Modeling the selective growth advantage of genetically variant human pluripotent stem cells to identify opportunities for manufacturing process control.

BACKGROUND AIMS: The appearance of genetically variant populations in human pluripotent stem cell (hPSC) cultures represents a concern for research and clinical applications. Genetic variations may alter hPSC differentiation potential or cause phenotype variation in differentiated cells. Further, variants may have properties such as proliferative rate, or response to the culture environment, that differ from wild-type cells. As such, understanding the behavior of these variants in culture, and any potential operational impact on manufacturing processes, will be necessary to control quality of putative hPSC-based products that include a proportion of variant threshold in their quality specification. METHODS: Here we show a computational model that mathematically describes the growth dynamics between commonly occurring genetically variant hPSCs and their counterpart wild-type cells in culture. RESULTS: We show that our model is capable of representing the growth behaviors of both wild-type and variant hPSCs in individual and co-culture systems. CONCLUSIONS: This representation allows us to identify three critical process parameters that drive critical quality attributes when genetically variant cells are present within the system: total culture density, proportion of variant cells within the culture system and variant cell overgrowth. Lastly, we used our model to predict how the variability of these parameters affects the prevalence of both populations in culture.

Physics-informed neural networks for biopharmaceutical cultivation processes: Consideration of varying process parameter settings.

We present a new modeling approach for the study and prediction of important process outcomes of biotechnological cultivation processes under the influence of process parameter variations. Our model is based on physics-informed neural networks (PINNs) in combination with kinetic growth equations. Using Taylor series, multivariate external process parameter variations for important variables such as temperature, seeding cell density and feeding rates can be integrated into the corresponding kinetic rates and the governing growth equations. In addition to previous approaches, PINNs also allow continuous and differentiable functions as predictions for the process outcomes. Accordingly, our results show that PINNs in combination with Taylor-series expansions for kinetic growth equations provide a very high prediction accuracy for important process variables such as cell densities and concentrations as well as a detailed study of individual and combined parameter influences. Furthermore, the proposed approach can also be used to evaluate the outcomes of new parameter variations and combinations, which enables a saving of experiments in combination with a model-driven optimization study of the design space.

Ensuring safety standards in sewage sludge-derived biochar: Impact of pyrolysis process temperature and carrier gas on micropollutant removal.

The application of sewage sludge to agricultural land is facing increasing restrictions due to concerns about various micropollutants, including polycyclic aromatic hydrocarbons (PAHs), dioxins and furans (PCDD/Fs), polychlorinated biphenyls (PCBs), per- and poly-fluoroalkyl substances (PFAS), and heavy metals (HMs). As an alternative approach to manage this residue, the use of pyrolysis, a process that transforms sludge into biochar, a carbon-rich solid material, is being explored. Despite the potential benefits of pyrolysis, there is limited data on its effectiveness in removing micropollutants and the potential presence of harmful elements in the resulting biochar. This study aims to evaluate the impact of the temperature and the use of a carrier gas (N2) during a two-stage pyrolysis and cooling on micropollutant removal. Pilot-scale tests showed that a higher temperature (650 °C) and the use of a carrier gas (0.4 L/min N2) during the pyrolysis and the cooling process led to a reduction of PAHs, PCDD/Fs, PCBs and PFAS below their detection limits. As such, the generated biochar aligns with the guidelines set by the International Biochar Initiative (IBI) and the European Biochar Certificate (EBC) for all micropollutants, except for zinc and copper. Additional investigation is required to determine whether the micropollutants undergo destruction or transition into other pyrolysis end-products, such as the gas or liquid phase.

[Extraction process optimization and link evaluation of Reyanning Mixture based on quality by design idea].

