A host cell protein that may impact polysorbate degradataion

There is growing interest and concern related to host cell proteins. Current issues with host cell proteins include questions related to the various available analytical approaches and the sensitivity of those approaches as well as issues with purification strategies and the impact of host cell proteins downstream. The availability of a sequenced genome enables new opportunities to address problematic host cell proteins via cell line engineering. We studied difficult to remove host cell proteins in CHO cells with the goal of identifying host cell proteins that may be product associated with a number of monoclonal antibodies, that may copurify with products on various polishing resins, and that may significantly alter their expression as a function of cell age. We identified more than 120 potentially problematic host cell proteins. We believe that at least one of these problematic host cell proteins may contribute to issues in the degradation of polysorbates which are commonly used in monoclonal antibody formulations. Knockdown and knockout cell lines for this host cell protein do not demonstrate the same level of polysorbate degradation. This work was supported by the National Science Foundation

Deep Representation Learning Of Spectroscopic Graphs

Graph representations of spectroscopic information have been increasing in popularity due to their efficiency and scalability in encoding large volumes of data; simply, energy levels are represented as nodes, and transitions as edges between each level. Thus, all quantum mechanical information pertaining to a molecule can be readily manipulated and transformed using a single data format, allowing computations and visualizations to be performed with ease. One application of spectroscopic graphs is to assist in the analysis of high resolution spectra of complex mixtures, comprising many observed transitions from an unknown number of molecules. Analysis of such mixtures comprises two coupled tasks: assignment of features to their respective signal carriers, and to decompose the full spectrum into known molecules. Viewing this problem from the perspective of spectroscopic graphs, our task is to fully reconstruct the subgraphs (i.e. molecules) from sparse information obtained with techniques such as AMDOR and MST. Here, we apply the use of deep graph learning techniques for spectroscopic graph reconstruction. Using convolutional autoencoder architectures, we experiment with the possibility of parameterizing graph neural networks to reproduce complex graphs when given only a limited number of ``observed'' energy levels and/or transitions. As part of this work, we perform a comprehensive investigation into the successes and challenges of our approach, including the interpretability of learned representations, how they can be manipulated and analyzed, and its applicability in complex mixture analysis

Astrochemical Forecasting With Machine Learning

Since the first molecules were detected in space, we have now reached a point where chemical and physical complexity in the interstellar medium reaches the boundaries of what human expertise and intuition alone can achieve. With every new molecule we discover, the question "What comes next?" grows more and more difficult to answer as more possibilities emerge. Conventionally, we turn to chemical models for guidance; this may be complicated when considering complex, non-LTE processes such as shocks, radiation, and grain-surface chemistry. Moreover, expansion of chemical networks typically requires hand-picked reactions and species, requiring an exhaustive knowledge of chemical and astrophysical literature, and can impose human bias on which reactions and molecules are important. As a complimentary approach to conventional chemical models, we have developed an unsupervised machine learning pipeline for predicting molecular abundances in a non-parametric fashion. Leveraging tools originally developed in high throughput drug discovery and data science, our pipeline captures and uses millions of molecules from various databases to create chemically descriptive vector representations for quantitative comparison. These representations are subsequently used to predict molecular properties in a given environment; as a proof-of-concept, we use the well-characterized chemical inventory of TMC-1, including the latest discoveries from the GOTHAM collaboration. We show that the model can be successfully conditioned on an inventory, able to reproduce column densities of unseen molecules to within an order of magnitude without any tuning parameters. Simultaneously, we are able to use the model to predict column densities of hundreds of thousands of molecules not yet detected in space, as a way to guide efforts, as well as provide a robust statistical baseline for expected abundances

Identifying Unknown Molecules With Probabilistic Deep Learning And Rotational Spectroscopy

A major bottleneck in the analysis of broadband chirped-pulse microwave spectra is the identification of unknown molecules. Often, a set of molecular frequencies are fit to an effective Hamiltonian, whereby a set of spectroscopic parameters are used to infer the molecular carrier. These constants are reproduced with electronic structure calculations through a trial and error process, accompanied by chemical intuition involving the precursors used, and the reaction conditions (e.g. electrical discharges). As the size of the molecules increase, the combinatorics of many hundreds to thousands of possible isomers becomes an intractable problem for chemical intuition alone. Since spectroscopic parameters are only weakly informative, we turn to statistical inference to complement conventional spectroscopic analysis. In this talk, I will discuss a new framework for identifying unknown molecules by performing inference on spectroscopic parameters with probabilistic deep learning. Using a series of decoder architectures, we are able to infer the approximate molecular composition/formula and what functional groups are present using only the rotational constants and derived quantities $\kappa$ (the asymmetry parameter) and $\Delta$ (the inertial defect), and approximate magnitudes and projections of the dipole moments

Session 5: Future of Aviation – Beyond COVID or With COVID?

