic arm, resulting in the acquisition of a large dataset of cell-based measurements. Two-dimensional inverse Laplace transformation was used for post-processing, followed by data classification performed with support vector machines (SVM) as well as optimized artificial neural networks (ANN). The trained networks were able to distinguish non-differentiated from differentiated MSCs with a prediction accuracy of 85%. To increase versatility, an ANN was trained on 354 independent, biological replicates distributed across ten different cell lines, resulting in a prediction accuracy of up to 98% depending on data composition. The present study provides a proof of principle for the application of T1 / T2 relaxometry as a non-destructive cell classification method. It does not require labeling of cells and can perform whole mount analysis of each sample. Since all measurements can be performed under sterile conditions, it can be used as an in-process control for cellular differentiation. This distinguishes it from other characterization techniques, as most are destructive or require some type of cell labeling. These advantages highlight the technique's potential for preclinical screening of patient-specific cell-based transplants and drugs.

Improving MR cell size imaging by inclusion of transcytolemmal water exchange

The goal of the current study is to include transcytolemmal water exchange in MR cell size imaging using the IMPULSED model for more accurate characterization of tissue cellular properties (e.g., apparent volume fraction of intracellular space v in ) and quantification of indicators of transcytolemmal water exchange. We propose a heuristic model that incorporates transcytolemmal water exchange into a multicompartment diffusion-based method (IMPULSED) that was developed previously to extract microstructural parameters (e.g., mean cell size d and apparent volume fraction of intracellular space v in ) assuming no water exchange. For t diff ≤ 5 ms, the water exchange can be ignored, and the signal model is the same as the IMPULSED model. For t diff ≥ 30 ms, we incorporated the modified Kärger model that includes both restricted diffusion and exchange between compartments. Using simulations and previously published in vitro cell data, we evaluated the accuracy and precision of model-derived parameters and determined how they are dependent on SNR and imaging parameters. The joint model provides more accurate d values for cell sizes ranging from 10 to 12 microns when water exchange is fast (e.g., intracellular water pre-exchange lifetime τ in ≤ 100 ms) than IMPULSED, and reduces the bias of IMPULSED-derived estimates of v in , especially when water exchange is relatively slow (e.g., τ in > 200 ms). Indicators of transcytolemmal water exchange derived from the proposed joint model are linearly correlated with ground truth τ in values and can detect changes in cell membrane permeability induced by saponin treatment in murine erythroleukemia cancer cells. Our results suggest this joint model not only improves the accuracy of IMPULSED-derived microstructural parameters, but also provides indicators of water exchange that are usually ignored in diffusion models of tissues.

Geant4 Modeling of Cellular Dosimetry of 188Re: Comparison between Geant4 Predicted Surviving Fraction and Experimentally Surviving Fraction Determined by MTT Assay

BACKGROUND

The importance of cellular dosimetry in both diagnostic and radiation therapy is becoming increasingly recognized.

OBJECTIVE

This study aims to compare surviving fractions, which were predicted using Geant4 and contained three types of cancer cell lines exposed to 188Re with the experimentally surviving fraction determined by MTT assay.

MATERIAL AND METHODS

In this comparative study, Geant4 was used to simulate the transport of electrons emitted by 188Re from the cell surface, cytoplasm, nucleus or medium around the cells. The nucleus dose per decay (S-value) was computed for models of single cell and random monolayer cell. Geant4-computed survival fraction (SF) of cancer cells exposed to 188Re was compared with the experimental SF values of MTT assay.

RESULTS

For single cell model, Geant4 S-values of nucleus-to-nucleus were consistent with values reported by Goddu et al. (ratio of S-values by analytical techniques vs. Geant4 = 0.811-0.975). Geant4 S-values of cytoplasm and cell surface to nucleus were relatively comparable to the reported values (ratio =0.914-1.21). For monolayer model, the values of SCy→N and SCS→N, were greater compared to those for model of single cell (2%-25% and 4%-38% were larger than single cell, respectively). The Geant4 predicted SF for monolayer MCF7, HeLa and A549 cells was in agreement with the experimental data in 10μCi activity (relative error of 2.29%, 2.69% and 2.99%, respectively).

CONCLUSION

Geant4 simulation with monolayer cell model showed the highest accuracy in predicting the SF of cancer cells exposed to homogeneous distribution of 188Re in the medium.

