Mathematics, capitalism and biosocial research

In my previous work, I criticised studies within the sociopolitical turn for disavowing a comprehension of schools as places of capitalist production. Here, I extend this critique to what is being flagged as a new turn in educational research. I am referring to biosocial research, particularly in the way it is coupled with new materialist and more than human philosophies in the work of Elizabeth de Freitas. I use elements from Marxian theory and Lacanian psychoanalysis to explore the concomitances between mathematics and capitalism, showing how both mathematics and capital need to suture the subject in order to thrive. Biosocial research epitomises this drive towards automation and totality, and, notwithstanding de Freitas’ attempts to rescue it from the logic of control, I will argue that agent-centred intentions dismiss the underlying workings of capital as a real abstraction. I do so by engaging with elements of Deleuze’s philosophy, showing how the more than human frame in which de Freitas’ biosocial research rests contradicts her own perception of how biosocial research can be rescued for inclusive purposes

Pain Behavior Changes Following Disc Puncture Relate to Nucleus Pulposus Rather than to the Disc Injury Per Se: An Experimental Study in Rats

It has previously been demonstrated that disc puncture in the rat induced changes in grooming and wet dog shakes, two behavioral changes that may be linked to discomfort and neuropathic pain. In this study the aim was to separate the effects of disc injury and the epidural presence of nucleus pulposus. Following anesthesia, the L4-5 disc was exposed using a dorsal approach. Ten rats received a superficial disc injury without nucleus pulposus leakage and ten rats received nucleus pulposus from a donor rat without disc injury. In ten animals the L4-5 disc was punctured using a ventral approach, with 10 corresponding controls. Spontaneous behavior was assessed after surgery. The data was matched to historical control of dorsal sham surgery and disc puncture. The study showed that the effects of nucleus pulposus were more pronounced than the effects induced by the disc injury. Ventral disc puncture did not induce any behavioral changes different from sham exposure. In conclusion, the data from the study indicate that behavioral changes induced by disc puncture are more likely to relate to the epidural presence of nucleus pulposus than the disc injury per se

Loss of ARNT in skeletal muscle limits muscle regeneration in aging

The ability of skeletal muscle to regenerate declines significantly with aging. The expression of aryl hydrocarbon receptor nuclear translocator (ARNT), a critical component of the hypoxia signaling pathway, was less abundant in skeletal muscle of old (23-25 months old) mice. This loss of ARNT was associated with decreased levels of Notch1 intracellular domain (N1ICD) and impaired regenerative response to injury in comparison to young (2-3 months old) mice. Knockdown of ARNT in a primary muscle cell line impaired differentiation in vitro. Skeletal muscle-specific ARNT deletion in young mice resulted in decreased levels of whole muscle N1ICD and limited muscle regeneration. Administration of a systemic hypoxia pathway activator (ML228), which simulates the actions of ARNT, rescued skeletal muscle regeneration in both old and ARNT-deleted mice. These results suggest that the loss of ARNT in skeletal muscle is partially responsible for diminished myogenic potential in aging and activation of hypoxia signaling holds promise for rescuing regenerative activity in old muscle

Machine learning for regulatory analysis and transcription factor target prediction in yeast

High throughput technologies, including array-based chromatin immunoprecipitation, have rapidly increased our knowledge of transcriptional maps—the identity and location of regulatory binding sites within genomes. Still, the full identification of sites, even in lower eukaryotes, remains largely incomplete. In this paper we develop a supervised learning approach to site identification using support vector machines (SVMs) to combine 26 different data types. A comparison with the standard approach to site identification using position specific scoring matrices (PSSMs) for a set of 104 Saccharomyces cerevisiae regulators indicates that our SVM-based target classification is more sensitive (73 vs. 20%) when specificity and positive predictive value are the same. We have applied our SVM classifier for each transcriptional regulator to all promoters in the yeast genome to obtain thousands of new targets, which are currently being analyzed and refined to limit the risk of classifier over-fitting. For the purpose of illustration we discuss several results, including biochemical pathway predictions for Gcn4 and Rap1. For both transcription factors SVM predictions match well with the known biology of control mechanisms, and possible new roles for these factors are suggested, such as a function for Rap1 in regulating fermentative growth. We also examine the promoter melting temperature curves for the targets of YJR060W, and show that targets of this TF have potentially unique physical properties which distinguish them from other genes. The SVM output automatically provides the means to rank dataset features to identify important biological elements. We use this property to rank classifying k-mers, thereby reconstructing known binding sites for several TFs, and to rank expression experiments, determining the conditions under which Fhl1, the factor responsible for expression of ribosomal protein genes, is active. We can see that targets of Fhl1 are differentially expressed in the chosen conditions as compared to the expression of average and negative set genes. SVM-based classifiers provide a robust framework for analysis of regulatory networks. Processing of classifier outputs can provide high quality predictions and biological insight into functions of particular transcription factors. Future work on this method will focus on increasing the accuracy and quality of predictions using feature reduction and clustering strategies. Since predictions have been made on only 104 TFs in yeast, new classifiers will be built for the remaining 100 factors which have available binding data

