Using an Online Image Analysis Technique to Characterize Sucrose Crystal Morphology during a Crystallization Run

The effects of dextran in residual impurity on trehalose crystallization and formula in food preservation

The residual dextran impurities in the upstream process significantly impact the crystallization of starch-based functional sugar and the related food properties. This study intends to reveal the mechanism of dextran's influence on trehalose crystallization, and build a relationship among the dextran in syrup and the physicochemical and functional properties of trehalose. Instead of incorporating into the crystal lattice, dextran changes the assembly rate of trehalose molecules on crystal surface. The different sensitivity and adsorption capacity of the crystal surface to the chain length of dextran determines the growth rate of crystal surfaces, resulting in different crystal morphology. The bulk trehalose crystals, which were obtained from syrups with short chain dextran, have excellent powder properties, including best flowability (35◦), highest crystal strength (2.7 N), lowest caking rate (62.22 %), and the most uniform mixing with other sweeteners (sucrose/xylitol) in food formulations, achieving more stable starch preservation.

Structural characterization and calcium absorption-promoting effect of sucrose-calcium chelate in Caco-2 monolayer cells and mice

Sucrose emerges as a chelating agent to form a stable sucrose-metal-ion chelate that can potentially improve metal-ion absorption. This study aimed to analyze the structure of sucrose-calcium chelate and its potential to promote calcium absorption in both Caco-2 monolayer cells and mice. The characterization results showed that calcium ions mainly chelated with hydroxyl groups in sucrose to produce sucrose-calcium chelate, altering the crystal structure of sucrose (forming polymer particles) and improving its thermal stability. Sucrose-calcium chelate dose dependently increased the amount of calcium uptake, retention, and transport in the Caco-2 monolayer cell model. Compared to CaCl2 , there was a significant improvement in the proportion of absorbed calcium utilized for transport but not retention (93.13 ± 1.75% vs. 67.67 ± 7.55%). Further treatment of calcium channel inhibitors demonstrated the active transport of sucrose-calcium chelate through Cav1.3. Cellular thermal shift assay and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assays indicated that the ability of sucrose-calcium chelate to promote calcium transport was attributed to its superior ability to bind with PMCA1b, a calcium transporter located on the basement membrane, and stimulate its gene expression compared to CaCl2 . Pharmacokinetic analysis of mice confirmed the calcium absorption-promoting effect of sucrose-calcium chelate, as evident by the higher serum calcium level (44.12 ± 1.90 mg/L vs. 37.42 ± 1.88 mmol/L) and intestinal PMCA1b gene expression than CaCl2 . These findings offer a new understanding of how sucrose-calcium chelate enhances intestinal calcium absorption and could be used as an ingredient in functional foods to treat calcium deficiency. PRACTICAL APPLICATION: The development of high-quality calcium supplements is crucial for addressing the various adverse symptoms associated with calcium deficiency. This study aimed to prepare a sucrose-calcium chelate and analyze its structure, as well as its potential to enhance calcium absorption in Caco-2 monolayer cells and mice. The results demonstrated that the sucrose-calcium chelate effectively promoted calcium absorption. Notably, its ability to enhance calcium transport was linked to its strong binding with PMCA1b, a calcium transporter located on the basement membrane, and its capacity to stimulate PMCA1b gene expression. These findings contribute to a deeper understanding of how the sucrose-calcium chelate enhances intestinal calcium absorption and suggest its potential use as an ingredient in functional foods for treating calcium deficiency.