An improved model for prostate diffusion incorporating the results of Monte Carlo simulations of diffusion in the cellular compartment

The purpose of this work was to refine a previously published model of prostate diffusion by incorporating improved estimates of cellular diffusivity obtained by Monte Carlo simulation. Stromal and epithelial cell size and intracellular volume fraction in different grades of cancer were determined from histological images. Diffusion in different mixtures of cells, corresponding to different tumor grades, was simulated and cellular apparent diffusion coefficient and kurtosis values determined. These values were incorporated into the previously published model of prostate diffusion and model predictions compared with values found in the literature. Stromal cell radius and intracellular volume fraction were 3.74 ± 0.96 μm and 13 ± 3% respectively in normal peripheral zone (PZ), and were similar in all grades of cancer. Epithelial cell radius and intracellular volume fraction were 3.40 ± 0.15 μm and 45 ± 5% respectively in normal PZ, rising to 4.75 ± 0.20 μm and 70 ± 8% in high grade cancer. Cellular apparent diffusion coefficient and kurtosis were 1.02 μm² ms^-1 and 0.58 respectively in normal PZ, and 0.61 μm² ms^-1 and 1.15 in high grade cancer (variation in simulation values are less than 0.1%). Agreement between model predictions and measurements were good, with a mean square error of 0.22 μm² ms^-1 . Incorporation of cellular diffusion coefficient and kurtosis values obtained by Monte Carlo simulation into a model of prostate diffusion gives good agreement with published results.

Apparent diffusion coefficient on magnetic resonance imaging (MRI) in bladder cancer: relations with recurrence/progression risk

AIMS

To evaluate the relationship between the apparent diffusion coefficient (ADC) value for bladder cancer and the recurrence/progression risk of post-transurethral resection (TUR).

METHODS

Forty-one patients with initial and non-muscle-invasive bladder cancer underwent MRI from 2009 to 2012. Two radiologists measured ADC values. A pathologist calculated the recurrence/progression scores, and risk was classified based on the scores. Pearson's correlation was used to analyze the correlations of ADC value with each score and with each risk group, and the optimal cut-off value was established based on receiver operating characteristic (ROC) curve analysis. Furthermore, the relationship between actual recurrence / progression of cases and ADC values was examined by Unpaird U test.

RESULTS

There were significant correlations between ADC value and the recurrence score as well as the progression score (P<0.01, P<0.01, respectively). There were also significant correlations between ADC value and the recurrence risk group as well as progression risk group (P=0.042, P<0.01, respectively). The ADC cut-off value on ROC analysis was 1.365 (sensitivity 100%; specificity 97.4%) for the low and intermediate recurrence risk groups, 1.024 (sensitivity 47.4%; specificity 100%) for the intermediate and high recurrence risk groups, 1.252 (sensitivity 83.3%; specificity 81.3%) for the low and intermediate progression risk groups, and 0.955 (sensitivity 87.5%; specificity 63.2%) between the intermediate and high progression risk groups. The difference between the ADC values of the recurrence and nonrecurrence group in Unpaired t test was significant (P<0.05).

CONCLUSION

ADC on MRI in bladder cancer could potentially be useful, non-invasive measurement for estimating the risks of recurrence and progression.

Intracellular water preexchange lifetime in neurons and astrocytes

PURPOSE

To determine the intracellular water preexchange lifetime, τ_i , the "average residence time" of water, in the intracellular milieu of neurons and astrocytes. The preexchange lifetime is important for modeling a variety of MR data sets, including relaxation, diffusion-sensitive, and dynamic contrast-enhanced data sets.

METHODS

Herein, τ_i in neurons and astrocytes is determined in a microbead-adherent, cultured cell system. In concert with thin-slice selection, rapid flow of extracellular media suppresses extracellular signal, allowing determination of the transcytolemmal-exchange-dominated, intracellular T₁ . With this knowledge, and that of the intracellular T₁ in the absence of exchange, τ_i can be derived.

RESULTS

Under normal culture conditions, τ_i for neurons is 0.75 ± 0.05 s versus 0.57 ± 0.03 s for astrocytes. Both neuronal and astrocytic τ_i s decrease within 30 min after the onset of oxygen-glucose deprivation, with the astrocytic τ_i showing a substantially greater decrease than the neuronal τ_i .

CONCLUSIONS

Given an approximate intra- to extracellular volume ratio of 4:1 in the brain, these data imply that, under normal physiological conditions, an MR experimental characteristic time of less than 0.012 s is required for a nonexchanging, two-compartment (intra- and extracellular) model to be valid for MR studies. This characteristic time shortens significantly (i.e., 0.004 s) under injury conditions. Magn Reson Med 79:1616-1627, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Presence of time-dependent diffusion in the brachial plexus

PURPOSE

This work describes the development of a method to measure the variation of apparent diffusion coefficient (ADC) with diffusion time (Δ) in the brachial plexus, as a potential method of probing microstructure.

