Bioprocess Research Articles

Classical vs. reactive distillation technologies for biodiesel production: An environmental comparison using LCA methodology

Sustainable fuels and technologies are expected to significantly contribute towards climate change mitigation considering that the transportation sector provides a 23% share out of the total CO2 emissions. Biodiesel is a green fuel produced by transesterification of triglycerides with an alcohol in the presence of a catalyst. The current study entails modelling and simulation of biodiesel production, through an acid transesterification process, using both classic and intensified methods, coupled with an environmental impact analysis performed following the Life Cycle Assessment methodology. The traditional biodiesel production consists in the synthesis and separation sections, while the intensified method is based on reactive distillation. ChemCAD software was used to simulate and evaluate the processes from a technical point of view. Methanol is generated using CO2 and H2, this method being considered as a new approach for CO2 utilization. Water electrolysis is employed for H2 generation, with either biomass or natural gas as power source. A cradle-to-gate environmental analysis is performed within the current research by means of GaBi software, considering the following system boundaries: i) upstream processes: catalyst supply chain, sunflower oil supply chain, natural gas supply chain, limestone extraction and decomposition, ii) main-processes: methanol and biodiesel production, iii) downstream processes: disposal of wastes. ReCiPe method was chosen as the impact assessment method. High purities for the main product and by-product are obtained (i.e., purities higher than 99%). The outcome of the process simulation points to the conclusion that the intensified path gives better performances from technical point of view. The environmental results show that the classic approach performs better when CO2 and H2 are used as raw materials, while reactive distillation displays a higher efficiency when natural gas is used as feedstock.

Exploring commercial upstream processing of AAV

David McCall, Editor, Cell and Gene Therapy Insights speaks to Hugo Rojas, Upstream Process Lead Scientist at uniQureHugo Rojas’s home-country is Mexico, where he did his BSc in Biotechnology Engineering at the National Polytechnic Institute, with a thesis on characterization of cyanobacteria growing in bioreactor. After finalizing his studies, he worked for a year at the local biopharmaceutical Probiomed as technician in analytical development. Then he pursued a MSc in Life Sciences and Technology and PhD in the group of Cell Systems Engineering at Delft University of Technology focusing on metabolic engineering of yeast. After his studies, he started his career as Fermentation Scientists at INVISTA UK, working on development of gas fermentation and valorization of waste streams. Then moved on to a role in Janssen (Johnson & Johnson) as USP Development Scientists in the department of Bacterial Vaccines Development. Currently, he works at uniQure as USP Lead Scientist, relentlessly pursuing a next-generation AAV production process with insect cells, which has taken his scientific interests towards investigating scale-down models in high-throughput platforms, cell line development, process modeling and rational process intensification leveraging information obtained through PAT. His hobbies are videogaming, animals, playing guitar and acting.

Flexible & scalable solutions for AAV viral vector production using a templated platform

Adeno-associated virus (AAV) has become an increasingly popular viral vector for gene therapy. Currently, there are two approved AAV-based gene therapies, and the number of clinical trials is steadily increasing. As with most viral vector-based therapies, production is labor-intensive and expensive due to the use of adherent cell culture production processes. Consequently, for process intensification, the industry has begun to utilize bioreactors. This article explores the development of a suspension-based AAV upstream process to provide a more efficient and cost-effective bioprocessing solution for large-scale production. The use of template tools for upstream process development will be examined, as will development of the clarification and tangential flow filtration unit operations immediately following harvest.

