Hot Streaks in Artistic, Cultural, and Scientific Careers

The hot streak, loosely defined as winning begets more winnings, highlights a specific period during which an individual's performance is substantially higher than her typical performance. While widely debated in sports, gambling, and financial markets over the past several decades, little is known if hot streaks apply to individual careers. Here, building on rich literature on lifecycle of creativity, we collected large-scale career histories of individual artists, movie directors and scientists, tracing the artworks, movies, and scientific publications they produced. We find that, across all three domains, hit works within a career show a high degree of temporal regularity, each career being characterized by bursts of high-impact works occurring in sequence. We demonstrate that these observations can be explained by a simple hot-streak model we developed, allowing us to probe quantitatively the hot streak phenomenon governing individual careers, which we find to be remarkably universal across diverse domains we analyzed: The hot streaks are ubiquitous yet unique across different careers. While the vast majority of individuals have at least one hot streak, hot streaks are most likely to occur only once. The hot streak emerges randomly within an individual's sequence of works, is temporally localized, and is unassociated with any detectable change in productivity. We show that, since works produced during hot streaks garner significantly more impact, the uncovered hot streaks fundamentally drives the collective impact of an individual, ignoring which leads us to systematically over- or under-estimate the future impact of a career. These results not only deepen our quantitative understanding of patterns governing individual ingenuity and success, they may also have implications for decisions and policies involving predicting and nurturing individuals with lasting impact

Open data and digital morphology

Over the past two decades, the development of methods for visualizing and analysing specimens digitally, in three and even four dimensions, has transformed the study of living and fossil organisms. However, the initial promise, that the widespread application of such methods would facilitate access to the underlying digital data, has not been fully achieved. The underlying datasets for many published studies are not readily or freely available, introducing a barrier to verification and reproducibility, and the reuse of data. There is no current agreement or policy on the amount and type of data that should be made available alongside studies that use, and in some cases are wholly reliant on, digital morphology. Here, we propose a set of recommendations for minimum standards and additional best practice for 3D digital data publication, and review the issues around data storage, management and accessibility

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Preliminary analysis of immune activation in early onset type 2 diabetes

Introduction. First Nations and other Aboriginal children are disproportionately affected by cardiometabolic diseases, including type 2 diabetes (T2D). In T2D, the disruption of insulin signalling can be driven by pro-inflammatory immunity. Pro-inflammatory responses can be fueled by toll-like receptors (TLR) on immune cells such as peripheral blood mononuclear cells (PBMC, a white blood cell population). TLR4 can bind to lipids from bacteria and food sources activating PBMC to produce cytokines tumour necrosis factor (TNF)-α and interleukin (IL)-1β. These cytokines can interfere with insulin signalling. Here, we seek to understand how TLR4 activation may be involved in early onset T2D. We hypothesized that immune cells from youth with T2D (n=8) would be more reactive upon TLR4 stimulation relative to cells from age and body mass index (BMI)-matched controls without T2D (n=8). Methods. Serum samples were assayed for adipokines (adiponectin and leptin), as well as cytokines. Freshly isolated PBMC were examined for immune reactivity upon culture with TLR4 ligands bacterial lipopolysaccharide (LPS, 2 and 0.2 ng/ml) and the fatty acid palmitate (200 µM). Culture supernatants were evaluated for the amount of TNF-α and IL-1β produced by PBMC. Results. Youth with T2D displayed lower median serum adiponectin levels compared to controls (395 vs. 904 ng/ml, p<0.05). PBMC isolated from youth with and without T2D produced similar levels of TNF-α and IL-1β after exposure to the higher LPS concentration. However, at the low LPS dose the T2D cohort exhibited enhanced IL-1β synthesis relative to the control cohort. Additionally, exposure to palmitate resulted in greater IL-1β synthesis in PBMCs isolated from youth with T2D versus controls (p<0.05). These differences in cytokine production corresponded to greater monocyte activation in the T2D cohort. Conclusion. These preliminary results suggest that cellular immune responses are exaggerated in T2D, particularly with respect to IL-1β activity. These studies aim to improve the understanding of the biology behind early onset T2D and its vascular complications that burden First Nations people

Social disparities in food preparation behaviours: a DEDIPAC study

BACKGROUND: The specific role of major socio-economic indicators in influencing food preparation behaviours could reveal distinct socio-economic patterns, thus enabling mechanisms to be understood that contribute to social inequalities in health. This study investigated whether there was an independent association of each socio-economic indicator (education, occupation, income) with food preparation behaviours. METHODS: A total of 62,373 adults participating in the web-based NutriNet-Santé cohort study were included in our cross-sectional analyses. Cooking skills, preparation from scratch and kitchen equipment were assessed using a 0-10-point score; frequency of meal preparation, enjoyment of cooking and willingness to cook better/more frequently were categorical variables. Independent associations between socio-economic factors (education, income and occupation) and food preparation behaviours were assessed using analysis of covariance and logistic regression models stratified by sex. The models simultaneously included the three socio-economic indicators, adjusting for age, household composition and whether or not they were the main cook in the household. RESULTS: Participants with the lowest education, the lowest income group and female manual and office workers spent more time preparing food daily than participants with the highest education, those with the highest income and managerial staff (P < 0.0001). The lowest educated individuals were more likely to be non-cooks than those with the highest education level (Women: OR = 3.36 (1.69;6.69); Men: OR = 1.83 (1.07;3.16)) while female manual and office workers and the never-employed were less likely to be non-cooks (OR = 0.52 (0.28;0.97); OR = 0.30 (0.11;0.77)). Female manual and office workers had lower scores of preparation from scratch and were less likely to want to cook more frequently than managerial staff (P < 0.001 and P < 0.001). Women belonging to the lowest income group had a lower score of kitchen equipment (P < 0.0001) and were less likely to enjoy cooking meal daily (OR = 0.68 (0.45;0.86)) than those with the highest income. CONCLUSION: Lowest socio-economic groups, particularly women, spend more time preparing food than high socioeconomic groups. However, female manual and office workers used less raw or fresh ingredients to prepare meals than managerial staff. In the unfavourable context in France with reduced time spent preparing meals over last decades, our findings showed socioeconomic disparities in food preparation behaviours in women, whereas few differences were observed in men