While the COVID pandemic continues to devastate the aviation industry, the long-term industry outlook remains positive. Yet to be fully prepared, we must consider that the future of aviation could be one with COVID instead of beyond COVID, as COVID become endemic around the world. What would the future of aviation look like in these scenarios? What needs to be done now to be ready for the future

Pregabalin and gabapentin for the management of chronic sciatica: determining utility, effect on functioning capacity, quality of life and clinical outcome

Background: Pain is a major clinical problem, the true prevalence of which is difficult to estimate as it encompasses a variety of disorders. Sciatica is considered a type of neuropathic pain (NP) characterised by severe low back pain radiating down the leg to below the knee. Chronic sciatica (CS) is sciatica lasting longer than three months. There are few clinical guidelines for treating of CS, reflecting a gap in quality evidence for effective therapies. Recently, two medications gabapentin (GBP) and pregabalin (PGB) have been used in the management of CS. Evidence for their usage is limited with no direct, high quality research to determine if one is superior to the other. This research answers that question and helps guide clinicians as to the best treatment option for CS. Methods: The thesis includes a literature review to gauge current management of CS with PGB and GBP. The work uses a mixed-methods approach to gain evidence on efficacy, disability and personality traits which will guide clinician's choice of either GBP or PGB. A mix of methods was chosen, to capture patient's treatment experiences more broadly and not simply being restricted to symptom relief. Anecdotal evidence suggests a variable response to either drug, both in terms of efficacy and adverse events (AEs). However, we are unsure at what point the balance of benefits against AEs tips and patients make the decision to abandon treatment. To gather this information and draw conclusions regarding the optimal treatment for patients with CS, this project collects background information on patient's perceptions related to treatment, and conducts a novel randomised controlled trial to determine head to head which treatment is more efficacious. We set out to establish whether one drug has a superior profile to the other and if there are any other differences in treatment outcomes. Hypothesis: We hypothesise that there are differences between the drugs, where (1) one drug (PGB) has a superior profile in pain and disability reduction, as well as (2) frequency and severity of adverse events. Results: Retrospective data showed AEs to be a limiting factor for treatment outcomes and compliance when GBP was added to a first line agent. The clinical trial reported here showed that, while PGB and GBP were both significantly efficacious in reducing pain intensity in patients with CS, GBP was superior when compared 'head-to-head'. Moreover, GBP was associated with fewer and less severe AEs. Neither drug was superior when compared 'head-to-head' for reducing disability in our study group. Our exploratory study on personality traits showed that patients with a predominantly external self-control had worse outcomes. Specifically, an external self-control resulted in lower pain severity reductions especially with PGB. Moreover, PGB alone demonstrated a high, and statistically significant, positive correlation with external self-control resulting in higher pain values for patients displaying this personality trait. There were no notable differences between drugs when personality and disability severity were compared. Conclusion: This research makes a significant original contribution to the literature by addressing a key gap regarding the utilisation of pain medication for CS, namely with PGB and GBP. We found that GBP was superior to PGB for reducing pain severity and for being associated with fewer and less severe AEs. Moreover, our results show having a personality trait of external locus of self-control, negatively effects treatment outcomes with PGB. Our findings provide a body of evidence which can formally guide treatment decisions for patients with CS considering pain severity, disability severity, AEs and personality

Opportunities for collective advancement in the biopharmaceutical manufacturing community

Technology innovation, workforce development, and regulatory advancement have been a hallmark of the industry for the past several decades. As the industry continues to expand, mature and evolve, there are new opportunities for shared risk in technology innovation, for partnerships to facilitate training, and for new approaches to engage with health authorities. It can be argued that collaborative efforts in this space, done appropriately, can 1) reduce the burden and investment that would otherwise be required by individual organizations to advance their technology needs and address issues with speed, quality, and cost; 2) refocus academic faculty on the training of students who are better prepared for industry careers; and 3) help faculty better understand the current technology needs of existing industry. Collaborate public-private partnerships offer one way to bring stakeholders together as well as pay for relevant activities. This presentation is intended to catalyze a discussion regarding the opportunities and challenges associated with collaborative technology development and will include a discussion about the ways that stakeholders may collaborate to create opportunities for the biopharmaceutical industry, government, and academic partners

The \u3cem\u3eRoots\u3c/em\u3e of Middle-Earth: William Morris\u27s Influence upon J. R. R. Tolkien

This study examines the influence of William Morris (1834-1896) upon J. R. R. Tolkien (1892-1973). It concentrates specifically upon the impact of Morris’s romance, The Roots of the Mountains, upon Tolkien’s The Lord of the Rings. After surveying the scholarly literature pertaining to this topic, it proceeds to discuss their work within the context of the nineteenth-century revival of interest in the medieval period and in folkloric and mythological narratives. It then analyzes numerous parallels between the two works in characterization; plot motifs; archaic diction, syntax, and semantics; and topographical description and reanimation are then analyzed. These parallels demonstrate that Morris’s work had a profound influence upon The Lord of the Rings. Significant differences that do occur between the two texts are evaluated within the context of the Romantic tradition and the divergent ways the two authors interpret the paradigm of the Fall. The study concludes that, while Tolkien’s work surpasses Morris’s in many respects, its achievements would not have been possible without the example of The Roots of the Mountains to build upon. It closes with possibilities for future directions of research pertaining to this topic

The benefit of outdoor environments for international migrants facing migratory stressors

There is an undeniable trend in international migration around the world, and this has only steadily increased in recent years. Those that choose to move away from their home countries face great opportunities, as well as challenges and it is these challenges that can pose a threat to some. The complex mix of emotions and mental challenges experienced by these international migrants can cause a particular type of stress unique to those that must adapt to a new culture and language. How do different people experience this problem? What are the ways people choose to face these challenges? In this qualitative study, five subjects who have moved from their home country are interviewed about their experiences moving to a new country. The challenges they face are explored, as well as how they chose to meet those challenges. Four major themes are presented and analyzed in the results, then discussed in the context of relevant literature in the final section. Although some migrant challenges and coping mechanisms are supported by current literature, the use of the outdoor environment was especially important for the majority of the subjects. Furthermore, past experiences in childhood in natural environments may have contributed to continued extensive use in their adult lives, affecting even their preferred choice of residence. This paper exposes the sparse research in this important field of international migration and the potential use of the outdoor environment to help this growing body of people