METHODS

Diffusion-weighted MRI with body signal suppression was used to highlight the nerves from surrounding tissues, and sequence parameters were optimized for sensitivity to change with diffusion time. A porous media-restricted diffusion model based on the Latour-Mitra equation was fitted to the diffusion time-dependent ADC data from the brachial plexus nerves and cord.

RESULTS

The ADC was observed to reduce at long diffusion times, confirming that diffusion was restricted in the nerves and cord in healthy subjects. T2 of the nerves was measured to be 80 ± 5 ms, the diffusion coefficient was found to vary from (1.5 ± 0.1) × 10^-3 mm² /s at a diffusion time of 18.3 ms to (1.0 ± 0.2) × 10^-3 mm² /s at a diffusion time of 81.3 ms.

CONCLUSION

A novel method of probing restricted diffusion in the brachial plexus was developed. Resulting parameters were comparable with values obtained previously on biological systems. Magn Reson Med 79:789-795, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Demonstration of Non-Gaussian Restricted Diffusion in Tumor Cells Using Diffusion Time-Dependent Diffusion-Weighted Magnetic Resonance Imaging Contrast

The diffusion-weighted magnetic resonance imaging (DWI) technique enables quantification of water mobility for probing microstructural properties of biological tissue and has become an effective tool for collecting information about the underlying pathology of cancerous tissue. Measurements using multiple b-values have indicated biexponential signal attenuation, ascribed to “fast” (high ADC) and “slow” (low ADC) diffusion components. In this empirical study, we investigate the properties of the diffusion time (Δ)-dependent components of the diffusion-weighted (DW) signal in a constant b-value experiment. A xenograft gliobastoma mouse was imaged using Δ = 11 ms, 20 ms, 40 ms, 60 ms, and b = 500–4000 s/mm² in intervals of 500 s/mm². Data were corrected for EPI distortions, and the Δ-dependence on the DW-signal was measured within three regions of interest [intermediate- and high-density tumor regions and normal-appearing brain (NAB) tissue regions]. In this study, we verify the assumption that the slow decaying component of the DW-signal is non-Gaussian and dependent on Δ, consistent with restricted diffusion of the intracellular space. As the DW-signal is a function of Δ and is specific to restricted diffusion, manipulating Δ at constant b-value (cb) provides a complementary and direct approach for separating the restricted from the hindered diffusion component. We found that Δ-dependence is specific to the tumor tissue signal. Based on an extended biexponential model, we verified the interpretation of the diffusion time-dependent contrast and successfully estimated the intracellular restricted ADC, signal volume fraction, and cell size within each ROI.

Estimation of the Number of Compartments Associated With the Apparent Diffusion Coefficient in MRI: The Theoretical and Experimental Investigations

OBJECTIVE

The goal of the present study was to estimate the number of compartments and the mean apparent diffusion coefficient (ADC) value with the use of the DWI signal curve.

MATERIALS AND METHODS

A useful new mathematic model that includes internal correlation among subcompartments with a distinct number of compartments was proposed. The DWI signal was simulated to estimate the approximate association between the number of subcompartments and the molecular density, with density corresponding to the ratio of the ADC values of the compartments, as determined using the Monte Carlo method.

RESULTS

Various factors, such as energy depletion, temperature, intracellular water accumulation, changes in the tortuosity of the extracellular diffusion paths, and changes in cell membrane permeability, have all been implicated as factors contributing to changes in the ADC of water (ADCw); therefore, one may consider them as pseudocompartments in the new model proposed in this study. The lower the coefficient is, the lower the contribution of the compartment to the net signal will be. The results of the simulation indicate that when the number of compartments increases, the signal will become significantly lower, because the gradient factor (i.e., the b value) will increase. In other words, the signal curve is approximately linear at all b values when the number of compartments in which the tissues have been severely damaged is low; however, when the number of compartments is high, the curve will become constant at high b values, and the perfusion parameters will prevail on the diffusion parameters at low b values. Therefore, normal tissues will be investigated when the number of compartments and the ADC values are high and the b values are low, whereas damaged tissues will be evaluated when the number of compartments and the ADC values are low and the b values are high.