Reyanning Mixture is one of the superior Chinese patent medicine varieties of "Qin medicine". Based on the idea of quality by design(QbD), the extraction process of the Reyanning Mixture was optimized. The caffeic acid, polydatin, resveratrol, and emodin were used as critical quality attributes(CQAs). The material-liquid ratio, extraction temperature, and extraction time were taken as critical process parameters(CPPs) by the Plackett-Burman test. The mathematical model was established by the star design-effect surface method, and the design space was constructed and verified. The optimal extraction process of the Reyanning Mixture was obtained as follows: material-liquid ratio of 11.84 g·mL~(-1), extraction temperature at 81 ℃, and two extractions. A partial least-square(PLS) quantitative model for CQAs was established by using near-infrared spectroscopy(NIRS) combined with high-performance liquid chromatography(HPLC) under the optimal extraction process. The results showed that the correlation coefficients of the correction set(R_c) and validation set(R_p) of the quantitative models of four CQAs were more than 0.9. The root mean square error of the correction set(RMSEC) were 0.744, 6.71, 3.95, and 1.53 µg·mL~(-1), respectively, and the root mean square error of the validation set(RMSEP) were 0.709, 5.88, 2.92, and 1.59 µg·mL~(-1), respectively. Therefore, the optimized extraction process of the Reyanning Mixture is reasonable, feasible, stable, and reliable. The NIRS quantitative model has a good prediction, which can be used for the rapid content determination of CQAs during extraction. They can provide an experimental basis for the process research and quality control of Reyanning Mixture.

[Optimization of processing technology of bark of Ilicis Rotundae Cortex based on quality by design concept].

Based on the concept of quality by design(QbD), this study optimized the processing technology of Ilicis Rotundae Cortex. According to the processing method and ingredient requirements of Ilicis Rotundae Cortex in the Chinese Pharmacopoeia, the content of syringin and pedunculoside, alcohol extract, fragmentation rate, and moisture content were taken as the critical quality attributes(CQAs). The soaking time, moistening time, and drying time were taken as critical process parameters(CPPs) by single factor tests. The weight coefficients of CQAs were determined by the analytic hierarchy process(AHP)-entropy weighting method, and the comprehensive score was calculated. With the comprehensive score as the response value, Box-Behnken design was employed to establish a mathematical model between CPPs and CQAs, and the design space for the processing of Ilicis Rotundae Cortex was built and verified. The results of ANOVA showed that the mathematical model had the P value below 0.05, the lack of fit greater than 0.05, adjusted R~2=0.910 5, and predicted R~2=0.831 0, which indicated that the proposed model had statistical significance and good prediction performance. Considering the factors in production, the best processing conditions of Ilicis Rotundae Cortex were decoction pieces of about 1 cm soaking for 1 h, moistening for 4 h, and drying at 60-70 ℃ in a blast drier for 2 h. The optimized processing technology of Ilicis Rotundae Cortex was stable and feasible, which can provide a reference for the standardized preparation and stable quality of Ilicis Rotundae Cortex.

Design space determination to optimize DNA complexation and full capsid formation in transient rAAV manufacturing.

Recombinant adeno-associated virus (rAAV) vectors are a promising platform for in vivo gene therapies. However, cost-effective, well-characterized processes necessary to manufacture rAAV therapeutics are challenging to develop without an understanding of how process parameters (PPs) affect rAAV product quality attributes (PQAs). In this work, a central composite orthogonal experimental design was employed to examine the influence of four PPs for transient transfection complex formation (polyethylenimine:DNA [PEI:DNA] ratio, total DNA/cell, cocktail volume, and incubation time) on three rAAV PQAs related to capsid content (vector genome titer, vector genome:capsid particle ratio, and two-dimensional vector genome titer ratio). A regression model was established for each PQA using partial least squares, and a design space (DS) was defined in which Monte Carlo simulations predicted < 1% probability of failure (POF) to meet predetermined PQA specifications. Of the three PQAs, viral genome titer was most strongly correlated with changes in complexation PPs. The DS and acceptable PP ranges were largest when incubation time and cocktail volume were kept at mid-high setpoints, and PEI:DNA ratio and total DNA/cell were at low-mid setpoints. Verification experiments confirmed model predictive capability, and this work establishes a framework for studying other rAAV PPs and their relationship to PQAs.

Mechanism Study of the Polymerization of Polyamide 56: Reaction Kinetics and Process Parameters.