MircoRNA-9-3p: a novel predictor of neurological outcome after cardiac arrest

Abstract Funding Acknowledgements Type of funding sources: None. Background Resuscitated out-of-hospital cardiac arrest (OHCA) patients who remain comatose after hospital arrival are at high risk of mortality due to anoxic brain injury. Markers of neurological outcome and consequently, neuroprotective targets are of great interest, and novel approaches are warranted. MicroRNA are small non-coding RNA molecules, ultimately involved in gene-silencing. They show promise as biomarkers, as they are stable in body fluids. The microRNA 9-3p (miR-9-3p) is associated to neurological injury in trauma and subarachnoid hemorrhage. Hypothesis: MiR-9-3p changes following OHCA and is associated with neurological outcome. Methods This post hoc analysis included 171 comatose patients included at a single center in the target temperature management (TTM) trial. Patients were randomized to TTM at either 33◦C or 36◦C for 24 h. MicroRNA-9-3p (miR-9-3p) was measured in plasma sampled at admission and at 28, 48 and 72 h. Results miR-9-3p levels changed markedly following OHCA with a peak at 48h. There were no significant differences in median miR-9-3p levels between TTM 33◦C vs. 36◦C at any of the four time points. Elevated miR-9-3p levels were strongly associated with a poor neurological outcome (see figure, p<0.0001). There were no significant differences in age, gender, comorbidities, and pre-hospital data, including lactate level at admission, between miR-9-3p level quartiles. Creatinine and C-reactive protein were not correlated with miR-9-3p levels at 48 h. Conclusion MiR-9-3p is strongly associated with the neurological outcome following OHCA, and the levels are highest 48 hours following cardiac arrest. MicroRNAs, including miR-9-3p, may be involved in upstream regulatory processes and its potential as a therapeutic target should be investigated

Perioperative Oxidative Stress Prospectively Predicts CRPS-Related Outcomes in the 6 months Following Total Knee Arthroplasty

This project tested whether oxidative stress (OS) related to extended tourniquet application during total knee arthroplasty (TKA) and subsequent ischemic reperfusion contributed to CRPS outcomes up to 6 month following TKA. Blood samples were obtained in 90 osteoarthritis patents (63.3% female; 95.6% Non-Hispanic White) undergoing TKA prior to tourniquet placement (T1), 45 minutes after tourniquet inflation (T2), and 15 minutes following tourniquet removal (T3). Plasma levels of F2-isoprostanes (IsoPs) and isofurans (IsoFs), the most specific measures of in vivo OS, were quantified. The primary OS measure was Combined OS (IsoPs+ IsoFs/2), which most accurately captures upstream OS processes independent of oxygen tension. CRPS outcomes included a continuous measure of CRPS symptom extent (CRPS Severity Score; CSS) and dichotomous CRPS diagnoses based on 2012 IASP diagnostic criteria. CRPS outcomes were assessed at 6 week and 6 month post-TKA follow-up. Results indicated that greater variability in Combined OS across T1-T3 predicted higher CSS scores at 6 week follow-up (p<.02). A CRPS diagnosis at 6 week follow-up was predicted by greater perioperative OS at T3 (p<.01), greater OS change from T1-T2 (p<.02), higher average OS across T1-T3 (p<.006), higher maximum OS across T1-T3 (p<.006), and greater variability in OS across T1-T3 (p<.02). Extent of CRPS symptoms at 6 month follow-up, which are more clearly interpretable as reflecting clinical CRPS, were predicted by greater increases in OS from T1 to T2 (p<.03), with a similar marginal trend (p<.08) for baseline pre-incision (T1) OS levels. Perioperative OS did not significantly predict CRPS diagnosis at 6 months. Results indicate that elevated perioperative OS status in patients undergoing TKA may increase risk for CRPS particularly in the early postoperative period. These findings implicate OS as a potential novel mechanism of CRPS risk in the surgical setting. R01AG048915 (SB) R01GM112871 (FTB) UL1 TR000445.

An investigation of how normalisation and local modelling techniques confound machine learning performance in a mental health study

