Galois theory in monoidal categories

The Galois theory of Chase and Sweedler [11], for commutative rings, is generalized to encompass commutative monoids in an arbitrary symmetric, closed, monoidal category with finite limits and colimits. The primary tool is the Morita theory of Pareigis [35, 36, 37], which also supplies a suitable definition for the concept of a “finite” object in a monoidal category. The Galois theory is then extended by an examination of “normal” sub-Hopf-monoids, and examples in various algebraic and topological categories are considered. In particular, symmetric, closed, monoidal structures on various categories of topological vector spaces are studied with respect to the existence of “finite” objects

Examining Trust and Reliance in Collaborations between Humans and Automated Agents

Human trust and reliance in artificial agents is critical to effective collaboration in mixed human computer teams. Understanding the conditions under which humans trust and rely upon automated agent recommendations is important as trust is one of the mechanisms that allow people to interact effectively with a variety of teammates. We conducted exploratory research to investigate how personality characteristics and uncertainty conditions affect human-machine interactions. Participants were asked to determine if two images depicted the same or different people, while simultaneously considering the recommendation of an automated agent. Results of this effort demonstrated a correlation between judgements of agent expertise and user trust. In addition, we found that in conditions of high and low uncertainty, the decision outcomes of participants moved significantly in the direction of the agent’s recommendation. Differences in reported trust in the agent were observed in individuals with low and high levels of extraversion

Multi-Level Kinetic Model of mRNA Delivery via Transfection of Lipoplexes

Recent work on the use of mRNA lipoplexes for gene delivery demonstrates the need for a mathematical model that simulates and predicts kinetics and transfection efficiency. The small copy numbers involved make it necessary to use stochastic models and include statistical analysis of the variation observed in the experimental data. The modeling requirements are further complicated by the multi-level nature of the problem, where mRNA molecules are contained in lipoplexes, which are in turn contained in endosomes, where each of these entities displays a behavior of its own. We have created a mathematical model that reproduces both the time courses and the statistical variance observed in recent experiments using single-cell tracking of GFP expression after transfection. By applying a few key simplifications and assumptions, we have limited the number of free parameters to five, which we optimize to match five experimental determinants by means of a simulated annealing algorithm. The models demonstrate the need for modeling of nested species in order to reproduce the shape of the dose-response and expression-level curves

Multi-Level Kinetic Model of mRNA Delivery via Transfection of Lipoplexes

Recent work on the use of mRNA lipoplexes for gene delivery demonstrates the need for a mathematical model that simulates and predicts kinetics and transfection efficiency. The small copy numbers involved make it necessary to use stochastic models and include statistical analysis of the variation observed in the experimental data. The modeling requirements are further complicated by the multi-level nature of the problem, where mRNA molecules are contained in lipoplexes, which are in turn contained in endosomes, where each of these entities displays a behavior of its own. We have created a mathematical model that reproduces both the time courses and the statistical variance observed in recent experiments using single-cell tracking of GFP expression after transfection. By applying a few key simplifications and assumptions, we have limited the number of free parameters to five, which we optimize to match five experimental determinants by means of a simulated annealing algorithm. The models demonstrate the need for modeling of nested species in order to reproduce the shape of the dose-response and expression-level curves

Stellar and Molecular Radii of a Mira Star: First Observations with the Keck Interferometer Grism

Using a new grism at the Keck Interferometer, we obtained spectrally dispersed (R ~ 230) interferometric measurements of the Mira star R Vir. These data show that the measured radius of the emission varies substantially from 2.0-2.4 microns. Simple models can reproduce these wavelength-dependent variations using extended molecular layers, which absorb stellar radiation and re-emit it at longer wavelengths. Because we observe spectral regions with and without substantial molecular opacity, we determine the stellar photospheric radius, uncontaminated by molecular emission. We infer that most of the molecular opacity arises at approximately twice the radius of the stellar photosphere.Comment: 12 pages, including 3 figures. Accepted by ApJ

Do Machines Replicate Humans? Toward a Unified Understanding of Radicalizing Content on the Open Social Web

The advent of the Internet inadvertently augmented the functioning and success of violent extremist organizations. Terrorist organizations like the Islamic State in Iraq and Syria (ISIS) use the Internet to project their message to a global audience. The majority of research and practice on web‐based terrorist propaganda uses human coders to classify content, raising serious concerns such as burnout, mental stress, and reliability of the coded data. More recently, technology platforms and researchers have started to examine the online content using automated classification procedures. However, there are questions about the robustness of automated procedures, given insufficient research comparing and contextualizing the difference between human and machine coding. This article compares output of three text analytics packages with that of human coders on a sample of one hundred nonindexed web pages associated with ISIS. We find that prevalent topics (e.g., holy war) are accurately detected by the three packages whereas nuanced concepts (Lone Wolf attacks) are generally missed. Our findings suggest that naïve approaches of standard applications do not approximate human understanding, and therefore consumption, of radicalizing content. Before radicalizing content can be automatically detected, we need a closer approximation to human understanding