Structural Characterization of Zinc-Sucrose Complex and Its Ability to Promote Zinc Absorption in Caco-2 Monolayer Cells and Mice

Sucrose emerges as a metal-ion chelating agent with excellent stability that may increase metal-ion absorption. This study aimed to characterize the structure of zinc-sucrose complex and investigate its ability to promote zinc absorption in Caco-2 monolayer cells and mice. Based on the results of the inductively coupled plasma emission spectrometer (ICP-ES), scanning electron microscopy-energy-dispersive X-ray spectroscopy (SEM-EDX), and Fourier transform infrared spectroscopy (FT-IR), it can be inferred that zinc and sucrose were chelated at a 1:1 ratio, with the hydroxyl groups playing a significant role. The Caco-2 monolayer cell model revealed that zinc-sucrose complex increased the amount of zinc uptake, retention, and transport in a dose- and time-dependent manner. Through the upregulation of genes and proteins for ZIP4, MT1, and DMT1, treatment with zinc-sucrose complex improved the proportion of absorbed zinc utilized for transport compared to ZnCl2 (26.21 ± 4.96 versus 8.50 ± 1.51%). Pharmacokinetic analysis of mice confirmed the zinc absorption-promoting effect of zinc-sucrose complex, as indicated by the considerably higher serum zinc level (4.16 ± 0.53 versus 2.56 ± 0.45 mg/L) and intestinal ZIP4, MT1, and DMT1 gene expression than ZnCl2. Further treatment of different zinc channel inhibitors and CETSA demonstrated the direct interaction of zinc-sucrose complex with ZIP4 protein and ZIP4-mediated cellular transport of zinc-sucrose complex. These findings provide a novel insight into the zinc absorption-promoting mechanism of zinc-sucrose complex, which could be used as an ingredient in functional foods to treat zinc deficiency.

Uncovering the role of impurity sugars on the crystallization of d-tagatose crystal: Experiments and molecular dynamics simulations

Impurity sugars produced in upstream process of functional sugars are significantly impacting the product quality. In this work, the effect of congeners (d-maltose (d-MAL), d-fructose (d-FRU), d-glucose (d-GLU)) on primary and secondary nucleation of d-tagatose (d-TAG) crystals was investigated. The impurity sugars showed an inhibition on primary nucleation of d-TAG crystals, while a promotion on the secondary nucleation of d-TAG. Interestingly, the impact of impurity sugars on d-TAG crystal growth was similar to that on primary nucleation. The diffusion ability, hydrogen bonding forming ability, interaction energy of d-TAG crystal surfaces and impurity sugars were evaluated by molecular dynamics (MD) simulations to reveal the nucleation and growth behavior. Based on the above findings, we designed the d-TAG crystallization experiments, and obtained d-TAG crystals with uniform particle size distribution and regular morphology. This study helps to understand the influence of impurity sugars on crystallization, guiding the industrial manufacturing of functional sugars.

In Situ Measurement Method Based on Edge Detection and Superpixel for Crystallization Imaging at High-Solid Concentrations

To facilitate measuring crystal sizes during batch crystallization at high-solid concentrations by using an invasive imaging system, an in situ imaging measurement strategy based on edge detection and superpixel is proposed for the ambiguous boundary problem of large amounts of crystals. Firstly, an image filtering is employed to cope with image degradation caused by noise disturbance and suspension turbulence in the crystallizer. Subsequently, an image segmentation method is developed by utilizing improved edge detection and superpixel, which can be easily performed for crystal extraction. Accordingly, crystal size measurement can be developed for evaluation of the crystal size distribution. The experiment results on α-form L-glutamic acid present the effectiveness of the proposed method.

Potential of Deep Learning Methods for Deep Level Particle Characterization in Crystallization

Crystalline particle properties, which are defined throughout the crystallization process chain, are strongly tied to the quality of the final product bringing along the need of detailed particle characterization. The most important characteristics are the size, shape and purity, which are influenced by agglomeration. Therefore, a pure size determination is often insufficient and a deep level evaluation regarding agglomerates and primary crystals bound in agglomerates is desirable as basis to increase the quality of crystalline products. We present a promising deep learning approach for particle characterization in crystallization. In an end-to-end fashion, the interactions and processing steps are minimized. Based on instance segmentation, all crystals containing single crystals, agglomerates and primary crystals in agglomerates are detected and classified with pixel-level accuracy. The deep learning approach shows superior performance to previous image analysis methods and reaches a new level of detail. In experimental studies, L-alanine is crystallized from aqueous solution. A detailed description of size and number of all particles including primary crystals is provided and characteristic measures for the level of agglomeration are given. This can lead to a better process understanding and has the potential to serve as cornerstone for kinetic studies.

