An Analysis of the Tsr-LsrB Interaction During Autoinducer-2 Chemotaxis In Escherichia coli

Escherichia coli senses a variety of chemoeffectors. The Tsr chemoreceptor is known to mediate attractant response to serine. Previously, serine was the only attractant described for Tsr. Recent work suggests Tsr senses Autoinducer-2 as an attractant via a periplasmic binding protein. Autoinducer-2 is a general quorum sensing molecule recognized by Gram positive and Gram negative bacteria. In E. coli it is bound to LsrB during AI-2 uptake. A testable model, based on the described interaction between MBP and the Tar chemoreceptor in E. coli, was generated. I first hypothesized that the shoulder regions of Tsr would associate with areas of both the amino and carboxyl domains of LsrB to elicit chemotaxis to AI-2. To test this, alanine-scanning mutations were generated in both Tsr and LsrB. Results suggest AI-2 is sensed through a direct interaction between Tsr and LsrB. I conclude residues Lys-147 and Glu-150 of Tsr and Asp-59, Asp-63 and Arg-252 of LsrB are critical for AI-2 chemotaxis. I investigated the relationship between LsrB expression and AI-2 chemotaxis. I hypothesized altering expression of LsrB relative to chromosomal level would affect AI-2 chemotaxis. This was tested by growing cells to late phase, increasing LsrB present, and by inducing plasmid-borne LsrB. The results suggest increasing the LsrB present decreases AI-2 chemotaxis, though a clear conclusion cannot be drawn. I also explored the effect making lsr deletions would have on LsrB expression and AI-2 chemotaxis. I conclude there is little effect on AI-2 chemotaxis in these mutants. Lastly, I hypothesized serine and AI-2 affect signaling to each other. This was tested by using Tsr variants deficient for serine chemotaxis to test AI-2 chemotaxis to establish that recognition of serine and AI-2 occurs independently at separate locations on Tsr. I introduced one ligand during log phase growth and tested chemotaxis response to the other ligand. Results indicate that serine and AI-2 bind at separate sites. However, AI-2 chemotaxis decreased when serine was present, though not vice versa. I conclude the response to serine is more robust since there are a limiting number of LsrB proteins present in the cell

From the Ashes: The Beginning of Morsifire

This project concerns the development of the Indie/Hip-Hop musical brand Morsifire through recorded material, live performance, and artistic branding. The project will see through the writing, recording, and mixing of an EP, live set creation using Ableton Live and full band, as well as visual branding. The goal is to fuse the genres of indie rock and hip-hop in with both recordings and live performance, as well as establish a strong digital footprint to propel Morsifire to the next stage of his career.https://remix.berklee.edu/graduate-studies-production-technology/1162/thumbnail.jp

Review and classification of variability analysis techniques with clinical applications

Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis

An Analysis of the Tsr-LsrB Interaction During Autoinducer-2 Chemotaxis In Escherichia coli

Escherichia coli senses a variety of chemoeffectors. The Tsr chemoreceptor is known to mediate attractant response to serine. Previously, serine was the only attractant described for Tsr. Recent work suggests Tsr senses Autoinducer-2 as an attractant via a periplasmic binding protein. Autoinducer-2 is a general quorum sensing molecule recognized by Gram positive and Gram negative bacteria. In E. coli it is bound to LsrB during AI-2 uptake. A testable model, based on the described interaction between MBP and the Tar chemoreceptor in E. coli, was generated. I first hypothesized that the shoulder regions of Tsr would associate with areas of both the amino and carboxyl domains of LsrB to elicit chemotaxis to AI-2. To test this, alanine-scanning mutations were generated in both Tsr and LsrB. Results suggest AI-2 is sensed through a direct interaction between Tsr and LsrB. I conclude residues Lys-147 and Glu-150 of Tsr and Asp-59, Asp-63 and Arg-252 of LsrB are critical for AI-2 chemotaxis. I investigated the relationship between LsrB expression and AI-2 chemotaxis. I hypothesized altering expression of LsrB relative to chromosomal level would affect AI-2 chemotaxis. This was tested by growing cells to late phase, increasing LsrB present, and by inducing plasmid-borne LsrB. The results suggest increasing the LsrB present decreases AI-2 chemotaxis, though a clear conclusion cannot be drawn. I also explored the effect making lsr deletions would have on LsrB expression and AI-2 chemotaxis. I conclude there is little effect on AI-2 chemotaxis in these mutants. Lastly, I hypothesized serine and AI-2 affect signaling to each other. This was tested by using Tsr variants deficient for serine chemotaxis to test AI-2 chemotaxis to establish that recognition of serine and AI-2 occurs independently at separate locations on Tsr. I introduced one ligand during log phase growth and tested chemotaxis response to the other ligand. Results indicate that serine and AI-2 bind at separate sites. However, AI-2 chemotaxis decreased when serine was present, though not vice versa. I conclude the response to serine is more robust since there are a limiting number of LsrB proteins present in the cell