CONCLUSION

The present study investigates damaged tissues at high b values for which the effect of eddy currents will also be compensated. These b values will probably be used in functional MRI.

Intravoxel Incoherent Motion-Magnetic Resonance Imaging as an Early Predictor of Treatment Response to Neoadjuvant Chemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma

The aim of the study was to prospectively evaluate the clinical value of intravoxel incoherent motion (IVIM)-magnetic resonance imaging (MRI) in early predicting the treatment response to neoadjuvant chemotherapy (NAC) for nasopharyngeal carcinoma (NPC). Forty-eight patients with locoregionally advanced NPC were imaged with IVIM-MRI (14 b-factors, 0-1000 s/mm2) on a 3.0-T Magnetic resonance system, at the baseline, and repeatedly at the third and 21st day after NAC started. The IVIM-derived parameters (D*, pure diffusion coefficient; f, perfusion fraction; and D, pseudodiffusion coefficient) were calculated with the Interactive Data Language version 6.3 software. The baseline parameters and their corresponding changes (Δparameter(day)) during NAC were compared using the Student t test or Mann-Whitney U test. Variation analyses of IVIM-derived parameters were tested with intraclass correlation coefficient. Receiver-operating characteristic (ROC) curve analysis was conducted to estimate the best diagnostic accuracy. Statistical analyses were performed on the SPSS 18.0 software, with a 2-tailed probability value, P < 0.05 was considered significant. Among recruited patients, 37 cases were categorized as responders and 11 cases as nonresponders after NAC completed. The intra- and interobserver intraclass correlation coefficient of IVIM-derived parameters were excellent, which ranged from 0.858 to 0.971. Compared with the baseline value, at the third and 21st day, the D value was significantly higher and the D* value significantly lower (P < 0.05, P < 0.001, respectively). In contrast, f parameter only changed slightly (P > 0.05). Compared with nonresponders, responders presented a notably lower baseline D value and higher ΔD3, ΔD21, ΔD3*, ΔD21*, and Δf21 (P < 0.05), but no significant change in Δf3 was observed (P > 0.1). The receiver-operating characteristic curve analyses indicated that the threshold of baseline D values that best predicted the responders for primary nasopharynx tumors and metastatic lymph nodes were 0.911  × 10(-3) mm2/s versus 0.951 × 10(-3) mm2/s, and their corresponding area under curve, sensitivity, and specificity were 0.714 versus 0.774, 0.658 versus 0.538, and 0.818 versus 0.944, respectively. IVIM-MRI can potentially early predict the treatment response of NAC for NPC patients. The baseline D value, and early changes in D and D value are better predictors of the chemotherapeutic responsiveness.

Cell hydration as a biomarker for estimation of biological effects of nonionizing radiation on cells and organisms

"Changes in cell hydration" have been hypothesized as an input signal for intracellular metabolic cascade responsible for biological effects of nonionizing radiation (NIR). To test this hypothesis a comparative study on the impacts of different temperature and NIR (infrasound frequency mechanical vibration (MV), static magnetic field (SMF), extremely low frequency electromagnetic field (ELF EMF), and microwave (MW)) pretreated water on the hydration of barley seeds in its dormant and germination periods was performed. In dormant state temperature sensitivity (Q 10) of seed hydration in distilled water (DW) was less than 2, and it was nonsensitive to NIR treated DW, whereas during the germination period (48-72 hours) seeds hydration exhibited temperature sensitivity Q 10 > 2 and higher sensitivity to NIR treated DW. Obtained data allow us to suggest that the metabolic driving of intracellular water dynamics accompanied by hydrogen bonding and breaking is more sensitive to NIR-induced water structure changes in seed bathing aqua medium than the simple thermodynamic processes such as osmotic gradient driven water absorption by seeds in dormant state. Therefore, cell hydration is suggested to be a universal and extrasensitive biomarker for detection of biological effects of NIR on cells and organisms.

Dynamic properties of water in breast pathology depend on the histological compounds: distinguishing tissue malignancy by water diffusion coefficients

Background

The parameters that characterize the intricate water diffusion in tumors may also reveal their distinct pathology. Specifically, characterization of breast cancer could be aided by diffusion magnetic resonance.

The present in vitro study aimed to discover connections between the NMR biexponential diffusion parameters [fast diffusion phase (D_FDP ), slow diffusion phase (D_SDP ), and spin population of fast diffusion phase (P₁)] and the histological constituents of nonmalignant (control) and malignant human breast tissue. It also investigates whether the diffusion coefficients indicate tissue status.

