The PageRank Axioms

This talk introduces the first graph-theoretic, ordinal representation theorem for the PageRank algorithm, bridging the gap between page ranking algorithms and the formal theory of social choice

Nonmanipulable Selections from a Tournament

A tournament is a binary dominance relation on a set of alternatives. Tournaments arise in many contexts that are relevant to AI, most notably in voting (as a method to aggregate the preferences of agents). There are many works that deal with choice rules that select a desirable alternative from a tournament, but very few of them deal directly with incentive issues, despite the fact that game-theoretic considerations are crucial with respect to systems populated by selfish agents. We deal with the problem of the manipulation of choice rules by considering two types of manipulation. We say that a choice rule is emph{monotonic} if an alternative cannot get itself selected by losing on purpose, and emph{pairwise nonmanipulable} if a pair of alternatives cannot make one of them the winner by reversing the outcome of the match between them. Our main result is a combinatorial construction of a choice rule that is monotonic, pairwise nonmanipulable, and onto the set of alternatives, for any number of alternatives besides three

BioNumbers—the database of key numbers in molecular and cell biology

BioNumbers (http://www.bionumbers.hms.harvard.edu) is a database of key numbers in molecular and cell biology—the quantitative properties of biological systems of interest to computational, systems and molecular cell biologists. Contents of the database range from cell sizes to metabolite concentrations, from reaction rates to generation times, from genome sizes to the number of mitochondria in a cell. While always of importance to biologists, having numbers in hand is becoming increasingly critical for experimenting, modeling, and analyzing biological systems. BioNumbers was motivated by an appreciation of how long it can take to find even the simplest number in the vast biological literature. All numbers are taken directly from a literature source and that reference is provided with the number. BioNumbers is designed to be highly searchable and queries can be performed by keywords or browsed by menus. BioNumbers is a collaborative community platform where registered users can add content and make comments on existing data. All new entries and commentary are curated to maintain high quality. Here we describe the database characteristics and implementation, demonstrate its use, and discuss future directions for its development

The Iterative Signature Algorithm for the analysis of large scale gene expression data

We present a new approach for the analysis of genome-wide expression data. Our method is designed to overcome the limitations of traditional techniques, when applied to large-scale data. Rather than alloting each gene to a single cluster, we assign both genes and conditions to context-dependent and potentially overlapping transcription modules. We provide a rigorous definition of a transcription module as the object to be retrieved from the expression data. An efficient algorithm, that searches for the modules encoded in the data by iteratively refining sets of genes and conditions until they match this definition, is established. Each iteration involves a linear map, induced by the normalized expression matrix, followed by the application of a threshold function. We argue that our method is in fact a generalization of Singular Value Decomposition, which corresponds to the special case where no threshold is applied. We show analytically that for noisy expression data our approach leads to better classification due to the implementation of the threshold. This result is confirmed by numerical analyses based on in-silico expression data. We discuss briefly results obtained by applying our algorithm to expression data from the yeast S. cerevisiae.Comment: Latex, 36 pages, 8 figure

International validation of Enhanced Recovery After Surgery Society guidelines on enhanced recovery for gynecologic surgery

Background: Enhanced Recovery After Surgery Society publishes guidelines on perioperative care, but these guidelines should be validated prospectively. Objective: To evaluate the association between compliance with Enhanced Recovery After Surgery Gynecologic/Oncology guideline elements and postoperative outcomes in an international cohort. Study Design: The study comprised 2101 patients undergoing elective gynecologic/oncology surgery between January 2011 and November 2017 in 10 hospitals across Canada, the United States, and Europe. Patient demographics, surgical/anesthesia details, and Enhanced Recovery After Surgery protocol compliance elements (pre-, intra-, and postoperative phases) were entered into the Enhanced Recovery After Surgery Interactive Audit System. Surgical complexity was stratified according to the Aletti scoring system (low vs medium/high). The following covariates were accounted for in the analysis: age, body mass index, smoking status, presence of diabetes, American Society of Anesthesiologists class, International Federation of Gynecology and Obstetrics stage, preoperative chemotherapy, radiotherapy, operating time, surgical approach (open vs minimally invasive), intraoperative blood loss, hospital, and Enhanced Recovery After Surgery implementation status. The primary end points were primary hospital length of stay and complications. Negative binomial regression was used to model length of stay, and logistic regression to model complications, as a function of compliance score and covariates. Results: Patient demographics included a median age 56 years, 35.5% obese, 15% smokers, and 26.7% American Society of Anesthesiologists Class III-IV. Final diagnosis was malignant in 49% of patients. Laparotomy was used in 75.9% of cases, and the remainder minimally invasive surgery. The majority of cases (86%) were of low complexity (Aletti score ≤3). In patients with ovarian cancer, 69.5% had a medium/high complexity surgery (Aletti score 4–11). Median length of stay was 2 days in the low- and 5 days in the medium/high-complexity group. Every unit increase in Enhanced Recovery After Surgery guideline score was associated with 8% (IRR, 0.92; 95% confidence interval, 0.90–0.95; P\u3c.001) decrease in days in hospital among low-complexity, and 12% (IRR, 0.88; 95% confidence interval, 0.82–0.93; P\u3c.001) decrease among patients with medium/high-complexity scores. For every unit increase in Enhanced Recovery After Surgery guideline score, the odds of total complications were estimated to be 12% lower (P\u3c.05) among low-complexity patients. Conclusion: Audit of surgical practices demonstrates that improved compliance with Enhanced Recovery After Surgery Gynecologic/Oncology guidelines is associated with an improvement in clinical outcomes, including length of stay, highlighting the importance of Enhanced Recovery After Surgery implementation

How does study quality affect the results of a diagnostic meta-analysis?