Polyamide 56 (PA56) has gained significant attention in the academic field due to its remarkable mechanical and thermal properties as a highly efficient and versatile biobased material. Its superior moisture absorption property also makes it a unique advantage in the realm of fiber textiles. However, despite extensive investigations on PA56's molecular and aggregate state structure, as well as processing modifications, little attention has been paid to its polymerization mechanism. Herein, the influence of temperature and time on PA56's polycondensation reaction is detailed studied by end-group titration and carbon nuclear magnetic resonance (NMR) techniques. The reaction kinetics equations for the pre-polymerization and vacuum melt-polymerization stages of PA56 are established, and possible side reactions during the polycondensation process are analyzed. By optimizing the reaction process based on kinetic characteristics, PA56 resin with superior comprehensive properties (melting temperature of 252.6 °C, degradation temperature of 371.6 °C, and tensile strength of 75 MPa) is obtained. The findings provide theoretical support for the industrial production of high-quality biobased PA56.

What affects the accuracy and applicability of determining wastewater sludge water content via low-field nuclear magnetic resonance?

The accurate determination of waster sludge water content is crucial to sludge dewatering treatment and its disposal management. Though previous studies highlight the great advantages of low-field nuclear magnetic resonance (LF-NMR) in the determination of sludge water content, its accuracy and applicability are not well studied. Herein, this study investigated the settling of operating parameters and the properties of sludge samples on the accuracy and applicability of LF-NMR method in measuring sludge water content. The results showed that the setting of basic parameters such as standard curve, number of scanning times (NS) and sample weight affected the accuracy of sludge water content by LF-NMR. The standard calibration curve constructed by 3 g/L CuSO4, NS = 8 and the sample weight of about 5 g, were suitable for the accurate determination of sludge water content. Furthermore, the existence of magnetic substances in sludge can affect the distribution gradient of main magnetic field, and thus restricted the applicability of LF-NMR. The saturation magnetization of chemical reagents strongly correlated with the measured relative errors of sludge water content (r = 0.995, p < 0.01), the greater the saturation magnetization of the magnetic material, the greater the error of the test results. On the whole, it is necessary to fully consider the influence of process parameters and sludge properties to evaluate the accuracy and applicability of the LF-NMR method, rather than simply copying the parameters in literatures.

Exploring microfluidics and membrane extrusion for the formulation of temozolomide-loaded liposomes: investigating the effect of formulation and process variables.

Liposomes have gained much attention in drug delivery since the entry of liposomal Doxorubicin (Doxil®) into the market. Liposomes can entrap lipophilic, hydrophilic as well as amphiphilic drug molecules due to their distinctive structural features. Yet the clinical translation of liposomes is limited due to the reproducibility issues owing to a lack of information related to the impact of process parameters and formulation variables on designed liposomes. Recently, preparation techniques like membrane extrusion and microfluidics have been reported to produce liposomes in a reproducible manner. The present research study selected an amphiphilic drug Temozolomide (TMZ). It has a short half-life in the plasma due to its pH-dependent stability. Various critical and non-critical parameters affecting the critical quality attributes were identified and studied using risk-based assessment. The effect of various material attributes and process parameters on the critical quality attributes of the temozolomide-loaded liposomes prepared by microfluidics and membrane extrusion techniques were investigated in detail. Liposomes in the size range of 100-150 nm were targeted. Both techniques were optimized with a minimum number of critical process parameters. The obtained information will be beneficial to formulation scientists for designing liposomes for an amphiphilic drug on a large scale.

Effect of moisture content, aeration rate, and C/N on maturity and gaseous emissions during kitchen waste rapid composting.

To determine factors affecting compost maturity and gaseous emissions during the rapid composting of kitchen waste, an orthogonal test was conducted with three factors: moisture content (MC) (55%, 60%, 65%), aeration rate (AR) (0.3,0.6 and 0.9 L·kg-1DM·min-1) and C/N ratio (21, 24, 27). The results showed that the importance of factors affecting compost maturity was: C/N > AR > MC, optimal conditions were: C/N of 24, AR of 0.3 L·kg-1DM·min-1and MC of 65%. For gaseous emissions, the sequence of essential factors affecting NH3 emissions was: C/N > MC > AR, and the optimal parameters for NH3 reduction were: C/N of 27, MC of 65%, and AR of L·kg-1DM·min-1. The important factors affecting N2O and H2S emissions are both: MC > C/N > AR, while their best parameters were different. The optimal parameters for N2O emission reduction were MC of 60%, AR of 0.3 L·kg-1DM·min-1 and C/N of 24, while these for H2S were MC of 55%, AR of 0.3 L·kg-1DM·min-1 and C/N of 21. The C/N mainly affected the compost maturity and AR further affected the maturity and pollutant gas emissions by influencing the temperature and O2 content. Considering comprehensively the maturity and gaseous reduction, the optimal control parameters were: MC of 60%-65%, AR of L·kg-1DM·min-1, and C/N of 24-27.