Methods

Post-surgical specimens of control (mastopathy and peritumoral tissues) and malignant human breast tissue were placed in an NMR spectrometer and diffusion sequences were applied. The resulting decay curves were analyzed by a biexponential model, and slow and fast diffusion parameters as well as percentage signal were identified. The same samples were also histologically examined and their percentage composition of several tissue constituents were measured: parenchyma (P), stroma (St), adipose tissue (AT), vessels (V) , pericellular edema (PCE), and perivascular edema (PVE). Correlations between the biexponential model parameters and tissue types were evaluated for different specimens. The effects of tissue composition on the biexponential model parameters, and the effects of histological and model parameters on cancer probability, were determined by non-linear regression.

Results

Meaningful relationships were found among the in vitro data. The dynamic parameters of water in breast tissue are stipulated by the histological constituents of the tissues (P, St, AT, PCE, and V). High coefficients of determination (R²) were obtained in the non-linear regression analysis: D_FDP (R² = 0.92), D_SDP (R² = 0.81), and P₁(R² = 0.93).

In the cancer probability analysis, the informative value (R²) of the obtained equations of cancer probability in distinguishing tissue malignancy depended on the parameters input to the model. In order of increasing value, these equations were: cancer probability (P, St, AT, PCE, V) (R² = 0.66), cancer probability (D_FDP, D_SDP)(R² = 0.69), cancer probability (D_FDP, D_SDP, P₁) (R² = 0.85).

Conclusion

Histological tissue components are related to the diffusion biexponential model parameters. From these parameters, the relative probability of cancer in a given specimen can be determined with some certainty.

Perfusion and diffusion sensitive 13C stimulated-echo MRSI for metabolic imaging of cancer

Metabolic imaging with hyperpolarized [1-(13)C]-pyruvate can rapidly probe tissue metabolic profiles in vivo and has been shown to provide cancer imaging biomarkers for tumor detection, progression, and response to therapy. This technique uses a bolus injection followed by imaging within 1-2 minutes. The observed metabolites include vascular components and their generation is also influenced by cellular transport. These factors complicate image interpretation, especially since [1-(13)C]lactate, a metabolic product that is a biomarker of cancer, is also produced by red blood cells. It would be valuable to understand the distribution of metabolites between the vasculature, interstitial space, and intracellular compartments. The purpose of this study was to better understand this compartmentalization by using a perfusion and diffusion-sensitive stimulated-echo acquisition mode (STEAM) MRSI acquisition method tailored to hyperpolarized substrates. Our results in mouse models showed that among metabolites, the injected substrate (13)C-pyruvate had the largest vascular fraction overall while (13)C-alanine had the smallest vascular fraction. We observed a larger vascular fraction of pyruvate and lactate in the kidneys and liver when compared to back muscle and prostate tumor tissue. Our data suggests that (13)C-lactate in prostate tumor tissue voxels was the most abundant labeled metabolite intracellularly. This was shown in STEAM images that highlighted abnormal cancer cell metabolism and suppressed vascular (13)C metabolite signals.

Sensitivities of statistical distribution model and diffusion kurtosis model in varying microstructural environments: a Monte Carlo study

The aim of this study was to investigate the microstructural sensitivity of the statistical distribution and diffusion kurtosis (DKI) models of non-monoexponential signal attenuation in the brain using diffusion-weighted MRI (DWI). We first developed a simulation of 2-D water diffusion inside simulated tissue consisting of semi-permeable cells and a variable cell size. We simulated a DWI acquisition of the signal in a volume using a pulsed gradient spin echo (PGSE) pulse sequence, and fitted the models to the simulated DWI signals using b-values up to 2500 s/mm(2). For comparison, we calculated the apparent diffusion coefficient (ADC) of the monoexponential model (b-value=1000 s/mm(2)). In separate experiments, we varied the cell size (5-10-15 μm), cell volume fraction (0.50-0.65-0.80), and membrane permeability (0.001-0.01-0.1mm/s) to study how the fitted parameters tracked simulated microstructural changes. The ADC was sensitive to all the simulated microstructural changes except the decrease in membrane permeability. The ADC increased with larger cell size, smaller cell volume fraction, and larger membrane permeability. The σstat of the statistical distribution model increased exclusively with a decrease in cell volume fraction. The Kapp of the DKI model was exclusively increased with decreased cell size and decreased with increasing membrane permeability. These results suggest that the non-monoexponential models of water diffusion have different, specific microstructural sensitivity, and a combination of the models may give insights into the microstructural underpinning of tissue pathology.

