Patterned crystal growth and heat wave generation in hydrogels

The crystallization of metastable liquid phase change materials releases stored energy as latent heat upon nucleation and may therefore provide a triggerable means of activating downstream processes that respond to changes in temperature. In this work, we describe a strategy for controlling the fast, exothermic crystallization of sodium acetate from a metastable aqueous solution into trihydrate crystals within a polyacrylamide hydrogel whose polymerization state has been patterned using photomasks. A comprehensive experimental study of crystal shapes, crystal growth front velocities and evolving thermal profiles showed that rapid growth of long needle-like crystals through unpolymerized solutions produced peak temperatures of up to 45˚C, while slower-crystallizing polymerized solutions produced polycrystalline composites and peaked at 30˚C due to lower rates of heat release relative to dissipation in these regions. This temperature difference in the propagating heat waves, which we describe using a proposed analytical model, enables the use of this strategy to selectively activate thermoresponsive processes in predefined areas.

Measurement of high protein concentrations by optical rotation: a case study for monitoring of monoclonal antibody drug downstream processes

Background: Recent advancements in cell engineering and bioreactor engineering have enabled high monoclonal antibody (mAb) concentrations in harvested solutions for the downstream process (DSP). Methods: As many unit operations such as capture chromatography, polish chromatography, membrane filtration, virus inactivation, virus filtration, and concentration by ultrafiltration are involved in DSP, it is crucial to monitor the process carefully in order to perform reliable and stable DSP operations. One of the most important signals (process parameter) to be monitored is the protein concentration CP. Although various methods are available, most of them are not suited for measuring high CP. In this paper, we have developed a method for measuring very high CP by optical rotation (OR). Result: Linear correlations were confirmed between OR and CP in the range CP = 0 to 80 g/L for mAbs with high repeatability and small variation coefficients. This method was applied to the monitoring of CP in the opaque (colored) solution during the cell culture. The CP by OR was in good agreement with those by the standard Protein A HPLC method. Conclusion: Monitoring of high CP by OR is expected to be an efficient process analytical tool (PAT) for DSP.

Morphological Tagging and Lemmatization in the Albanian Language

An important element of Natural Language Processing is parts of speech tagging. With fine-grained word-class annotations, the word forms in a text can be enhanced and can also be used in downstream processes, such as dependency parsing. The improved search options that tagged data offers also greatly benefit linguists and lexicographers. Natural language processing research is becoming increasingly popular and important as unsupervised learning methods are developed. There are some aspects of the Albanian language that make the creation of a part-of-speech tag set challenging. This research provides a discussion of those issues linguistic phenomena and presents a proposal for a part-of-speech tag set that can adequately represent them. The corpus contains more than 250,000 tokens, each annotated with a medium-sized tag set. The Albanian language’s syntagmatic aspects are adequately represented. Additionally, in this paper are morphologically and part-of-speech tagged corpora for the Albanian language, as well as lemmatize and neural morphological tagger trained on these corpora. Based on the held-out evaluation set, the model achieves 93.65% accuracy on part-of-speech tagging, The morphological tagging rate was 85.31 % and the lemmatization rate was 88.95%. Furthermore, the TF-IDF technique weighs terms and with the scores are highlighted words that have additional information for the Albanian corpus.

Cultured Meat Prospects for a Billion!

The dietary protein requirements of almost 9.8 billion people need to be fulfilled in a healthy and sustainable manner by 2050. Meat consumption contributes to 35% of the total protein requirement of the Indian population. Meat intake needs to be sustainable and economical without causing food security and production issues. Consumption of meat in India is projected to rise with an increase in consumer incomes. Hence, novel alternative proteins, including cultured meat (CM) and plant-based meat (PBM), are being developed to satisfy the demand for meat-derived proteins in the diet. This involves the creation of novel PBM/CM products with a similar taste and texture as conventional animal meat with tailor-made nutritional attributes. In this article, we provide critical insights into the technical and business aspects of relevance to production and sustainability encountered by the Indian CM industry at a series of stages that can be termed the CM value chain comprising upstream and downstream processes. We shed light on the need for regulatory authorities and a framework. Consumer concerns towards CM products can be alleviated through effective scientific communication strategies, including prior familiarity, narrative building and transparency, and labelling aspects of CM products.

