The dramaturgy of epidemics

My essay focuses on Charles Rosenberg's provocative and enduring ideal type of epidemic drama in three acts, which he assembled from a vast knowledge of disease history that stretched from the end of the seventeenth century to his then-present pandemic, HIV/AIDS of the 1980s. Reaching back to the Plague of Athens, my essay elaborates on Rosenberg's dramaturgy by questioning whether blame, division, and collective violence were so universal or even the dominant "acts" of epidemics not only before the nineteenth century but to the present. Instead, with certain pandemics such as yellow fever in the Deep South or the Great Influenza of 1918–20, unity, mass volunteerism, and self-abnegation played leading roles. Finally, not all epidemics ended "with a whimper" as attested by the long early modern history of plague. These often concluded literally with a bang: lavish planning of festivals of thanksgiving, choreographed with processions, innumerable banners, commissions of paintings, ex-voto churches, trumpets, tambourines, artillery fire, and fireworks

Infinite factorization of multiple non-parametric views

Combined analysis of multiple data sources has increasing application interest, in particular for distinguishing shared and source-specific aspects. We extend this rationale of classical canonical correlation analysis into a flexible, generative and non-parametric clustering setting, by introducing a novel non-parametric hierarchical mixture model. The lower level of the model describes each source with a flexible non-parametric mixture, and the top level combines these to describe commonalities of the sources. The lower-level clusters arise from hierarchical Dirichlet Processes, inducing an infinite-dimensional contingency table between the views. The commonalities between the sources are modeled by an infinite block model of the contingency table, interpretable as non-negative factorization of infinite matrices, or as a prior for infinite contingency tables. With Gaussian mixture components plugged in for continuous measurements, the model is applied to two views of genes, mRNA expression and abundance of the produced proteins, to expose groups of genes that are co-regulated in either or both of the views. Cluster analysis of co-expression is a standard simple way of screening for co-regulation, and the two-view analysis extends the approach to distinguishing between pre- and post-translational regulation

Dancing with death. A historical perspective on coping with covid-19

In this paper, we address the question on how societies coped with pandemic crises, how they tried to control or adapt to the disease, or even managed to overcome the death trap in history. On the basis of historical research, we describe how societies in the western world accommodated to or exited hardship and restrictive measures over the course of the last four centuries. In particular, we are interested in how historically embedded citizens' resources were directed towards living with and to a certain extent accepting the virus. Such an approach of “applied history” to the management of crises and public hazards, we believe, helps address today's pressing question of what adaptive strategies can be adopted to return to a normalized life, including living with socially acceptable medical, hygienic and other pandemic‐related measures

Measurement of the branching fraction and CP content for the decay B(0) -> D(*+)D(*-)

This is the pre-print version of the Article. The official published version can be accessed from the links below. Copyright @ 2002 APS.We report a measurement of the branching fraction of the decay B0→D*+D*- and of the CP-odd component of its final state using the BABAR detector. With data corresponding to an integrated luminosity of 20.4  fb-1 collected at the Υ(4S) resonance during 1999–2000, we have reconstructed 38 candidate signal events in the mode B0→D*+D*- with an estimated background of 6.2±0.5 events. From these events, we determine the branching fraction to be B(B0→D*+D*-)=[8.3±1.6(stat)±1.2(syst)]×10-4. The measured CP-odd fraction of the final state is 0.22±0.18(stat)±0.03(syst).This work is supported by DOE and NSF (USA), NSERC (Canada), IHEP (China), CEA and CNRS-IN2P3 (France), BMBF (Germany), INFN (Italy), NFR (Norway), MIST (Russia), and PPARC (United Kingdom). Individuals have received support from the A.P. Sloan Foundation, Research Corporation, and Alexander von Humboldt Foundation

Measurement of the B0-anti-B0-Oscillation Frequency with Inclusive Dilepton Events