Machine learning (ML) is increasingly deployed on biomedical studies for biomarker development (feature selection) and diagnostic/prognostic technologies (classification). While different ML techniques produce different feature sets and classification performances, less understood is how upstream data processing methods (e.g., normalisation) impact downstream analyses. Using a clinical mental health dataset, we investigated the impact of different normalisation techniques on classification model performance. Gene Fuzzy Scoring (GFS), an in-house developed normalisation technique, is compared against widely used normalisation methods such as global quantile normalisation, class-specific quantile normalisation and surrogate variable analysis. We report that choice of normalisation technique has strong influence on feature selection. with GFS outperforming other techniques. Although GFS parameters are tuneable, good classification model performance (ROC-AUC > 0.90) is observed regardless of the GFS parameter settings. We also contrasted our results against local modelling, which is meant to improve the resolution and meaningfulness of classification models built on heterogeneous data. Local models, when derived from non-biologically meaningful subpopulations, perform worse than global models. A deep dive however, revealed that the factors driving cluster formation has little to do with the phenotype-of-interest. This finding is critical, as local models are often seen as a superior means of clinical data modelling. We advise against such naivete. Additionally, we have developed a combinatorial reasoning approach using both global and local paradigms: This helped reveal potential data quality issues or underlying factors causing data heterogeneity that are often overlooked. It also assists to explain the model as well as provides directions for further improvement.

Monitoring multiple quality attributes of a complex Fc-fusion protein during cell culture production processes by mD-LC-MS peptide mapping

Fc-fusion proteins represent a successful class of biopharmaceutical products. They are considered highly heterogeneous products due to the common degradation of amino acids that occurs during their production in upstream and downstream processes (e.g., oxidation and deamidation) and, above all, their complex glycosylation profile. Multi-dimensional liquid chromatography-mass spectrometry (mD-LC-MS) has recently gained much interest for process analytical technology, enabling the integration of this analytical technology in production and purification environments. In this study, an online mD-LC-MS/MS peptide mapping method was developed for monitoring multiple quality attributes, including the N-glycosylation state of a complex Fc-fusion protein, which is made by combining two heavily glycosylated cytokines with an Fc domain. This fully automated workflow includes sample purification, reduction, digestion, peptide mapping, and subsequent mass spectrometric analysis. Two immobilized enzyme cartridges based on trypsin and Lys-C protease were employed to generate a detailed glycosylation mapping, as trypsin allowed the identification of only one of four glycosylation sites, while Lys-C was more informative for two other sites. Site-specific glycosylation information such as antennarity, sialyation, and core fucosylation state was also determined. In addition to glycans, other post-translational modifications could be monitored simultaneously during the cell culture production processes by the mD-LC-MS/MS approach. In summary, the generated data demonstrate the applicability of mD-LC-MS for the monitoring and trending of multiple attributes for complex antibody formats over production processes in an automated and fast manner, compared to the complex and time-consuming traditional offline assays.

Neuronal differentiation potential of primary and immortalized adipose stem cells by photobiomodulation.

Adipose Stem Cells (ASCs) are capable of neuronal differentiation, which makes them an ideal choice for therapies in nerve injuries. Principally, the differentiation of autologous ASCs to neurons offers solutions for the replacement therapies of nervous system with patient's own genetic background. On the contrary, the use of genetically modified (immortalized) ASCs has the benefit of accessibility by surpassing ethical concerns and ease for propagation as a continuous cell culture. Photobiomodulation (PBM) is a therapeutic modality with laser or light, which is widely been used for modulating stem cell bioprocesses viz. proliferation and differentiation. A comparative analysis was performed to evaluate the neuronal differentiation potential of primary ASCs isolated from a healthy human subject with commercially obtained immortalized ASCs with PBM. The outcome of this analysis will help us to know either primary or immortalized ASCs are most suitable for biomedical applications. Both primary and immortalized ASCs were characterized using their surface protein markers CD44/90/133/166 and induced to differentiate into neuronal cells using Fibroblast Growth Factor, basic (bFGF) and forskolin following PBM using Near Infra-Red (NIR) lasers. Based on the expression of nestin, an early neuronal marker an exposure to 5, 10 and 15J/cm2 of NIR and growth inducers for 14days the primary ASCs demonstrated a higher neuronal differentiation potential compared to the immortalized ASCs. However, newly differentiated cells from either of these ASCs did not reveal βIII-tubulin, an intermediate neuronal marker even by 21days of differentiation. This study gives an indication that immortalized ASCs have a phenotype and differentiation potential slightly less but comparable to the freshly isolated ASCs. We suggest that PBM along with growth inducers offer a better solution of differentiating ASCs to neurons.