A Review of the Milestones Reached by the Attainable Region Optimisation Technique in Particle Size Reduction

The attainable region (AR) is an optimization method adopted for use in comminution to achieve different objective functions, which all converge to optimising the production of the desired particle size distributions for downstream processes. The technique has so far mostly been used to optimise the breakage of particles in tumbling mills. It achieved the desired purpose by unveiling all possible outcomes derived from a combination of operational parameters that are bound by trajectories showing the limitations of a system. The technique has given the scientific community lenses to see the behaviour of different parameters in ball mills otherwise known as the black boxes due to their concealing nature. Since its inception, the AR technique has been applied to data obtained from the laboratory tests and simulated industrial mills and the results sometimes contradict or confirm the conventional milling practices in the industry. This makes the already conservative mining industry sceptical about its adoption. This review thus assesses the milestone covered as far as the AR development in comminution is concerned. It also helps to clarify the sources of the discrepancies between the AR results and the conventional knowledge concerning the optimisation of ball mill operational parameters.

Assessing detergent-mediated virus inactivation, protein stability and impurity clearance in biologics downstream processes

Detergent-mediated virus inactivation (VI) provides a valuable orthogonal strategy for viral clearance particularly for next generation continuous manufacturing. Furthermore, there exists an industry-wide need to replace the conventionally employed detergent, Triton X-100, with eco-friendly alternatives. This study provides a systematic approach to screen detergents as VI agents through the study of VI of three different enveloped viruses for monoclonal antibodies and fusion proteins. We investigated three major aspects of VI namely, the impact of VI agent on the therapeutic quality attributes, clearance of the VI agent and other impurities through subsequent chromatographic steps and lastly the efficacy of VI for the said detergent. Several quality attributes such as charge variance, oxidation, deamidation, glycosylation and aggregation were investigated. Aggregation was a key indicator of stability. Experimental and modeling data was used to decipher the mechanism and kinetics of aggregation for pH sensitive molecules by exploring worst case VI conditions. We found product aggregation and its kinetics to be driven by extrinsic factors such as detergent and protein concentration. Aggregation was also impacted by initial aggregation level as well as intrinsic factors such as the protein sequence and detergent hydrophobicity and critical micelle concentration (CMC). VI efficiency was dependent on the virus tested, duration of incubation as well as detergent CMC and concentration. Dodecyl maltopyranoside (DDM) was found to be a promising candidate for potential application in VI. Knowledge gained here on factors driving product stability and VI provides valuable insight to design, standardize and optimize conditions (concentration, duration of inactivation) for screening of detergent-mediated VI.

Manufacturing Bacteriophages (Part 1 of 2): Cell Line Development, Upstream, and Downstream Considerations

Within this first part of the two-part series on phage manufacturing, we will give an overview of the process leading to bacteriophages as a drug substance, before covering the formulation into a drug product in the second part. The principal goal is to provide the reader with a comprehensive framework of the challenges and opportunities that present themselves when developing manufacturing processes for bacteriophage-based products. We will examine cell line development for manufacture, upstream and downstream processes, while also covering the additional opportunities that engineered bacteriophages present.

TFTenricher: a python toolbox for annotation enrichment analysis of transcription factor target genes

Background Transcription factors (TFs) are the upstream regulators that orchestrate gene expression, and therefore a centrepiece in bioinformatics studies. While a core strategy to understand the biological context of genes and proteins includes annotation enrichment analysis, such as Gene Ontology term enrichment, these methods are not well suited for analysing groups of TFs. This is particularly true since such methods do not aim to include downstream processes, and given a set of TFs, the expected top ontologies would revolve around transcription processes. Results We present the TFTenricher, a Python toolbox that focuses specifically at identifying gene ontology terms, cellular pathways, and diseases that are over-represented among genes downstream of user-defined sets of human TFs. We evaluated the inference of downstream gene targets with respect to false positive annotations, and found an inference based on co-expression to best predict downstream processes. Based on these downstream genes, the TFTenricher uses some of the most common databases for gene functionalities, including GO, KEGG and Reactome, to calculate functional enrichments. By applying the TFTenricher to differential expression of TFs in 21 diseases, we found significant terms associated with disease mechanism, while the gene set enrichment analysis on the same dataset predominantly identified processes related to transcription. Conclusions and availability The TFTenricher package enables users to search for biological context in any set of TFs and their downstream genes. The TFTenricher is available as a Python 3 toolbox at https://github.com/rasma774/Tftenricher, under a GNU GPL license and with minimal dependencies.