Towards a continuous manufacturing strategy for complex oral health formulations

The conversion of traditional batch operations into continuous processes represents an important goal towards process intensification. The rigorous design of continuous manufacturing operations poses several challenges, especially for processes involving complex fluids, whose rheological properties change during processing. The scope of this thesis is to provide a new approach for the development of a continuous process aimed at the production of a non-aqueous Carbopol gel used in oral health formulations. The dissertation addresses two main challenges related to the process: (i) in-line mixing of complex liquids and (ii) control over the Carbopol gelation. First, the impact of complex rheological properties on the mixing stage was investigated experimentally and numerically. Concentrations maps, obtained at different mixers lengths via Planar Laser Induced Fluorescence experiments, revealed that mixing of viscoelastic fluids reduces when the elastic rheological response becomes significant. To prevent these effects and better control the evolution of the rheological properties over the entire process, the kinetics of the gelation process was investigated via time-resolved rheometry and UV-Vis spectroscopy. This study yielded insights into the mechanism of gelation, leading to a kinetic relation to describe the time-evolution of the linear elastic properties of the Carbopol matrix. To further link the kinetic findings with the evolution of the flow properties, the rheological properties of Carbopol dispersions and the impact of different solvents on the swollen configuration of the microgels were investigated. In the presence of co-solvents, the kinetic aspect of the swelling process is critical in determining the final swollen state. Once the final particle dimension has been determined, a generalized scaling behaviour of the flow properties can be retrieved as function of the particle volume fraction. Finally, the scaling laws and the kinetic model were implemented in a computational fluid dynamic model to enable simulations of the gelating flow in different operating conditions

Effect of polydispersity and bubble clustering on the steady shear viscosity of semidilute bubble suspensions in Newtonian media

In this work, we examine the steady shear rheology of semidilute polydisperse bubble suspensions to elucidate the role of polydispersity on the viscosity of these systems. We prove theoretically that the effect of polydispersity on suspension viscosity becomes apparent only if the bubble size distribution is bimodal, with very small and very large bubbles having similar volume fractions. In any other case, we can consider the polydisperse suspension as monodisperse, with the average bubble diameter equal to the De Brouckere mean diameter (d43). To confirm the theoretical results, we carried out steady shear rheological tests. Our measurements revealed an unexpected double power-law decay of the suspension relative viscosity at average capillary numbers between 0.01 and 1. To investigate this behavior further, we visualized the produced bubble suspensions under shear. The visualization experiments revealed that bubbles started forming clusters and threads at an average capillary number around 0.01, where we observed the first decay of viscosity. Clustering and alignment have been associated with shear-thinning behavior in particle suspensions. We believe that the same holds for bubble suspensions, where bubble clusters and threads align with the imposed shear flow, reducing the streamline distortions and, in turn, resulting in a decrease in the suspension viscosity. Consequently, we can attribute the first decay of the relative viscosity to the formation of bubble clusters and threads, proving that the novel shear-thinning behavior we observed is due to a combination of bubble clustering and deformation

The Epigenetic Evolution of Glioma Is Determined by the IDH1 Mutation Status and Treatment Regimen

Tumor adaptation or selection is thought to underlie therapy resistance in glioma. To investigate longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 132 matched initial and recurrent tumors from patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) glioma. IDHwt gliomas showed a stable epigenome over time with relatively low levels of global methylation. The epigenome of IDHmut gliomas showed initial high levels of genome-wide DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. Integration of epigenomics, gene expression, and functional genomics identified HOXD13 as a master regulator of IDHmut astrocytoma evolution. Furthermore, relapse of IDHmut tumors was accompanied by histologic progression that was associated with survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment varied between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neoangiogenesis and T-cell infiltration upon treatment of IDHmut gliomas. This study provides one of the largest cohorts of paired longitudinal glioma samples with epigenomic, transcriptomic, and genomic profiling and suggests that treatment of IDHmut glioma is associated with epigenomic evolution toward an IDHwt-like phenotype.</p