A review of struvite crystallization for nutrient source recovery from wastewater.

Nutrient recovery from wastewater not only reduces the nutrient load on water resources but also alleviates the environmental problems in aquatic ecosystems, which is a solution to achieve a sustainable society. Besides, struvite crystallization technology is considered a potential nutrient recovery technology because the precipitate obtained can be reused as a slow-release fertilizer. This review presents the basic properties of struvite and the theory of the basic crystallization process. In addition, the possible influencing variables of the struvite crystallization process on the recovery efficiency and product purity are also examined in detail. Then, the advanced auxiliary technologies for facilitating the struvite crystallization process are systematically discussed. Moreover, the economic and environmental benefits of the struvite crystallization process for nutrient recovery are introduced. Finally, the shortcomings and inadequacies of struvite crystallization technology are presented, and future research prospects are provided. This work serves as the foundation for the future use of struvite crystallization technology to recover nutrients in response to the increasingly serious environmental problems and resource depletion.

Investigating the Effect of Operational Variables on the Yield, Characterization, and Properties of End-of-Life Olive Stone Biomass Pyrolysis Products.

In recent years, biomass has emerged as a promising raw material to produce various products, including hydrocarbons, platform chemicals, and fuels. However, a more comprehensive evaluation of the potential production of desirable value-added products and chemical intermediates is required. For these reasons, this study aimed to investigate the impact of various operating parameters on the pyrolysis of end-of-life olive stone, an agriculture and food industry waste, using a tubular quartz reactor operated at 773 K. The results revealed that the product compositions were comparable under batch or semi-batch nitrogen feeding conditions and with reaction times of 1 or 3 h. The product distribution and composition were significantly influenced by changes in the heating rate from 5 to 50 K min-1, while the effect of changing the biomass particle size from 0.3 to 5 mm was negligible in the semi-batch test. This work provides a comprehensive understanding of the relationship between pyrolysis operational parameters and obtained product distribution and composition. Moreover, the results confirmed the possible exploitation of end-of-life olive stone waste to produce high-added value compounds in the zero-waste strategy and biorefinery concept.

Optimization of Physical Refining Process of Camellia Oil for Reduction of 3-Monochloropropane-1,2-Diol (3-MCPD) Ester Formation Using Response Surface Methodology on a Laboratory Scale.

Refined and deodorized camellia oil has been reported to contain a high amount of 3-monochloropropane-1,2-diol esters (3-MCPDE) due to the high-temperature deodorization step. To reduce 3-MCPDE in camellia oil, the physical refining process of camellia oil was simulated on a laboratory scale. Response surface methodology (RSM) was designed to modify and optimize the refining process with five processing parameters (water degumming dosage, degumming temperature, activated clay dosage, deodorization temperature and deodorization time). The optimized new refining approach achieved a 76.9% reduction in 3-MCPDE contents, in which the degumming moisture was 2.97%, the degumming temperature was 50.5 °C, the activated clay dosage was 2.69%, the deodorizing temperature was 230 °C, and the deodorizing time was 90 min. A significance test and analysis of variance results demonstrated that the deodorization temperature and deodorization time contributed significantly to the reduction of 3-MCPD ester. The joint interaction effects of activated clay dosage and deodorization temperature were significant for 3-MCPD ester formation.

[Optimization of ethanol precipitation process of Nauclea officinalis extract based on concept of quality by design(QbD)].