Coupling of an IOT wear sensor and numerical modelling in predicting wear evolution of a slurry pump

Slurry pump is an integral system between upstream and downstream mineral processing circuit to transport product streams. It is critical to monitor the slurry pump liner wear to ensure safe and efficient circuit operation, as well as achieving targeted product quality. This study aims to develop a digital wear sensor to monitor slurry pump liner wear and to predict its wear evolution by coupling to a numerical modelling framework. The digital sensor is designed to track and report live point-wise thickness on a slurry pump liner while in operation. A liner wear evolution model was then developed by integrating the wear sensor reading and wear intensity results obtained through numerical modelling. The wear intensity was obtained by coupling Smoothed Particle Hydrodynamics and Discrete Element Modelling. Liner wear evolution prediction results were subsequently compared with site measurements after operating for 95 days. Results suggested that the liner wear evolution prediction showed good agreements with measured results in terms of high wear zone as well as quantitative wear rate prediction. Outcome of this study can be utilised in mineral processing industry for safer operation as well as automated plant monitoring.

Transfer of continuous manufacturing process principles for mAb production in a GMP environment: A step in the transition from batch to continuous.

Implementation of continuous in lieu of batch upstream processing (USP) and downstream process (DSP) for the production of recombinant therapeutic protein is a significant paradigm change. The present report describes how the first kilograms of monoclonal antibody were produced with equipment originally designed for batch operations while using continuous manufacturing processes and principles. Project timelines for the delivery of clinical material have driven this ambition and helped the transition. Nevertheless, because of equipment availability, a tradeoff between the envisaged continuous downstream process (cDSP) operations and the ones described in this article had to be taken. A total of 2.1 kg of monoclonal antibody were produced in two GMP runs for clinical trials. For USP, a 200-L single-use pilot scale bioreactor was upgraded to enable perfusion operation. DSP steps were designed to be easily transferable to cDSP for later clinical or commercial productions. An in-line conditioning buffer preparation strategy was tested in a discontinuous way to prove its efficiency and the purification cascade was structured in parallel to the continuous collection of antibody-containing cell culture supernatant. This strategy will avoid any process change when later moving to the continuous equipment that is currently under qualification. Alignment between small-scale references runs and the GMP runs in terms of productivity and quality confirmed that the presented approach was valid. Thus, we demonstrate that existing fed-batch infrastructure can be adapted to continuous manufacturing without significant additional investments. Such approach is useful to evaluate next-generation manufacturing processes before making large investments.

Current advances and future prospects in production of recombinant insulin and other proteins to treat diabetes mellitus.

Diabetes mellitus is the most prevalent deadly disease caused by the destruction and dysfunction of pancreatic β cells that consequentially increased blood glucose levels. The management of this disease via external administration of insulin/insulin analogs has been difficult and challenging due to their limited production and accessibility at affordable prices. The conventional insulin production platforms (Escherichia coli, Saccharomyces cerevisiae and mammalian cell lines) with limited scalability and high upstream process costs have not been successful in meeting the rapidly increasing insulin demands. However, plants have been used as safe, scalable, environmentally friendly and cost-effective high capacity production platforms for recombinant orally delivered insulin. Recent technological advances in genome engineering and editing technologies for adequate insulin and insulin analogs production, renewable cellular sources of insulin through transplantation of islets or insulin-producing cells and reprogramming or differentiation of non β cells into β-like cells, used either alone or in combination, for diabetes containment are reviewed here along with their future prospects.