Symbolising the real of mathematics education

This text, occasioned by a critical reading of Tony Brown’s new book Mathematics Education and Subjectivity, aims at contributing to the building of a sociopolitical approach to mathematics education based on Lacanian psychoanalysis and Slavoj Žižek’s philosophy. Brown has been bringing into the field of mathematics education the work of these two scholars, and his work has been important in understanding the cultural dynamics of school mathematics. This article highlights the limitations of Brown’s use of Lacanian theory and outlines a framework to understand students’ learning not in terms of the inherent properties of mathematics but in terms of the role this school subject plays within political economy

Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources

<p>Abstract</p> <p>Background</p> <p>Gene expression profiling studies of mastitis in ruminants have provided key but fragmented knowledge for the understanding of the disease. A systematic combination of different expression profiling studies via meta-analysis techniques has the potential to test the extensibility of conclusions based on single studies. Using the program Pointillist, we performed meta-analysis of transcription-profiling data from six independent studies of infections with mammary gland pathogens, including samples from cattle challenged <it>in vivo </it>with <it>S. aureus</it>, <it>E. coli</it>, and <it>S. uberis</it>, samples from goats challenged <it>in vivo </it>with <it>S. aureus</it>, as well as cattle macrophages and ovine dendritic cells infected <it>in vitro </it>with <it>S. aureus</it>. We combined different time points from those studies, testing different responses to mastitis infection: overall (common signature), early stage, late stage, and cattle-specific.</p> <p>Results</p> <p>Ingenuity Pathway Analysis of affected genes showed that the four meta-analysis combinations share biological functions and pathways (e.g. protein ubiquitination and polyamine regulation) which are intrinsic to the general disease response. In the overall response, pathways related to immune response and inflammation, as well as biological functions related to lipid metabolism were altered. This latter observation is consistent with the milk fat content depression commonly observed during mastitis infection. Complementarities between early and late stage responses were found, with a prominence of metabolic and stress signals in the early stage and of the immune response related to the lipid metabolism in the late stage; both mechanisms apparently modulated by few genes, including <it>XBP1 </it>and <it>SREBF1</it>.</p> <p>The cattle-specific response was characterized by alteration of the immune response and by modification of lipid metabolism. Comparison of <it>E. coli </it>and <it>S. aureus </it>infections in cattle <it>in vivo </it>revealed that affected genes showing opposite regulation had the same altered biological functions and provided evidence that <it>E. coli </it>caused a stronger host response.</p> <p>Conclusions</p> <p>This meta-analysis approach reinforces previous findings but also reveals several novel themes, including the involvement of genes, biological functions, and pathways that were not identified in individual studies. As such, it provides an interesting proof of principle for future studies combining information from diverse heterogeneous sources.</p

From Harm to Robustness: A Principled Approach to Vice Regulation

John Stuart Mill’s harm principle maintains that adult behavior cannot justifiably be subject to social coercion unless the behavior involves harm or a significant risk of harm to non-consenting others. The absence of harms to others, however, is one of the distinguishing features of many manifestations of “vices” such as the consumption of alcohol, nicotine, recreational drugs, prostitution, pornography, and gambling. It is with respect to vice policy, then, that the harm principle tends to be most constraining, and some current vice controls, such as prohibitions on drug possession and prostitution, violate Mill’s precept. In the vice arena, we seem to be willing to accept social interference with what Mill termed “self-regarding” behavior. But does that willingness then imply that any social intervention into private affairs is justifiable, that the government has just as much right to outlaw Protestantism, or shag carpets, or spicy foods, as it does to outlaw drugs? In this paper I argue that advances in neuroscience and behavioral economics offer strong evidence that vices and other potentially addictive goods or activities frequently involve less-than-rational choices, and hence are exempt from the full force of the harm principle. As an alternative guide to vice policy, and following some guidance from Mill, I propose the “robustness principle”: public policy towards addictive or vicious activities engaged in by adults should be robust with respect to departures from full rationality. That is, policies should work pretty well if everyone is completely rational, and policies should work pretty well even if many people are occasionally (or frequently) irrational in their vice-related choices. The harm and robustness principles cohere in many ways, but the robustness principle offers more scope for policies that try to direct people “for their own good,” without opening the door to tyrannical inroads upon self-regarding behavior

13C NMR-based chemical fingerprint for the varietal and geographical discrimination of wines

A fast, economic, and eco-friendly methodology for the wine variety and geographical origin differentiation using 13C nuclear magnetic resonance (NMR) data in combination with machine learning was developed. Wine samples of different grape varieties cultivated in different regions in Greece were subjected to 13C NMR analysis. The relative integrals of the 13C spectral window were processed and extracted to build a chemical fingerprint for the characterization of each specific wine variety, and then subjected to factor analysis, multivariate analysis of variance, and k-nearest neighbors analysis. The statistical analysis results showed that the 13C NMR fingerprint could be used as a rapid and accurate indicator of the wine variety differentiation. An almost perfect classification rate based on training (99.8%) and holdout methods (99.9%) was obtained. Results were further tested on the basis of Cronbach's alpha reliability analysis, where a very low random error (0.30) was estimated, indicating the accuracy and strength of the aforementioned methodology for the discrimination of the wine variety. The obtained data were grouped according to the geographical origin of wine samples and further subjected to principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The PLS-DA and variable importance in projection (VIP) allowed the determination of a chemical fingerprint characteristic of each geographical group. The statistical analysis revealed the possibility of acquiring useful information on wines, by simply processing the 13C NMR raw data, without the need to determine any specific metabolomic profile. In total, the obtained fingerprint can be used for the development of rapid quality-control methodologies concerning wine