Finite Element Analysis of Large Body Deformation Induced by a Catastrophic Near Impact Event

Finite element simulations of near impacts of terrestrial bodies are presented to investigate possible deformation behavior induced by a massive body during the creation week and/or Genesis Flood. Using the universal law of gravitation, a gravitationally loaded objected is subjected to the ‘pull’ of a near passing fly-by object, and the resulting surface deformations are studied. An Internal State Variable (ISV) pressure dependent plasticity model for silicate rocks (Cho et al., 2018) is used to model the deformation behavior and to capture the history effects involved during the complex surface loading/unloading found in a near impact event. The model is used to simulate the earth and a “fly-by” object interaction and is able to accurately reproduce the internal pressure profiles of the earth and fly-by object. In this context, the fly-by object can be the original Moon, a meteor, or another type of large object that has moved through space to interact with the Earth. Due to the wide range of features that can drive surface deformations during a near impact event, a Design Of Experiments (DOE) methodology was used to independently investigate the influences of five parameters (stationary body size, core material, core/mantle thickness ratio, passing object mass, and passing object distance) concerning surface deformation. The results indicate that the passing body distance, stationary body size, and core/mantle ratio are the most dominant influence parameters on surface deformation. Examination of the ISV parameters of the mantle during deformation shows a complex relationship between the hardening and recovery terms of the model and the resulting plastic strain and surface deformation induced from the near pass event. Surface rise from the near passage of a Moon sized object could be as high as 800 m, in turn causing large tsunamis and possibly causing the Earth’s crust to crack. For this first of its kind study, the conclusions provide understanding of the possible ranges of deformations observed from a near pass event and provides insights into possible catastrophic deformation mechanisms relevant to the young Earth paradigm

Guiding principles and proposed classification system for the responsible adoption of artificial intelligence in scientific writing in medicine

The integration of large language models (LLMs) and artificial intelligence (AI) into scientific writing, especially in medical literature, presents both unprecedented opportunities and inherent challenges. This manuscript evaluates the transformative potential of LLMs for the synthesis of information, linguistic enhancements, and global knowledge dissemination. At the same time, it raises concerns about unintentional plagiarism, the risk of misinformation, data biases, and an over-reliance on AI. To address these, we propose governing principles for AI adoption that ensure integrity, transparency, validity, and accountability. Additionally, guidelines for reporting AI involvement in manuscript development are delineated, and a classification system to specify the level of AI assistance is introduced. This approach uniquely addresses the challenges of AI in scientific writing, emphasizing transparency in authorship, qualification of AI involvement, and ethical considerations. Concerns regarding access equity, potential biases in AI-generated content, authorship dynamics, and accountability are also explored, emphasizing the human author’s continued responsibility. Recommendations are made for fostering collaboration between AI developers, researchers, and journal editors and for emphasizing the importance of AI’s responsible use in academic writing. Regular evaluations of AI’s impact on the quality and biases of medical manuscripts are also advocated. As we navigate the expanding realm of AI in scientific discourse, it is crucial to maintain the human element of creativity, ethics, and oversight, ensuring that the integrity of scientific literature remains uncompromised