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Effect of D-Mannitol on the Microstructure and Rheology of Non-Aqueous Carbopol Microgels

D-mannitol is a common polyol that is used as additive in pharmaceutical and personal care product formulations. We investigated its effect on the microstructure and rheology of novel non-aqueous Carbopol dispersions employing traditional and time-resolved rheological analysis. We considered two types of sample, (i) fresh (i.e., mannitol completely dissolved in solution) and aged (i.e., visible in crystalline form). The analysis of the intracycle rheological transitions that were observed for different samples revealed that, when completely dissolved in solution, mannitol does not alter the rheological behaviour of the Carbopol dispersions. This highlights that the chemical similarity of the additive with the molecules of the surrounding solvent allows preserving the swollen dimension and interparticle interactions of the Carbopol molecules. Conversely, when crystals are present, a hierarchical structure forms, consisting of a small dispersed phase (Carbopol) agglomerated around a big dispersed phase (crystals). In keeping with this microstructural picture, as the concentration of Carbopol reduces, the local dynamics of the crystals gradually start to control the integrity of the microstructure. Rheologically, this results in a higher elasticity of the suspensions at infinitesimal deformations, but a fragile yielding process at intermediate strains

Hydrodynamics of compartmented fluidized beds under uneven fluidization conditions

Fluidized beds may be conveniently applied to demanding thermal and thermochemical processes thanks to their inherently good thermal performances: bed-to-surface heat transfer coefficients, effective thermal diffusivities. Collection and thermal storage of solar radiation in Concentrated Solar Power (CSP) systems is one challenging example of this application. Thermal properties may be further enhanced by non-conventional design and operation of fluidized beds based on uneven or unsteady (pulsed) fluidization. A novel concept of solar receiver for CHP (combined heat and power) generation consisting of a compartmented dense gas fluidized bed has been proposed to effectively accomplish collection of incident solar radiation, heat transfer to the working fluid of the thermodynamic cycle and thermal energy storage. This application, like others of the same kind, poses the objective of achieving controlled compartmentation of a large scale fluidized bed by selectively promoting fluidization in some regions while keeping others in a fixed state. This task may be accomplished by means of a compartmented windbox, without physical partitioning or internals immersed in the bed. This study addresses this problem by investigating the hydrodynamics of a near-2D dense gas-fluidized bed operated at ambient conditions and equipped with a compartmented fluidizing gas distributor. The hydrodynamics was characterized by pressure measurement at different locations in the bed to mark the onset of local fluidization and to map the extension and location of fluidized and de-fluidized regions in the bed for different choices of operating conditions. An important follow-up of the study is the analysis of the dynamics of the bubble and emulsion phase in an unevenly fluidized bed. Dynamical patterns of bubble and emulsion phases have been scrutinized by analysis of space- and time-resolved void fraction profiles obtained by electrical capacitance measurements.Altogether results indicate that a perfectly compartmented fluidized bed cannot be obtained simply using a compartmented windbox. However a proper choice of fluidizing gas partitioning between the compartments enables good control of the local fluidization conditions, of gas cross-flow between the compartments, of large-scale solids circulation

Hydrodynamics of compartmented fluidized beds under uneven fluidization conditions