The role of tissue microstructure and water exchange in biophysical modelling of diffusion in white matter

Biophysical models that describe the outcome of white matter diffusion MRI experiments have various degrees of complexity. While the simplest models assume equal-sized and parallel axons, more elaborate ones may include distributions of axon diameters and axonal orientation dispersions. These microstructural features can be inferred from diffusion-weighted signal attenuation curves by solving an inverse problem, validated in several Monte Carlo simulation studies. Model development has been paralleled by microscopy studies of the microstructure of excised and fixed nerves, confirming that axon diameter estimates from diffusion measurements agree with those from microscopy. However, results obtained in vivo are less conclusive. For example, the amount of slowly diffusing water is lower than expected, and the diffusion-encoded signal is apparently insensitive to diffusion time variations, contrary to what may be expected. Recent understandings of the resolution limit in diffusion MRI, the rate of water exchange, and the presence of microscopic axonal undulation and axonal orientation dispersions may, however, explain such apparent contradictions. Knowledge of the effects of biophysical mechanisms on water diffusion in tissue can be used to predict the outcome of diffusion tensor imaging (DTI) and of diffusion kurtosis imaging (DKI) studies. Alterations of DTI or DKI parameters found in studies of pathologies such as ischemic stroke can thus be compared with those predicted by modelling. Observations in agreement with the predictions strengthen the credibility of biophysical models; those in disagreement could provide clues of how to improve them. DKI is particularly suited for this purpose; it is performed using higher b-values than DTI, and thus carries more information about the tissue microstructure. The purpose of this review is to provide an update on the current understanding of how various properties of the tissue microstructure and the rate of water exchange between microenvironments are reflected in diffusion MRI measurements. We focus on the use of biophysical models for extracting tissue-specific parameters from data obtained with single PGSE sequences on clinical MRI scanners, but results obtained with animal MRI scanners are also considered. While modelling of white matter is the central theme, experiments on model systems that highlight important aspects of the biophysical models are also reviewed.

Identification of F-actin as the dynamic hub in a microbial-induced GTPase polarity circuit

Polarity in mammalian cells emerges from the assembly of signaling molecules into extensive biochemical interaction networks. Despite their complexity, bacterial pathogens have evolved parsimonious mechanisms to hijack these systems. Here, we develop a tractable experimental and theoretical model to uncover fundamental operating principles, in both mammalian cell polarity and bacterial pathogenesis. Using synthetic derivatives of the enteropathogenic Escherichia coli guanine-nucleotide exchange factor (GEF) Map, we discover that Cdc42 GTPase signal transduction is controlled by the interaction between Map and F-actin. Mathematical modeling reveals how actin dynamics coupled to a Map-dependent positive feedback loop spontaneously polarizes Cdc42 on the plasma membrane. By rewiring the pathogenic signaling circuit to operate through β-integrin stimulation, we further show how Cdc42 is polarized in response to an extracellular spatial cue. Thus, a molecular pathway of polarity is proposed, centered on the interaction between GEFs and F-actin, which is likely to function in diverse biological systems.

In-cell NMR in mammalian cells: part 2

Delivery of isotope-labeled IDPs into mammalian cells for the purpose of generating suitable in-cell NMR samples can also be facilitated by action of pore-forming bacterial toxins. In the course of this procedure, mammalian cell membranes are permeated for short periods of time in order to enable the influx of exogenous proteins via a concentration gradient between the outside and the inside of the targeted "host" cells. In contrast to CPP-mediated IDP uptake, toxins offer the advantage that cellular protein transduction does not rely on active biological processes like endocytosis, but on simple passive diffusion. Therefore, proteins that are to be delivered into mammalian cells are not required to contain additional "targeting" sequences, and can be employed in their native contexts. The protocol outlined here employs isotope-labeled human α-synuclein, adherent human HeLa cells, and the Streptococcus pyogenes endotoxin Streptolysin O (SLO).