Impact of process parameters on product size and morphology in hydrometallurgical antisolvent crystallization

The recovery of scandium from waste streams of mining and metallurgical operations presents an opportunity to balance supply and demand of this commodity. This study expands on the research focusing...

Quantitative Microscopy: Particle Size/Shape Characterization, Addressing Common Errors Using 'Analytics Continuum' Approach

Particle size/shape characterization of active pharmaceutical ingredient (API) is integral to successful product development. It is more of a correlative property than a decision-making measure. Though microscopy is the only technique that provides a direct measure of particle properties, it is neglected for reasons like non-repeatability and non-reproducibility which is often attributed to a) fundamental error, b) segregation error, c) human error, d) sample randomness, e) sample representativeness etc. Using the "Sucrose" as model sample, we propose "analytics continuum" approach that integrates optical microscope PSD measurements complimented by NIR spectroscopy-based trending analysis as a prescreening tool to demonstrate sample randomness and representativeness. Furthermore, plethora of statistical tests are utilized to infer population statistics. Subsequently, an attribute-based control chart and bootstrap-based confidence interval was developed to monitor product performance. A flowchart to serve as an elementary guideline is developed, which is then extended to handle more complex situations involving API crystallized from two different solvent systems. The results show that the developed methodology can be utilized as a quantitative procedure to assess the suitability of API/excipients from different batches or from alternate vendors and can significantly help in understanding the differences between material even on a minor scale.

Fed-Batch Sucrose Crystallization Model for the B Massecuite Vacuum Pan, Solution by Deterministic and Heuristic Methods

Fed-batch crystallization is a crucial step for sugar production. In order to relate parameters that are difficult to measure (average diameter of the crystals and total mass formed) to other easier to measure parameters (volume, temperature, and concentration), a model was developed for a B massecuite vacuum pan composed of mass and energy balances together with empirical relations that describe the crystal development inside equipment. The generated system of ordinary differential equations (ODE) had eight parameters which were adjusted through minimization of relative differences between the model results and experimental data. It was solved through the function fmincon, available in MATLABTM, which is a deterministic and gradient-based optimization method. The objective of this paper is to improve the model obtained and, for this purpose, two metaheuristic functions were used: genetic algorithm and particle swarm. To compare the results, the convergence time of each algorithm was used as well as the resulting quadratic deviation. The particle swarm method was the best option among the three used, presenting a shorter execution time and lower quadratic relative deviation.

Crystal Shape Modification via Cycles of Growth and Dissolution in a Tubular Crystallizer

Besides size and polymorphic form, crystal shape takes a central role in engineering advanced solid materials for the pharmaceutical and chemical industries. This work demonstrates how multiple cycles of growth and dissolution can manipulate the habit of an acetylsalicylic acid crystal population. Considerable changes of the crystal habit could be achieved within minutes due to rapid cycling, i.e., up to 25 cycles within <10 min. The required fast heating and cooling rates were facilitated using a tubular reactor design allowing for superior temperature control. The face-specific interactions between solvent and the crystals' surface result in face-specific growth and dissolution rates and hence alterations of the final shape of the crystals in solution. Accurate quantification of the crystal shapes was essential for this work, but is everything except simple. A commercial size and shape analyzer had to be adapted to achieve the required accuracy. Online size, and most important shape, analysis was achieved using an automated microscope equipped with a flow-through cell, in combination with a dedicated image analysis routine for particle tracking and shape analysis. Due to the implementation of this analyzer, capable of obtaining statistics on the crystals' shape while still in solution (no sampling and manipulation required), the dynamic behavior of the size shape distribution could be studied. This enabled a detailed analysis of the solvent's effect on the change in crystal habit.

Determination of the critical mixing intensity for secondary nucleation of paracetamol in an oscillatory flow crystallizer

The critical mixing intensity for secondary nucleation of paracetamol was determined in an oscillatory flow crystallizer for the first time.