Fluidized beds may be conveniently applied to demanding thermal and thermochemical processes thanks to their inherently good thermal performances: bed-to-surface heat transfer coefficients, effective thermal diffusivities. Collection and thermal storage of solar radiation in Concentrated Solar Power (CSP) systems is one challenging example of this application. Thermal properties may be further enhanced by non-conventional design and operation of fluidized beds based on uneven or unsteady (pulsed) fluidization. A novel concept of solar receiver for CHP (combined heat and power) generation consisting of a compartmented dense gas fluidized bed has been proposed to effectively accomplish collection of incident solar radiation, heat transfer to the working fluid of the thermodynamic cycle and thermal energy storage. This application, like others of the same kind, poses the objective of achieving controlled compartmentation of a large scale fluidized bed by selectively promoting fluidization in some regions while keeping others in a fixed state. This task may be accomplished by means of a compartmented windbox, without physical partitioning or internals immersed in the bed. This study addresses this problem by investigating the hydrodynamics of a near-2D dense gas-fluidized bed operated at ambient conditions and equipped with a compartmented fluidizing gas distributor. The hydrodynamics was characterized by pressure measurement at different locations in the bed to mark the onset of local fluidization and to map the extension and location of fluidized and de-fluidized regions in the bed for different choices of operating conditions. An important follow-up of the study is the analysis of the dynamics of the bubble and emulsion phase in an unevenly fluidized bed. Dynamical patterns of bubble and emulsion phases have been scrutinized by analysis of space- and time-resolved void fraction profiles obtained by electrical capacitance measurements.Altogether results indicate that a perfectly compartmented fluidized bed cannot be obtained simply using a compartmented windbox. However a proper choice of fluidizing gas partitioning between the compartments enables good control of the local fluidization conditions, of gas cross-flow between the compartments, of large-scale solids circulation

Simultaneous identification of clinically relevant single nucleotide variants, copy number alterations and gene fusions in solid tumors by targeted next-generation sequencing

In this study, we have set-up a routine pipeline to evaluate the clinical application of Oncomine™ Focus Assay, a panel that allows the simultaneous detection of single nucleotide hotspot mutations in 35 genes, copy number alterations (CNAs) in 19 genes and gene fusions involving 23 genes in cancer samples. For this study we retrospectively selected 106 patients that were submitted to surgical resection for lung, gastric, colon or rectal cancer. We found that 56 patients out of 106 showed at least one alteration (53%), with 47 patients carrying at least one relevant nucleotide variant, 10 patients carrying at least one CNA and 3 patients carrying one gene fusion. On the basis of the mutational profiles obtained, we have identified 22 patients (20.7%) that were potentially eligible for targeted therapy. The most frequently mutated genes across all tumor types included KRAS (30 patients), PIK3CA (16 patients), BRAF (6 patients), EGFR (5 patients), NRAS (4 patients) and ERBB2 (3 patients) whereas CCND1, ERBB2, EGFR and MYC were the genes most frequently subjected to copy number gain. Finally, gene fusions were identified only in lung cancer patients and involved MET [MET(13)-MET(15) fusion] and FGFR3 [FGFR3(chr 17)-TACC3(chr 11)]. In conclusion, we demonstrate that the analysis with a multi-biomarker panel of cancer patients after surgery, may present several potential advantages in clinical daily practice, including the simultaneous detection of different potentially druggable alterations, reasonable costs, short time of testing and automated interpretation of results

Identification of different mutational profiles in cancers arising in specific colon segments by next generation sequencing

The objective of this study was to investigate the mutational profiles of cancers arising in different colon segments. To this aim, we have analyzed 37 colon cancer samples by use of the Ion AmpliSeq™ Comprehensive Cancer Panel. Overall, we have found 307 mutated genes, most of which already implicated in the development of colon cancer. Among these, 15 genes were mutated in tumors originating in all six colon segments and were defined "common genes" (i.e. APC, PIK3CA, TP53) whereas 13 genes were preferentially mutated in tumors originating only in specific colon segments and were defined "site-associated genes" (i.e. BLNK, PTPRD). In addition, the presence of mutations in 10 of the 307 identified mutated genes (NBN, SMUG1, ERBB2, PTPRT, EPHB1, ALK, PTPRD, AURKB, KDR and GPR124) were found to be of clinical relevance. Among clinically relevant genes, NBN and SMUG1 were identified as independent prognostic factors that predicted poor survival in colon cancer patients. In conclusion, the findings reported here indicate that tumors arising in different colon segments present differences in the type and/or frequency of genetic variants, with two of them being independent prognostic factors that predict poor survival in colon cancer patients