Coupling anammox and feammox via polymeric ferric sulfate: An efficient and aeration-saving way for nitrogen removal

To address the issue that Fe3+ precipitate would inhibit microbial metabolic activity, and to further promote the total nitrogen removal efficiency (TNRE), polymeric ferric sulfate (PFS) was added to coupling anammox and feammox. The results showed that PFS could hydrolyze part of the extracellular polymeric substances (EPS), making the spatial structure of microbial aggregations loose and porous, which probably alleviated the potential Fe(OH)3's inhibition. Meanwhile, the hydrolyzed EPS, such as aromatic amino acid, e.g., tryptophan, associated with protein-like substances, could be used as electron donors for denitrification to remove NO3−-N produced by anammox. Thus, TNRE achieved up to 95.60% when the NO2−-N/NH4+-N ratio was 0.9 in the influent flow. Coupling feammox, 9.53% of oxygen demand could be saved in the upstream partial nitrification process because of the reduction of NO2−-N/NH4+-N in the influent flow. The total nitrogen removed by anammox was 72.44%, feammox was 16.34% and denitrification was 6.82%, with 4.40% remaining in the effluent. The addition of PFS selected two possible feammox bacteria, norank_f__Bacillaceae and norank_f__Acidimicrobiaceae.

Improved Titer in Late-Stage Mammalian Cell Culture Manufacturing by Re-Cloning.

Improving productivity to reduce the cost of biologics manufacturing and ensure that therapeutics can reach more patients remains a major challenge faced by the biopharmaceutical industry. Chinese hamster ovary (CHO) cell lines are commonly prepared for biomanufacturing by single cell cloning post-transfection and recovery, followed by lead clone screening, generation of a research cell bank (RCB), cell culture process development, and manufacturing of a master cell bank (MCB) to be used in early phase clinical manufacturing. In this study, it was found that an additional round of cloning and clone selection from an established monoclonal RCB or MCB (i.e., re-cloning) significantly improved titer for multiple late phase monoclonal antibody upstream processes. Quality attributes remained comparable between the processes using the parental clones and the re-clones. For two CHO cells expressing different antibodies, the re-clone performance was successfully scaled up at 500-L or at 2000-L bioreactor scales, demonstrating for the first time that the re-clone is suitable for late phase and commercial manufacturing processes for improvement of titer while maintaining comparable product quality to the early phase process.

Resilience in food processing supply chain networks: empirical evidence from the Indian dairy operations

PurposeThis paper identifies sources of disruptions that impede resilience in the dairy supply chain in an emerging economy context.Design/methodology/approachA case study approach is used. The unit of analysis is the Indian dairy supply chain (IDSC). Data were collected from nine major dairy cooperatives and five major private firms operating across the Indian states. A total of 28 face-to-face semi-structured interviews were conducted with two individuals from each case dairy organisation during January 2016 to December 2017.FindingsDisruption sources in the IDSC are both external and internal and impact the quality of products and the distribution network. Compared to developed economies, in an emerging economy context such as India, the number of disruptions is very high. These disruptions negatively impact resilience and affect efficiency, flexibility, responsiveness and product quality.Research limitations/implicationsThe findings stress the importance of integration across upstream and downstream processes in the IDSC. However, contextual factors should also be considered when designing the supply chain configuration. Small supply sources may be conceptualised as distributed sources that can be consolidated on the move using logistics and IT-enabled solutions. Moreover, the underlying processes of the dairy supply chain need to adapt to the external environment, and internal causes of disruptions should be eliminated through process redesign.Practical implicationsThe findings highlight that the efficient operation of the IDSC is challenged by disruptions, the fragmentation of various stages and poor support infrastructure. The findings may be useful in managing supply networks which have linkages in emerging economies.Social implicationsThe upstream stage of the IDSC involves many small- and medium-sized unorganised producers. The overall inefficiency and poor value generation across the entire IDSC constrain the livelihood and interests of these unorganised producers. Therefore, supply chain design needs to be aligned with social context.Originality/valueThe central contribution of this article is to present sources of disruptions that impact dairy supply chain performance in an emerging economy context. Areas requiring process improvement are also highlighted.