In-cell NMR in mammalian cells: part 1

Many mammalian IDPs exert important biological functions in key cellular processes and often in highly specialized subsets of cells. For these reasons, tools to characterize the structural and functional characteristics of IDPs inside mammalian cells are of particular interest. Moving from bacterial and amphibian in-cell NMR experiments to mammalian systems offers the unique opportunity to advance our knowledge about general IDP properties in native cellular environments. This is never more relevant than for IDPs that exhibit pathological structural rearrangements under certain cellular conditions, as is the case for human α-synuclein in dopaminergic neurons of the substantia nigra in the course of Parkinson's disease, for example. To efficiently deliver isotope-labeled IDPs into mammalian cells is one of the first challenges when preparing a mammalian in-cell NMR sample. The method presented here provides a detailed protocol for the transduction of isotope-labeled α-synuclein, as a model IDP, into cultured human HeLa cells. Cellular IDP delivery is afforded by action of a cell-penetrating peptide (CPP) tag. In the protocol outlined below, the CPP tag is "linked" to the IDP cargo moiety via an oxidative, disulfide-coupling reaction.

Diffusion, confusion and functional MRI

Diffusion MRI has been introduced in 1985 and has had a very successful life on its own. While it has become a standard for imaging stroke and white matter disorders, the borders between diffusion MRI and the general field of fMRI have always remained fuzzy. First, diffusion MRI has been used to obtain images of brain function, based on the idea that diffusion MRI could also be made sensitive to blood flow, through the intravoxel incoherent motion (IVIM) concept. Second, the IVIM concept helped better understand the contribution from different vasculature components to the BOLD fMRI signal. Third, it has been shown recently that a genuine fMRI signal can be obtained with diffusion MRI. This "DfMRI" signal is notably different from the BOLD fMRI signal, especially for its much faster response to brain activation both at onset and offset, which points out to structural changes in the neural tissues, perhaps such as cell swelling, occurring in activated neural tissue. This short article reviews the major steps which have paved the way for this exciting development, underlying how technical progress with MRI equipment has each time been instrumental to expand the horizon of diffusion MRI toward the field of fMRI.

Destroying the ring: Freeing DNA from Ku with ubiquitin

The Ku heterodimer, consisting of the proteins Ku70 and Ku80, is the central component of the non-homologous end joining (NHEJ) pathway of double strand break (DSB) repair. Ku is able to recognize and bind a DSB by virtue of its ring-like structure. Both pre-repair and topologically trapped post-repair Ku heterodimers are thought to be inhibitory to multiple cellular processes. Thus, a regulated mechanism for the removal of Ku from chromatin was predicted to exist. Recent evidence shows that Ku80 is removed from DNA through a ubiquitin-mediated process. Similar processes have been shown to be involved in the regulated dissociation of a host of other proteins from chromatin, and this appears to be a general and conserved mechanism for the regulation of chromatin-associated factors. A potential mechanism for this pathway is discussed.

Comparative analysis of viscosity of complex liquids and cytoplasm of mammalian cells at the nanoscale

We present a scaling formula for size-dependent viscosity coefficients for proteins, polymers, and fluorescent dyes diffusing in complex liquids. The formula was used to analyze the mobilities of probes of different sizes in HeLa and Swiss 3T3 mammalian cells. This analysis unveils in the cytoplasm two length scales: (i) the correlation length ξ (approximately 5 nm in HeLa and 7 nm in Swiss 3T3 cells) and (ii) the limiting length scale that marks the crossover between nano- and macroscale viscosity (approximately 86 nm in HeLa and 30 nm in Swiss 3T3 cells). During motion, probes smaller than ξ experienced matrix viscosity: η(matrix) ≈ 2.0 mPa·s for HeLa and 0.88 mPa·s for Swiss 3T3 cells. Probes much larger than the limiting length scale experienced macroscopic viscosity, η(macro) ≈ 4.4 × 10(-2) and 2.4 × 10(-2) Pa·s for HeLa and Swiss 3T3 cells, respectively. Our results are persistent for the lengths scales from 0.14 nm to a few hundred nanometers.

Changes in intracellular water diffusion and energetic metabolism in response to ischemia in perfused C6 rat glioma cells

This work reports results of experiments in hollow-fiber bioreactor C6 glioma cell cultures where the apparent diffusion coefficient (ADC) of intracellular water (iADC) was measured at diffusion times between 0.83 and 40 ms. The experiments were carried out before and after the onset of permanent ischemia. The changes in iADC following ischemia were dependent on the diffusion time employed in the experiment. An ischemia-induced decrease in the iADC was measured at short diffusion times, while at long diffusion times the iADC increased. Decreases in the iADC measured at short diffusion times are interpreted to be a result of a decrease in the intrinsic diffusivity of intracellular water due to energy failure. Increases in iADC measured at long diffusion times, are interpreted to result from cell swelling.