Temozolomide resistance in glioblastoma cells occurs partly through epidermal growth factor receptor-mediated induction of connexin 43

Glioblastoma Multiforme (GBM) is an aggressive adult primary brain tumor with poor prognosis. GBM patients develop resistance to the frontline chemotherapy, temozolomide (TMZ). As the connexins (Cx) have been shown to have a complex role in GBM, we investigated the role of Cx43 in TMZ resistance. Cx43 was increased in the TMZ-resistant low passage and cell lines. This correlated with the data in The Cancer Genome Atlas. Cx43 knockdown, reporter gene assays, chromatin immunoprecipitation assay, real-time PCR and western blots verified a role for Cx43 in TMZ resistance. This occurred by TMZ-resistant GBM cells being able to activate epidermal growth factor receptor (EGFR). In turn, EGFR activated the JNK-ERK1/2-AP-1 axis to induce Cx43. The increased Cx43 was functional as indicated by gap junctional intercellular communication among the resistant GBM cells. Cell therapy could be a potential method to deliver drugs, such as anti-EGF to tumor cells. Similar strategies could be used to reverse the expression of Cx43 to sensitize GBM cells to TMZ. The studies showed the potential for targeting EGF in immune therapy. These agents can be used in conjunction with stem cell therapy to treat GBM

Single-cell mRNA transfection studies: Delivery, kinetics and statistics by numbers

AbstractIn artificial gene delivery, messenger RNA (mRNA) is an attractive alternative to plasmid DNA (pDNA) since it does not require transfer into the cell nucleus. Here we show that, unlike for pDNA transfection, the delivery statistics and dynamics of mRNA-mediated expression are generic and predictable in terms of mathematical modeling. We measured the single-cell expression time-courses and levels of enhanced green fluorescent protein (eGFP) using time-lapse microscopy and flow cytometry (FC). The single-cell analysis provides direct access to the distribution of onset times, life times and expression rates of mRNA and eGFP. We introduce a two-step stochastic delivery model that reproduces the number distribution of successfully delivered and translated mRNA molecules and thereby the dose–response relation. Our results establish a statistical framework for mRNA transfection and as such should advance the development of RNA carriers and small interfering/micro RNA-based drugs.From the Clinical EditorThis team of authors established a statistical framework for mRNA transfection by using a two-step stochastic delivery model that reproduces the number distribution of successfully delivered and translated mRNA molecules and thereby their dose-response relation. This study establishes a nice connection between theory and experimental planning and will aid the cellular delivery of mRNA molecules

The ins and outs of Mycobacterium tuberculosis protein export

Mycobacterium tuberculosis is an important pathogen that infects approximately one third of the world’s population and kills almost two million people annually. An important aspect of M. tuberculosis physiology and pathogenesis is its ability to export proteins into and across the thick mycobacterial cell envelope, where they are ideally positioned to interact with the host. In addition to the specific proteins that are exported by M. tuberculosis, the systems through which these proteins are exported represent potential targets for future drug development. M. tuberculosis possesses two well-known and conserved export systems: the housekeeping Sec pathway and the Tat pathway. In addition, M. tuberculosis possesses specialized export systems including the accessory SecA2 pathway and five ESX pathways. Here we review the current understanding of each of these export systems, with a focus on M. tuberculosis, and discuss the contribution of each system to disease and physiology

Protein Export by the Mycobacterial SecA2 System Is Determined by the Preprotein Mature Domain

At the core of the bacterial general secretion (Sec) pathway is the SecA ATPase, which powers translocation of unfolded preproteins containing Sec signal sequences through the SecYEG membrane channel. Mycobacteria have two nonredundant SecA homologs: SecA1 and SecA2. While the essential SecA1 handles “housekeeping” export, the nonessential SecA2 exports a subset of proteins and is required for Mycobacterium tuberculosis virulence. Currently, it is not understood how SecA2 contributes to Sec export in mycobacteria. In this study, we focused on identifying the features of two SecA2 substrates that target them to SecA2 for export, the Ms1704 and Ms1712 lipoproteins of the model organism Mycobacterium smegmatis. We found that the mature domains of Ms1704 and Ms1712, not the N-terminal signal sequences, confer SecA2-dependent export. We also demonstrated that the lipid modification and the extreme N terminus of the mature protein do not impart the requirement for SecA2 in export. We further showed that the Ms1704 mature domain can be efficiently exported by the twin-arginine translocation (Tat) pathway. Because the Tat system exports only folded proteins, this result implies that SecA2 substrates can fold in the cytoplasm and suggests a putative role of SecA2 in enabling export of such proteins. Thus, the mycobacterial SecA2 system may represent another way that bacteria solve the problem of exporting proteins that can fold in the cytoplasm