The $B^0$-$\bar B^0$ oscillation frequency has been measured with a sample of 23 million \B\bar B pairs collected with the BABAR detector at the PEP-II asymmetric B Factory at SLAC. In this sample, we select events in which both B mesons decay semileptonically and use the charge of the leptons to identify the flavor of each B meson. A simultaneous fit to the decay time difference distributions for opposite- and same-sign dilepton events gives $\Delta m_d = 0.493 \pm 0.012{(stat)}\pm 0.009{(syst)}$ ps$^{-1}$.Comment: 7 pages, 1 figure, submitted to Physical Review Letter

Predicting Positive p53 Cancer Rescue Regions Using Most Informative Positive (MIP) Active Learning

Many protein engineering problems involve finding mutations that produce proteins with a particular function. Computational active learning is an attractive approach to discover desired biological activities. Traditional active learning techniques have been optimized to iteratively improve classifier accuracy, not to quickly discover biologically significant results. We report here a novel active learning technique, Most Informative Positive (MIP), which is tailored to biological problems because it seeks novel and informative positive results. MIP active learning differs from traditional active learning methods in two ways: (1) it preferentially seeks Positive (functionally active) examples; and (2) it may be effectively extended to select gene regions suitable for high throughput combinatorial mutagenesis. We applied MIP to discover mutations in the tumor suppressor protein p53 that reactivate mutated p53 found in human cancers. This is an important biomedical goal because p53 mutants have been implicated in half of all human cancers, and restoring active p53 in tumors leads to tumor regression. MIP found Positive (cancer rescue) p53 mutants in silico using 33% fewer experiments than traditional non-MIP active learning, with only a minor decrease in classifier accuracy. Applying MIP to in vivo experimentation yielded immediate Positive results. Ten different p53 mutations found in human cancers were paired in silico with all possible single amino acid rescue mutations, from which MIP was used to select a Positive Region predicted to be enriched for p53 cancer rescue mutants. In vivo assays showed that the predicted Positive Region: (1) had significantly more (p<0.01) new strong cancer rescue mutants than control regions (Negative, and non-MIP active learning); (2) had slightly more new strong cancer rescue mutants than an Expert region selected for purely biological considerations; and (3) rescued for the first time the previously unrescuable p53 cancer mutant P152L

Identification of Retinoic Acid in a High Content Screen for Agents that Overcome the Anti-Myogenic Effect of TGF-Beta-1

Transforming growth factor beta 1 (TGF-β1) is an inhibitor of muscle cell differentiation that is associated with fibrosis, poor regeneration and poor function in some diseases of muscle. When neutralizing antibodies to TGF-β1 or the angiotensin II inhibitor losartan were used to reduce TGF-β1 signaling, muscle morphology and function were restored in mouse models of Marfan Syndrome and muscular dystrophy. The goal of our studies was to identify additional agents that overcome the anti-myogenic effect of TGF-β1.A high-content cell-based assay was developed in a 96-well plate format that detects the expression of myosin heavy chain (MHC) in C2C12 cells. The assay was used to quantify the dose-dependent responses of C2C12 cell differentiation to TGF-β1 and to the TGF-β1 Type 1 receptor kinase inhibitor, SB431542. Thirteen agents previously described as promoting C2C12 differentiation in the absence of TGF-β1 were screened in the presence of TGF-β1. Only all-trans retinoic acid and 9-cis retinoic acid allowed a maximal level of C2C12 cell differentiation in the presence of TGF-β1; the angiotensin-converting enzyme inhibitor captopril and 10 nM estrogen provided partial rescue. Vitamin D was a potent inhibitor of retinoic acid-induced myogenesis in the presence of TGF-β1. TGF-β1 inhibits myoblast differentiation through activation of Smad3; however, retinoic acid did not inhibit TGF-β1-induced activation of a Smad3-dependent reporter gene in C2C12 cells.Retinoic acid alleviated the anti-myogenic effect of TGF-β1 by a Smad3-independent mechanism. With regard to the goal of improving muscle regeneration and function in individuals with muscle disease, the identification of retinoic acid is intriguing in that some retinoids are already approved for human therapy. However, retinoids also have well-described adverse effects. The quantitative, high-content assay will be useful to screen for less-toxic retinoids or combinations of agents that promote myoblast differentiation in the presence of TGF-β1