Peranan Penilaian Daur Hidup (Life Cycle Assessment) Dalam Menunjang Perolehan Program Penilaian Peringkat Kinerja Perusahaan (Proper) Pada Industri Mineral Timah

The Ministry of Environment and Forestry added a new criteria, Life Cycle Assessment (LCA) on PROPER assessment 2021. This assessment aims to identify, calculate the sustainable usage of natural resources, discharge of pollution to environment as well as evaluate and implement possible environmental improvements. In the tin mining industry that has negative impact on the environment due to their activities, has to conducted life cycle assessment to support the acquisition of green PROPER. Asociation exporter tin Indonesia proposes scope of LCA from cradle to gate, this scope divided into an upstream process &amp; tin smelterwhich consists of several processing units, namely preparing, smelting, refining, water treatment etc. Functional units are set as input and output references and have been normalized per 1 tonne of tin with impact categories as follows: Global warming, Ozone depletion, acidification potential, eutrophication, photochemical oxidant, abiotic depletion, human toxicity, land use, water footprint and carcinogenic

Carbon dioxide Removal via Absorption using Artificial Seawater in a Microchannel for the Case of CO2-Rich Gas

The separation of CO2 is important for upstream processing of natural gas, which generally contains high concentration of CO2. In this work, a T-microchannel was applied for the absorption of CO2 using artificial seawater as absorbent. The first part involved the optimization of operating conditions for CO2 absorption using water. The experiments were performed under the pressure of 1.7 bar and 60%V/V of CO2 was used as feed mixture. At the optimal condition (the flowrate of liquid of 1 mL/min, the flowrate of gas of 125 mL/min and the temperature of 30 °C), the CO2 removal was 71.14%. The optimized condition was adapted for the application of artificial seawater as absorbent. Each salt including NaCl, CaCl2, and MgCl2 was used at different concentration levels based on the natural concentration in seawater. MgCl2 solution (0.106 mol/L) provided an improvement compared to the case of pure water as absorbent. The removal efficiency and the overall liquid-side mass transfer coefficient (KLa) were 83.88% and 73.12 s−1, respectively. Therefore, seawater can be effectively utilized as absorbent for the removal of CO2.

Development and validation of MicrobEx: an open-source package for microbiology culture concept extraction.

ObjectiveMicrobiology culture reports contain critical information for important clinical and public health applications. However, microbiology reports often have complex, semistructured, free-text data that present a barrier for secondary use. Here we present the development and validation of an open-source package designed to ingest free-text microbiology reports, determine whether the culture is positive, and return a list of Systemized Nomenclature of Medicine (SNOMED)-CT mapped bacteria.Materials and MethodsOur concept extraction Python package, MicrobEx, is built upon a rule-based natural language processing algorithm and was developed using microbiology reports from 2 different electronic health record systems in a large healthcare organization, and then externally validated on the reports of 2 other institutions with manually reviewed results as a benchmark.ResultsMicrobEx achieved F1 scores >0.95 on all classification tasks across 2 independent validation sets with minimal customization. Additionally, MicrobEx matched or surpassed our MetaMap-based benchmark algorithm performance across positive culture classification and species capture classification tasks.DiscussionOur results suggest that MicrobEx can be used to reliably estimate binary bacterial culture status, extract bacterial species, and map these to SNOMED organism observations when applied to semistructured, free-text microbiology reports from different institutions with relatively low customization.ConclusionMicrobEx offers an open-source software solution (available on both GitHub and PyPI) for bacterial culture status estimation and bacterial species extraction from free-text microbiology reports. The package was designed to be reused and adapted to individual institutions as an upstream process for other clinical applications such as: machine learning, clinical decision support, and disease surveillance systems.

Addressing Rice Waste in University Cafeterias Using Material Flow Analysis and System Dynamics Modeling

