Divergent mathematical treatments in utility theory

In this paper I study how divergent mathematical treatments affect mathematical modelling, with a special focus on utility theory. In particular I examine recent work on the ranking of information states and the discounting of future utilities, in order to show how, by replacing the standard analytical treatment of the models involved with one based on the framework of Nonstandard Analysis, diametrically opposite results are obtained. In both cases, the choice between the standard and nonstandard treatment amounts to a selection of set-theoretical parameters that cannot be made on purely empirical grounds. The analysis of this phenomenon gives rise to a simple logical account of the relativity of impossibility theorems in economic theory, which concludes the paper

Efficiency of primary saliva secretion: an analysis of parameter dependence in dynamic single-cell and acinus models, with application to aquaporin knockout studies

Secretion from the salivary glands is driven by osmosis following the establishment of osmotic gradients between the lumen, the cell and the interstitium by active ion transport. We consider a dynamic model of osmotically driven primary saliva secretion and use singular perturbation approaches and scaling assumptions to reduce the model. Our analysis shows that isosmotic secretion is the most efficient secretion regime and that this holds for single isolated cells and for multiple cells assembled into an acinus. For typical parameter variations, we rule out any significant synergistic effect on total water secretion of an acinar arrangement of cells about a single shared lumen. Conditions for the attainment of isosmotic secretion are considered, and we derive an expression for how the concentration gradient between the interstitium and the lumen scales with water- and chloride-transport parameters. Aquaporin knockout studies are interpreted in the context of our analysis and further investigated using simulations of transport efficiency with different membrane water permeabilities. We conclude that recent claims that aquaporin knockout studies can be interpreted as evidence against a simple osmotic mechanism are not supported by our work. Many of the results that we obtain are independent of specific transporter details, and our analysis can be easily extended to apply to models that use other proposed ionic mechanisms of saliva secretion

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

The intersection of COVID-19 and autoimmunity

Acute coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, is characterized by diverse clinical presentations, ranging from asymptomatic infection to fatal respiratory failure, and often associated with varied longer-term sequelae. Over the past 18 months, it has become apparent that inappropriate immune responses contribute to the pathogenesis of severe COVID-19. Researchers working at the intersection of COVID-19 and autoimmunity recently gathered at an American Autoimmune Related Disease Association (AARDA) Noel R. Rose Colloquium to address the current state of knowledge regarding two important questions: Does established autoimmunity predispose to severe COVID-19? And, at the same time, can SARS-CoV-2 infection trigger de novo autoimmunity? Indeed, work to date has demonstrated that 10 to 15% of patients with critical COVID-19 pneumonia exhibit autoantibodies against type I interferons, suggesting that preexisting autoimmunity underlies severe disease in some patients. Other studies have identified functional autoantibodies following infection with SARS-CoV-2, such as those that promote thrombosis or antagonize cytokine signaling. These autoantibodies may arise from a predominantly extrafollicular B cell response that is more prone to generating autoantibody-secreting B cells. This review highlights the current understanding, evolving concepts, and unanswered questions provided by this unique opportunity to determine mechanisms by which a viral infection can be exacerbated by, and even trigger, autoimmunity. The potential role of autoimmunity in post-acute sequelae of COVID-19 is also discussed

An Anti-Human ICAM-1 Antibody Inhibits Rhinovirus-Induced Exacerbations of Lung Inflammation

Human rhinoviruses (HRV) cause the majority of common colds and acute exacerbations of asthma and chronic obstructive pulmonary disease (COPD). Effective therapies are urgently needed, but no licensed treatments or vaccines currently exist. Of the 100 identified serotypes, ∼90% bind domain 1 of human intercellular adhesion molecule-1 (ICAM-1) as their cellular receptor, making this an attractive target for development of therapies; however, ICAM-1 domain 1 is also required for host defence and regulation of cell trafficking, principally via its major ligand LFA-1. Using a mouse anti-human ICAM-1 antibody (14C11) that specifically binds domain 1 of human ICAM-1, we show that 14C11 administered topically or systemically prevented entry of two major groups of rhinoviruses, HRV16 and HRV14, and reduced cellular inflammation, pro-inflammatory cytokine induction and virus load in vivo. 14C11 also reduced cellular inflammation and Th2 cytokine/chemokine production in a model of major group HRV-induced asthma exacerbation. Interestingly, 14C11 did not prevent cell adhesion via human ICAM-1/LFA-1 interactions in vitro, suggesting the epitope targeted by 14C11 was specific for viral entry. Thus a human ICAM-1 domain-1-specific antibody can prevent major group HRV entry and induction of airway inflammation in vivo