The ethanol precipitation process of Nauclea officinalis extract was optimized based on the concept of quality by design(QbD). Single factor tests were carried out to determine the levels of test factors. The ethanol volume fraction, pre-ethanol precipitation drug concentration, and ethanol precipitation time were taken as critical process parameters(CPPs). With the comprehensive scores of strictosamide transfer rate and solid removal rate as the critical quality attributes(CQAs), Box-Behnken design was employed to establish the mathematical models and space design between CPPs and CQAs, and the obtained optimal operating space was validated. The optimal operating space included ethanol volume fraction of 65%-70%, pre-ethanol precipitation drug concentration of 22-27 mg·mL~(-1), and ethanol precipitation time of 12 h. Based on the concept of QbD, this study adopted the design space to optimize the ethanol precipitation process of N. officinalis extract, which provided a reliable theoretical basis for the quality control in the production process of N. officinalis preparations. Moroever, this study provided a reference value for guiding the research and industrial production of traditional Chinese medicines.

Formation and mitigation of PAHs in barbecued meat - a review.

Polycyclic Aromatic Hydrocarbons (PAHs) are chemicals, which can occur in barbecued or grilled foods, and particularly in meats. They originate from incomplete combustion of the heat source, pyrolysis of organic compounds, or fat-induced flame formation. This review therefore summarizes relevant parameters for mitigation of especially carcinogenic PAHs in barbecued meat. Consumption of PAHs increases the risk of cancer, and thus the relevance for the mitigation of PAHs formation is very high for barbecued meat products. Parameters such as heat source, barbecue geometry, and meat type as well as marinating, adding spices, and other antioxidants reduce the final benzo[a]pyrene and PAHs concentrations and minimize the exposure. Overall, mitigation of carcinogenic PAHs from barbecuing includes removal of visual charring, reducing fat pyrolysis by minimizing dripping from the meat onto the heat source, the use of acidic marinades or choosing leaner cuts of meat. Estimation of human exposure to barbecued meat, includes several challenges such as substantial differences in barbecuing frequencies and practices, heat sources and meat types used for grilling.

Valorization of food waste by anaerobic digestion: A bibliometric and systematic review focusing on optimization.

As food waste gets acknowledged as a global potential source of biomass, its valorization through anaerobic digestion becomes an attractive strategy. This work describes the state-of-the-art on the valorization of food waste by anaerobic digestion and the optimization of the process. The methodology used was a bibliometric and systematic review of the optimization of the process from 66 articles selected. Bibliometric mapping allowed us to identify that, until now, most studies have been focused on the: i) anaerobic co-digestion strategy in order to stabilize the process, ii) interest in the generation of biofuels to replace non-renewable fuels, iii) study of metabolic processes for a better understanding of the system iv) reactor design optimization and others facilities to increase process efficiency. The systematic analysis showed that the operational parameters has been extensively studied to optimize the process. Therefore, co-digestion has been the main strategy to improve the process. In this sense, knowledge of the substrate and co-substrate is extremely important to operate the reactors. For methane production, the ideal operating conditions indicated were: pH of 7, solids content between 4.0 and 15%, C/N ratio of 25, hydraulic retention time from 25 to 40 days and alkalinity from 2850 to 2970.5mgCaCO3/L. In addition, the ideal OLR will vary mainly according to operating temperature, number of reactor stages, and raw material characteristics. This review indicates trends and knowledge gaps that are important to guide new research on the anaerobic digestion of food waste, pointing out the potential advantages, optimization strategies, by-products of interest and challenges of the process. The results were used for the development of references of ideal operating conditions for energy production, being able to guide the design and operation of reactors.

Model construction and application for effluent prediction in wastewater treatment plant: Data processing method optimization and process parameters integration.

Wastewater treatment based on the activated sludge process is complex process, which is easily affected by influent quality, aeration time and other factors, leading to unstable effluent. Facing increasingly stringent sewage discharge standards in China, it is necessary to build a prediction model for early warning of effluent quality. In this study, nine machine learning algorithms were adopted to construct models for the prediction of effluent Chemical Oxygen Demand (COD). In order to improve the prediction accuracy of the models, model optimization was conducted by introducing the hysteresis condition [Hydraulic Retention Time (HRT) of 18 h], data processing method (K-FOLD) and process parameters [dissolved oxygen (DO), sludge return ratio (SRR) and mixed liquid suspended solids (MLSS)]. Results showed that both K-Nearest Neighbour (KNN) and Gradient Boosting Decision Tree (GBDT) displayed excellent prediction effects, the best results of MAPE, RMSE and R2 were 7.34%/1.29/0.92(COD, KNN). The optimized models were further applied to the prediction of effluent total phosphorus (TP), total nitrogen (TN) and pH. The MAPE/RMSE/R2 were 7.43%/0.92/0.93(TN, GBDT), 17.81%/0.19/0.99(TP, KNN), 0.53%/0.16/0.99 (pH, KNN) respectively, indicating high prediction accuracy. The change and comparison of modeling conditions provide a new insight to wastewater prediction models. In addition, this study is close to the actual application scenario of WWTPs operation and management, also laying a foundation for the reverse regulation of energy saving and consumption reduction of wastewater treatment plants (WWTPs).