Background: The use of systematic literature review to inform evidence based practice in diagnostics is rapidly expanding. Although the primary diagnostic literature is extensive, studies are often of low methodological quality or poorly reported. There has been no rigorously evaluated, evidence based tool to assess the methodological quality of diagnostic studies. The primary objective of this study was to determine the extent to which variations in the quality of primary studies impact the results of a diagnostic meta-analysis and whether this differs with diagnostic test type. A secondary objective was to contribute to the evaluation of QUADAS, an evidence-based tool for the assessment of quality in diagnostic accuracy studies. Methods: This study was conducted as part of large systematic review of tests used in the diagnosis and further investigation of urinary tract infection (UTI) in children. All studies included in this review were assessed using QUADAS, an evidence-based tool for the assessment of quality in systematic reviews of diagnostic accuracy studies. The impact of individual components of QUADAS on a summary measure of diagnostic accuracy was investigated using regression analysis. The review divided the diagnosis and further investigation of UTI into the following three clinical stages: diagnosis of UTI, localisation of infection, and further investigation of the UTI. Each stage used different types of diagnostic test, which were considered to involve different quality concerns. Results: Many of the studies included in our review were poorly reported. The proportion of QUADAS items fulfilled was similar for studies in different sections of the review. However, as might be expected, the individual items fulfilled differed between the three clinical stages. Regression analysis found that different items showed a strong association with test performance for the different tests evaluated. These differences were observed both within and between the three clinical stages assessed by the review. The results of regression analyses were also affected by whether or not a weighting (by sample size) was applied. Our analysis was severely limited by the completeness of reporting and the differences between the index tests evaluated and the reference standards used to confirm diagnoses in the primary studies. Few tests were evaluated by sufficient studies to allow meaningful use of meta-analytic pooling and investigation of heterogeneity. This meant that further analysis to investigate heterogeneity could only be undertaken using a subset of studies, and that the findings are open to various interpretations. Conclusion: Further work is needed to investigate the influence of methodological quality on the results of diagnostic meta-analyses. Large data sets of well-reported primary studies are needed to address this question. Without significant improvements in the completeness of reporting of primary studies, progress in this area will be limited

Treatment of established postoperative nausea and vomiting: a quantitative systematic review

BACKGROUND: The relative efficacy of antiemetics for the treatment of postoperative nausea and vomiting (PONV) is poorly understood. METHODS: Systematic search (MEDLINE, Embase, Cochrane Library, bibliographies, any language, to 8.2000) for randomised comparisons of antiemetics with any comparator for the treatment of established PONV. Dichotomous data on prevention of further nausea and vomiting, and on side effects were combined using a fixed effect model. RESULTS: In seven trials (1,267 patients), 11 different antiemetics were tested without placebos; these data were not further analysed. Eighteen trials (3,809) had placebo controls. Dolasetron 12.5–100 mg, granisetron 0.1–3 mg, tropisetron 0.5–5 mg, and ondansetron 1–8 mg prevented further vomiting with little evidence of dose-responsiveness; with all regimens, absolute risk reductions compared with placebo were 20%–30%. The anti-nausea effect was less pronounced. Headache was dose-dependent. Results on propofol were contradictory. The NK(1) antagonist GR205171, isopropyl alcohol vapor, metoclopramide, domperidone, and midazolam were tested in one trial each with a limited number of patients. CONCLUSIONS: Of 100 vomiting surgical patients receiving a 5-HT(3) receptor antagonist, 20 to 30 will stop vomiting who would not have done so had they received a placebo; less will profit from the anti-nausea effect. There is a lack of evidence for a clinically relevant dose-response; minimal effective doses may be used. There is a discrepancy between the plethora of trials on prevention of PONV and the paucity of trials on treatment of established symptoms. Valid data on the therapeutic efficacy of classic antiemetics, which have been used for decades, are needed

Cell Lineages and the Logic of Proliferative Control

It is widely accepted that the growth and regeneration of tissues and organs is tightly controlled. Although experimental studies are beginning to reveal molecular mechanisms underlying such control, there is still very little known about the control strategies themselves. Here, we consider how secreted negative feedback factors (“chalones”) may be used to control the output of multistage cell lineages, as exemplified by the actions of GDF11 and activin in a self-renewing neural tissue, the mammalian olfactory epithelium (OE). We begin by specifying performance objectives—what, precisely, is being controlled, and to what degree—and go on to calculate how well different types of feedback configurations, feedback sensitivities, and tissue architectures achieve control. Ultimately, we show that many features of the OE—the number of feedback loops, the cellular processes targeted by feedback, even the location of progenitor cells within the tissue—fit with expectations for the best possible control. In so doing, we also show that certain distinctions that are commonly drawn among cells and molecules—such as whether a cell is a stem cell or transit-amplifying cell, or whether a molecule is a growth inhibitor or stimulator—may be the consequences of control, and not a reflection of intrinsic differences in cellular or molecular character