Influence of cell cycle phase on apparent diffusion coefficient in synchronized cells detected using temporal diffusion spectroscopy

The relationship between the apparent diffusion coefficient of tissue water measured by MR methods and the physiological status of cells is of particular relevance for better understanding and interpretation of diffusion-weighted MRI. In addition, there is considerable interest in developing diffusion-dependent imaging methods capable of providing novel information on tissue microstructure, including intracellular changes. To this end, both the conventional pulsed gradient spin-echo methods and the oscillating gradient spin-echo method, which probes diffusion over very short distance (<<cell size) and time scales, were used to measure apparent diffusion coefficient of synchronized packed HL-60 cells at 7 T. The results show that the pulsed gradient spin-echo method with relatively long diffusion times does not detect changes in apparent diffusion coefficient when structural variations arise during cell division. On the contrary, the oscillating gradient spin-echo method can detect and quantify major changes in intracellular organization that occur during mitosis by appropriate choice of gradient frequency. Cell structural parameters, including cell size, intracellular diffusion coefficient, and surface-to-volume ratio were also obtained by fitting the oscillating gradient spin-echo data to simple analytical models. These oscillating gradient spin-echo features may be used in diffusion-weighted MRI to create parametric maps that may be useful for detecting cancer or changes caused by treatment.

The use of MR-detectable reporter molecules and ions to evaluate diffusion in normal and ischemic brain

As a result of the technical challenges associated with distinguishing the MR signals arising from intracellular and extracellular water, a variety of endogenous and exogenous MR-detectable molecules and ions have been employed as compartment-specific reporters of water motion. Although these reporter molecules and ions do not have the same apparent diffusion coefficients (ADCs) as water, their ADCs are assumed to be directly related to the ADC of the water in which they are solvated. This approach has been used to probe motion in the intra- and extracellular space of cultured cells and intact tissue. Despite potential interpretative challenges with the use of reporter molecules or ions and the wide variety used, the following conclusions are consistent considering all studies: (i) the apparent free diffusive motion in the intracellular space is approximately one-half of that in dilute aqueous solution; (ii) ADCs for intracellular and extracellular water are similar; (iii) the intracellular ADC decreases in association with brain injury. These findings provide support for the hypothesis that the overall brain water ADC decrease that accompanies brain injury is driven primarily by a decrease in the ADC of intracellular water. We review the studies supporting these conclusions, and interpret them in the context of explaining the decrease in overall brain water ADC that accompanies brain injury.

Theoretical models of the diffusion weighted MR signal

Diffusion MRI plays a very important role in studying biological tissue structure and functioning both in health and disease. Proper interpretation of experimental data requires development of theoretical models that connect the diffusion MRI signal to salient features of tissue microstructure at the cellular level. In this review, we present some models (mostly, relevant to the brain) for describing diffusion attenuated MR signals. These range from the simplest approach, where the signal is described in terms of an apparent diffusion coefficient, to rather complicated models, where consideration is given to signals originating from extra- and intracellular spaces and where account is taken of the specific geometry and orientation distribution of cells. To better understand the characteristics of the diffusion attenuated MR signal arising from the complex structure of whole tissue, it is instructive to appreciate first the characteristics of the signal arising from simple single-cell-like structures. For this purpose, we also present here a theoretical analysis of models allowing exact analytical calculation of the MR signal, specifically, a single-compartment model with impermeable boundaries and a periodic structure of identical cells separated by permeable membranes. Such pure theoretical models give important insights into mechanisms contributing to the MR signal formation in the presence of diffusion. In this review we targeted both scientists just entering the MR field and more experienced MR researchers interested in applying diffusion methods to study biological tissues.

Quantitative characterization of tissue microstructure with temporal diffusion spectroscopy

The signals recorded by diffusion-weighted magnetic resonance imaging (DWI) are dependent on the micro-structural properties of biological tissues, so it is possible to obtain quantitative structural information non-invasively from such measurements. Oscillating gradient spin echo (OGSE) methods have the ability to probe the behavior of water diffusion over different time scales and the potential to detect variations in intracellular structure. To assist in the interpretation of OGSE data, analytical expressions have been derived for diffusion-weighted signals with OGSE methods for restricted diffusion in some typical structures, including parallel planes, cylinders and spheres, using the theory of temporal diffusion spectroscopy. These analytical predictions have been confirmed with computer simulations. These expressions suggest how OGSE signals from biological tissues should be analyzed to characterize tissue microstructure, including how to estimate cell nuclear sizes. This approach provides a model to interpret diffusion data obtained from OGSE measurements that can be used for applications such as monitoring tumor response to treatment in vivo.