Mapping the solid-state properties of crystalline lysozyme during pharmaceutical unit-operations

Bulk crystallisation of protein therapeutic molecules towards their controlled drug delivery is of interest to the biopharmaceutical industry. The complexity of biotherapeutic molecules is likely to lead to complex material properties of crystals in the solid state and to complex transitions. This complexity is explored using batch crystallised lysozyme as a model. The effects of drying and milling on the solid-state transformations of lysozyme crystals were monitored using differential scanning calorimetry (DSC), X-ray powder diffraction (XRPD), FT-Raman, and enzymatic assay. XRPD was used to characterise crystallinity and these data supported those of crystalline lysozyme which gave a distinctive DSC thermogram. The apparent denaturation temperature (Tm) of the amorphous lysozyme was ∼201 °C, while the Tm of the crystalline form was ∼187 °C. Raman spectra supported a more α-helix rich structure of crystalline lysozyme. This structure is consistent with reduced cooperative unit sizes compared to the amorphous lysozyme and is consistent with a reduction in the Tm of the crystalline form. Evidence was obtained that milling also induced denaturation in the solid-state, with the denatured lysozyme showing no thermal transition. The denaturation of the crystalline lysozyme occurred mainly through its amorphous form. Interestingly, the mechanical denaturation of lysozyme did not affect its biological activity on dissolution. Lysozyme crystals on drying did not become amorphous, while milling-time played a crucial role in the crystalline-amorphous-denatured transformations of lysozyme crystals. DSC is shown to be a key tool to monitor quantitatively these transformations

Hemodynamically informed parcellation of cerebral FMRI data

Standard detection of evoked brain activity in functional MRI (fMRI) relies on a fixed and known shape of the impulse response of the neurovascular coupling, namely the hemodynamic response function (HRF). To cope with this issue, the joint detection-estimation (JDE) framework has been proposed. This formalism enables to estimate a HRF per region but for doing so, it assumes a prior brain partition (or parcellation) regarding hemodynamic territories. This partition has to be accurate enough to recover accurate HRF shapes but has also to overcome the detection-estimation issue: the lack of hemodynamics information in the non-active positions. An hemodynamically-based parcellation method is proposed, consisting first of a feature extraction step, followed by a Gaussian Mixture-based parcellation, which considers the injection of the activation levels in the parcellation process, in order to overcome the detection-estimation issue and find the underlying hemodynamics

Fast joint detection-estimation of evoked brain activity in event-related fMRI using a variational approach

In standard clinical within-subject analyses of event-related fMRI data, two steps are usually performed separately: detection of brain activity and estimation of the hemodynamic response. Because these two steps are inherently linked, we adopt the so-called region-based Joint Detection-Estimation (JDE) framework that addresses this joint issue using a multivariate inference for detection and estimation. JDE is built by making use of a regional bilinear generative model of the BOLD response and constraining the parameter estimation by physiological priors using temporal and spatial information in a Markovian modeling. In contrast to previous works that use Markov Chain Monte Carlo (MCMC) techniques to approximate the resulting intractable posterior distribution, we recast the JDE into a missing data framework and derive a Variational Expectation-Maximization (VEM) algorithm for its inference. A variational approximation is used to approximate the Markovian model in the unsupervised spatially adaptive JDE inference, which allows fine automatic tuning of spatial regularisation parameters. It follows a new algorithm that exhibits interesting properties compared to the previously used MCMC-based approach. Experiments on artificial and real data show that VEM-JDE is robust to model mis-specification and provides computational gain while maintaining good performance in terms of activation detection and hemodynamic shape recovery

Physiologically Informed Bayesian Analysis of ASL fMRI Data

Arterial Spin Labelling (ASL) functional Magnetic Resonance Imaging (fMRI) data provides a quantitative measure of blood perfusion, that can be correlated to neuronal activation. In contrast to BOLD measure, it is a direct measure of cerebral blood flow. However, ASL data has a lower SNR and resolution so that the recovery of the perfusion response of interest suffers from the contamination by a stronger hemodynamic component in the ASL signal. In this work we consider a model of both hemodynamic and perfusion components within the ASL signal. A physiological link between these two components is analyzed and used for a more accurate estimation of the perfusion response function in particular in the usual ASL low SNR conditions

Toxicity and toxicokinetics of cadmium in \u3ci\u3eCapitella\u3c/i\u3e sp. I: Relative importance of water and sediment as routes of cadmium uptake

The importance of dissolved versus sediment-bound cadmium as uptake routes for the deposit-feeding polychaete Capitella species I and the toxicity and toxicokinetics of cadmium from these exposure routes were investigated. Effects were reported as changes in worm growth rate, egestion rate and allometry. Radioactive cadmium (109Cd) was used as a tracer to examine the uptake (5 d) and subsequent depuration (6 d) of cadmium. Both effects and kinetics were investigated in systems with and without sediment. Individual Capitella sp. I were exposed to (1) dissolved (i.e. –1). Worms in water-only treatments showed negative growth rates, which decreased linearly from –5 to –10% d–1 with increasing cadmium concentration. Cadmium had no detectable effect on egestion rate or growth in the presence of sediment in either sediment-bound only (ca 36% d–1) or porewater & sediment (ca 30% d–1) treatments. Cadmium exposure had no detectable effect on the allometric exponent (i. e. area-length relation) in any of the treatments; however, worms in water-only treatments were relatively thinner than in the 2 treatments with sediment. Worms in porewater & sediment treatments took up ca 50-fold more cadmium (ca 195 ng Cd worm–1) than worms in water-only treatments (3.9 ng Cd worm–1) during 5 d of exposure. Sediment-bound cadmium was calculated to contribute 95 % of the total amount taken up by feeding worms. Starving worms retained all of the cadmium during the subsequent depuration period (6 d), and exhibited an increased weight-specific body burden (μg Cd g–1 dry wt worm) due to shrinkage. In feeding worms, the decrease in weight-specific body burden was faster (T½ = 3 d) than the decrease in total body burden (μg Cd worm–1; T½ = 11 d), indicating that both active excretion and dilution of cadmium body burden as a result of growth contributed to the change in cadmium tissue concentration during the depuration period. Thus, our results indicate that in Capitella sp. I sediment-bound cadmium is the major route of uptake. We found that cadmium affects starving but not fed worms, despite the fact that fed worms took up considerably more cadmium than starving worms. Our results suggest that stress associated with food limitation increases the susceptibility of worms to cadmium stress