Food waste has emerged as one of the focus areas in sustainability research. At the Ateneo de Manila University, previous studies have found that food waste is composed mainly of rice. This study, therefore, analyzed cafeteria rice systems in the university through a material flow analysis (MFA) to identify key factors for formulating effective rice waste reduction techniques and then applied the results toward developing system dynamics (SD) models as tools for decision-making. The MFA found that the total mass of produced known rice waste was 49.48 kg/d. The largest sources of rice wastes were the upstream processes of the cafeteria rice system involving the cooking and serving of rice. The SD model developed for one cafeteria found that the service stage was the largest source of rice waste. The main factor influencing service waste generation was the surplus of cooked rice. A scenario was simulated in which the amount of rice used in additional batches cooked was minimized, yielding a substantial decrease in the mass of service waste and lost revenue. Not only does this research provide baseline information that enables the university to enhance sustainable consumption and food waste minimization efforts, but it also contributes to the data pool for rice wastage in the Philippine and Southeast Asian contexts. Furthermore, results indicate a need to re-strategize rice waste campaigns that focus on consumption when much can be done in the preparation and service stages. Collaborating with cafeteria management to improve efficiency in the kitchen is key in addressing the overall rice waste problem. Downstream, consumer-focused interventions targeting changes in attitudes and behaviors must be complemented by upstream changes in operations and management approaches to support both a structural and cultural transformation for sustainability.

Pilot scale extraction of protein from cold and hot-pressed rapeseed cake: Preliminary studies on the effect of upstream mechanical processing

It is important from a techno-economic perspective to understand the challenges associated with developing scalable processes to extract functional proteins from rapeseed cake for applications as functional food ingredients. One of these challenges is to develop a better understanding of the link between upstream mechanical processing of the rapeseed cake and the yield of extracted protein. An initial trial with cold pressed rapeseed cake (CPR) indicated that wet milling had no impact on protein yield. Measurement of protein yields with the Bradford assay indicated that 14% would be recovered. The total protein recovered (5.4% by Kjeldahl analysis) contained a glucosinolate and phytate content that was similar to the rapeseed cake at the start of the process. The fate of the protein extraction was followed during a pilot scale trial with hot-pressed rapeseed cake (HPR), using only stirring followed by sieving, revealing an increase in protein yields, as determined by the Bradford assay, from 8.0% at the start to 22.6% at the end of processing. In addition, only 16% of HPR was solubilized. A similar pilot scale trial with HPR using wet milling and stirring followed by decanting also showed an increase in protein concentration from 15.3% at the start to 23.7% at the end of processing. In addition, 38% of HPR was solubilized. This study provides an insight into what the effect of upstream mechanical processing (wet milling) has in releasing protein from rapeseed cake in order to improve process efficiency. This could have important consequences for upscaling and commercial extraction of rapeseed cake protein.

Impact of the Design Industry on Carbon Emissions in the Manufacturing Industry in China: A Case Study of Zhejiang Province

Reducing carbon emissions during the manufacturing process is a top priority for realizing the strategic “carbon neutral” target. Currently, there is a great deal of research about carbon production in the middle and later stages of production. However, studies on upstream processes are relatively scarce. Studies concerning the design stages are particularly uncommon, although this phase has a profound effect on carbon emissions during manufacturing. Therefore, it is vital to study this and related fields in depth. In this paper, we take Zhejiang Province, China, as the research object, and study the relationship between the design industry and carbon emissions in the manufacturing industry. Through analysis, we developed a first-level evaluation index for the influence of design on carbon emissions in the production stage. Then, we subdivided the first-level indexes into several second-level indexes using the entropy method. Subsequently, we calculated their weights and comprehensively evaluated the influence of these design factors on carbon emissions in the manufacturing industry using the ridge regression model test. Results from our research reveal that at the design end of the production chain, the expansion of resource scale of each design phase has a significant inhibitory effect on the carbon emissions of the manufacturing stage. Conversely, improvements to the industrial economic benefit index have a significant positive effect on the carbon emissions in the manufacturing industry, while government support and the innovation composite index have little influence. The main conclusions of this study are as follows: To reduce carbon emissions in the manufacturing industry, the scale of the inhibitory effect of the design process should be fully evaluated, while the scale construction and related resource input of the design phase should be emphasized. Furthermore, guidance regarding the social responsibility of design enterprises should be strengthened to further promote the concept of “green design” and reverse the purely market-oriented focus of the industry. Also, to promote a greener design industry, the provision of high-quality green design talents should be fortified. In the future, an appropriate green design evaluation index system should be devised to ensure the stable economic development of the design industry and challenge the current situation where a focus on economic indexes results in increased carbon emissions.