High moisture extrusion cooking of meat analogs: A review of mechanisms of protein texturization.

High-moisture extrusion cooking (HMEC) is an efficient method for converting proteins and polysaccharides into fibrous structure that is used in the industrial production of meat analogs. The purpose of this review is to systematically evaluate current knowledge regarding the modification of protein structure including denaturation and reassembly upon extrusion processing and to correlate this understanding to the structure of the final products. Although there is no consensus on the relative importance of a certain type of bond on extrudates' structure, literature suggests that, regardless of moisture level, these linkages and interactions give rise to distinctive hierarchical order. Both noncovalent and disulfide bonds contribute to the extrudates' fibrous structure. At high water levels, hydrogen and disulfide bonds play a dominant role in extrudates' texture. The process parameters including cooking temperature, screw speed, and moisture content have significant albeit different levels of impact on the texturization process. Their correlation with the ingredients' physiochemical properties provides a greater insight into the process-structure-function relationship of meat analogs. The tendency of protein and polysaccharide blends to phase separate rather than produce a homogeneous mix is a particularly important aspect that leads to the formation of fibrous layers when extruded. This review shows that systematic studies are required to measure and explain synergistic and competitive interactions between proteins and other ingredients such as carbohydrates with a focus on their incompatibility. The wide range of plant protein source can be utilized in the HMEC process to produce texturized products, including meat analogs.

Recent advances and persistent challenges in the design of freeze-drying process for monoclonal antibodies.

Monoclonal antibodies constitute nowadays an important therapeutic class and the number of approved molecules for clinical uses continues to increase, achieving considerable part of the therapeutic market. Yet, the stability in solution of these biopharmaceuticals is often low. That is why freeze-drying has been and remains the method of choice to obtain monoclonal antibodies in the solid state and to improve their stability. The design of freeze-drying process and its optimization are still topical subjects of interest and the pharmaceutical industry is regularly challenged by the requirements of quality, safety and efficiency set by the regulatory authorities. These requirements imply a deep understanding of each step of the freeze-drying process, developing techniques to control the critical parameters and to monitor the quality of the intermediate and the final product. In addition to quality issues, the optimization of the freeze-drying process in order to reduce the cycle length is of great interest since freeze-drying is known to be an energy-expensive and time-consuming process. In this review, we will present the recent literature dealing with the freeze-drying of monoclonal antibodies and focus on the process parameters and strategies used to improve the stability of these molecules and to optimize the FD process.

[Prediction of formability of flavonoid extract granules by dry granulation based on design space and RBFNN].

In this paper, a flavonoid extract powder properties-process parameters-granule forming rate prediction model was constructed based on design space and radial basis function neural network(RBFNN) to predict the formability of flavonoid extract gra-nules. Box-Behnken experimental design was employed to explore the mathematical relationships between critical process parameters and quality attributes. The design space of critical process parameters was developed, and the accuracy of the design space was verified by Monte Carlo method(MC). Design Expert 10 was used for Box-Behnken design and mixture design. Scutellariae Radix mixed powder was prepared and its powder properties were measured. The mixed powder was then subjected to dry granulation and the granule forming rate was determined. The correlations between powder properties were analyzed by variance influence factor(VIF), and principal component analysis(PCA) was performed for the factors with strong collinearity. In this way, a prediction model of powder properties-process parameters-granule forming rate was established based on RBFNN, the accuracy of which was evaluated with examples. The results showed that the model had a good predictive effect on the granule forming rate, with the average relative error of 1.04%. The predicted value and the measured value had a high degree of fitting, which indicated that model presented a good prediction ability. The prediction model established in this study can provide reference for the establishment of quality control methods for Chinese medicinal preparations with similar physical properties.