Ribose 2′-O-methylation provides a molecular signature for the distinction of self and non-self mRNA dependent on the RNA sensor Mda5

The 5'-cap-structures of higher eukaryote mRNAs are ribose 2'-O-methylated. Likewise, a number of viruses replicating in the cytoplasm of eukayotes have evolved 2'-O-methyltransferases to modify autonomously their mRNAs. However, a defined biological role of mRNA 2'-O-methylation remains elusive. Here we show that viral mRNA 2'-O-methylation is critically involved in subversion of type-I-interferon (IFN-I) induction. We demonstrate that human and murine coronavirus 2'-O-methyltransferase mutants induce increased IFN-I expression, and are highly IFN-I sensitive. Importantly, IFN-I induction by 2'-O-methyltransferase-deficient viruses is dependent on the cytoplasmic RNA sensor melanoma differentiation-associated gene 5 (MDA5). This link between MDA5-mediated sensing of viral RNA and mRNA 2'-O-methylation suggests that RNA modifications, such as 2'-O-methylation, provide a molecular signature for the discrimination of self and non-self mRNA

Tracing the role of human civilization in the globalization of plant pathogens

Acknowledgments. We apologize to all those colleagues whose work was not cited because of space restrictions.Peer reviewedPostprin

Determining the neurotransmitter concentration profile at active synapses

Establishing the temporal and concentration profiles of neurotransmitters during synaptic release is an essential step towards understanding the basic properties of inter-neuronal communication in the central nervous system. A variety of ingenious attempts has been made to gain insights into this process, but the general inaccessibility of central synapses, intrinsic limitations of the techniques used, and natural variety of different synaptic environments have hindered a comprehensive description of this fundamental phenomenon. Here, we describe a number of experimental and theoretical findings that has been instrumental for advancing our knowledge of various features of neurotransmitter release, as well as newly developed tools that could overcome some limits of traditional pharmacological approaches and bring new impetus to the description of the complex mechanisms of synaptic transmission

Enriched environment and physical activity reduce microglia and influence the fate of NG2 cells in the amygdala of adult mice

Proliferative cells expressing proteoglycan neuron-glia 2 (NG2) are considered to represent parenchymal precursor cells in the adult brain and are thought to differentiate primarily into oligodendrocytes. We have studied cell genesis in the adult amygdala and found that, up to 1 year after the labeling of proliferating cells with bromodeoxyuridine, most proliferating NG2 cells remain NG2 cells, and only a few slowly differentiate into mature oligodendrocytes, as assessed by the expression of 2',3'-cyclic nucleotide 3'-phosphodiesterase. We have detected no signs of neurogenesis but have confirmed the expression of “neuronal” markers such as Doublecortin in NG2 cells. Nestin-expressing NG2 cells in the amygdala show electrophysiological properties known for oligodendrocyte precursor cells in the corpus callosum. Application of the glutamate agonist kainate elicits a “complex” response consisting of a rapid and long-lasting blockade of the resting K+ conductance, a transient cationic current, and a transient increase of an outwardly directed K+ conductance, suggesting the responsiveness of NG2 cells to excitation. Proliferation of NG2 cells increases in response to behavioral stimuli of activity, voluntary wheel running, and environmental enrichment. In addition to reducing the number of newborn microglia, behavioral activity results in a decrease in S100β-expressing newborn NG2 cells in the amygdala. Because S100β expression in NG2 cells ceases with oligodendrocyte maturation, this finding suggests that NG2 cells in the amygdala undergo activity-dependent functional alterations, without resulting in a measurable increase in new mature oligodendrocytes over the time period covered by the present study. The adult amygdala thus shows signs of mixed activity-dependent plasticity: reduced numbers of microglia and, presumably, an altered fate of NG2 cells

The Eyes Have It: Sex and Sexual Orientation Differences in Pupil Dilation Patterns

Recent research suggests profound sex and sexual orientation differences in sexual response. These results, however, are based on measures of genital arousal, which have potential limitations such as volunteer bias and differential measures for the sexes. The present study introduces a measure less affected by these limitations. We assessed the pupil dilation of 325 men and women of various sexual orientations to male and female erotic stimuli. Results supported hypotheses. In general, self-reported sexual orientation corresponded with pupil dilation to men and women. Among men, substantial dilation to both sexes was most common in bisexual-identified men. In contrast, among women, substantial dilation to both sexes was most common in heterosexual-identified women. Possible reasons for these differences are discussed. Because the measure of pupil dilation is less invasive than previous measures of sexual response, it allows for studying diverse age and cultural populations, usually not included in sexuality research