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Dose-Specific Adverse Drug Reaction Identification in Electronic Patient Records: Temporal Data Mining in an Inpatient Psychiatric Population

BACKGROUND: Data collected for medical, filing and administrative purposes in electronic patient records (EPRs) represent a rich source of individualised clinical data, which has great potential for improved detection of patients experiencing adverse drug reactions (ADRs), across all approved drugs and across all indication areas. OBJECTIVES: The aim of this study was to take advantage of techniques for temporal data mining of EPRs in order to detect ADRs in a patient- and dose-specific manner. METHODS: We used a psychiatric hospital’s EPR system to investigate undesired drug effects. Within one workflow the method identified patient-specific adverse events (AEs) and links these to specific drugs and dosages in a temporal manner, based on integration of text mining results and structured data. The structured data contained precise information on drug identity, dosage and strength. RESULTS: When applying the method to the 3,394 patients in the cohort, we identified AEs linked with a drug in 2,402 patients (70.8 %). Of the 43,528 patient-specific drug substances prescribed, 14,736 (33.9 %) were linked with AEs. From these links we identified multiple ADRs (p < 0.05) and found them to occur at similar frequencies, as stated by the manufacturer and in the literature. We showed that drugs displaying similar ADR profiles share targets, and we compared submitted spontaneous AE reports with our findings. For nine of the ten most prescribed antipsychotics in the patient population, larger doses were prescribed to sedated patients than non-sedated patients; five patients exhibited a significant difference (p < 0.05). Finally, we present two cases (p < 0.05) identified by the workflow. The method identified the potentially fatal AE QT prolongation caused by methadone, and a non-described likely ADR between levomepromazine and nightmares found among the hundreds of identified novel links between drugs and AEs (p < 0.05). CONCLUSIONS: The developed method can be used to extract dose-dependent ADR information from already collected EPR data. Large-scale AE extraction from EPRs may complement or even replace current drug safety monitoring methods in the future, reducing or eliminating manual reporting and enabling much faster ADR detection. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s40264-014-0145-z) contains supplementary material, which is available to authorised users

Identification of metabolic pathways influenced by the G-protein coupled receptors GprB and GprD in Aspergillus nidulans

Heterotrimeric G-protein-mediated signaling pathways play a pivotal role in transmembrane signaling in eukaryotes. Our main aim was to identify signaling pathways regulated by A. nidulans GprB and GprD G-protein coupled receptors (GPCRs). When these two null mutant strains were compared to the wild-type strain, the DeltagprB mutant showed an increased protein kinase A (PKA) activity while growing in glucose 1% and during starvation. In contrast, the DeltagprD has a much lower PKA activity upon starvation. Transcriptomics and (1)H NMR-based metabolomics were performed on two single null mutants grown on glucose. We noted modulation in the expression of 11 secondary metabolism gene clusters when the DeltagprB and DeltagprD mutant strains were grown in 1% glucose. Several members of the sterigmatocystin-aflatoxin gene cluster presented down-regulation in both mutant strains. The genes of the NR-PKS monodictyphenone biosynthesis cluster had overall increased mRNA accumulation in DeltagprB, while in the DeltagprD mutant strain the genes had decreased mRNA accumulation. Principal component analysis of the metabolomic data demonstrated that there was a significant metabolite shift in the DeltagprD strain. The (1)H NMR analysis revealed significant expression of essential amino acids with elevated levels in the DeltagprD strain, compared to the wild-type and DeltagprB strains. With the results, we demonstrated the differential expression of a variety of genes related mainly to secondary metabolism, sexual development, stress signaling, and amino acid metabolism. We propose that the absence of GPCRs triggered stress responses at the genetic level. The data suggested an intimate relationship among different G-protein coupled receptors, fine-tune regulation of secondary and amino acid metabolisms, and fungal development

The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex

Is visual cortex made up of general-purpose information processing machinery, or does it consist of a collection of specialized modules? If prior knowledge, acquired from learning a set of objects is only transferable to new objects that share properties with the old, then the recognition system’s optimal organization must be one containing specialized modules for different object classes. Our analysis starts from a premise we call the invariance hypothesis: that the computational goal of the ventral stream is to compute an invariant-to-transformations and discriminative signature for recognition. The key condition enabling approximate transfer of invariance without sacrificing discriminability turns out to be that the learned and novel objects transform similarly. This implies that the optimal recognition system must contain subsystems trained only with data from similarly-transforming objects and suggests a novel interpretation of domain-specific regions like the fusiform face area (FFA). Furthermore, we can define an index of transformation-compatibility, computable from videos, that can be combined with information about the statistics of natural vision to yield predictions for which object categories ought to have domain-specific regions in agreement with the available data. The result is a unifying account linking the large literature on view-based recognition with the wealth of experimental evidence concerning domain-specific regions.National Science Foundation (U.S.). Science and Technology Center (Award CCF-1231216)National Science Foundation (U.S.) (Grant NSF-0640097)National Science Foundation (U.S.) (Grant NSF-0827427)United States. Air Force Office of Scientific Research (Grant FA8650-05-C-7262)Eugene McDermott Foundatio