Critiquing Protein Family Classification Models Using Sufficient Input Subsets.

In many application domains, neural networks are highly accurate and have been deployed at large scale. However, users often do not have good tools for understanding how these models arrive at their predictions. This has hindered adoption in fields such as the life and medical sciences, where researchers require that models base their decisions on underlying biological phenomena rather than peculiarities of the dataset. We propose a set of methods for critiquing deep learning models and demonstrate their application for protein family classification, a task for which high-accuracy models have considerable potential impact. Our methods extend the Sufficient Input Subsets (SIS) technique, which we use to identify subsets of features in each protein sequence that are alone sufficient for classification. Our suite of tools analyzes these subsets to shed light on the decision-making criteria employed by models trained on this task. These tools show that while deep models may perform classification for biologically relevant reasons, their behavior varies considerably across the choice of network architecture and parameter initialization. While the techniques that we develop are specific to the protein sequence classification task, the approach taken generalizes to a broad set of scientific contexts in which model interpretability is essential

Give me a break! Unavoidable fatigue effects in cognitive pupillometry

Issue Online: 08 June 2023Pupillometry has a rich history in the study of perception and cognition. One perennial challenge is that the magnitude of the task-evoked pupil response diminishes over the course of an experiment, a phenomenon we refer to as a fatigue effect. Reducing fatigue effects may improve sensitivity to task effects and reduce the likelihood of confounds due to systematic physiological changes over time. In this paper, we investigated the degree to which fatigue effects could be ameliorated by experimenter intervention. In Experiment 1, we assigned participants to one of three groups—no breaks, kinetic breaks (playing with toys, but no social interaction), or chatting with a research assistant—and compared the pupil response across conditions. In Experiment 2, we additionally tested the effect of researcher observation. Only breaks including social interaction significantly reduced the fatigue of the pupil response across trials. However, in all conditions we found robust evidence for fatigue effects: that is, regardless of protocol, the task-evoked pupil response was substantially diminished (at least 60%) over the duration of the experiment. We account for the variance of fatigue effects in our pupillometry data using multiple common statistical modeling approaches (e.g., linear mixed-effects models of peak, mean, and baseline pupil diameters, as well as growth curve models of time-course data). We conclude that pupil attenuation is a predictable phenomenon that should be accommodated in our experimental designs and statistical models.Agencia Estatal de Investigación, Grant/Award Number: CEX2020-001010- S; Eusko Jaurlaritza; National Institutes of Health, Grant/ Award Number: R01 DC014281 and R01 DC019507; National Science Foundation, Grant/Award Number: DGE-174503

Examining how changes in provincial policy on vape marketing impacted the distribution of vaping advertisements near secondary schools in London, Ontario

Objectives: On January 1, 2020, the Government of Ontario passed a regulation banning vaping advertisements by retailers, apart from specialty shops. A motivation for this ban was to limit youth exposure to vaping advertisements. The primary goal of this research was to evaluate the impact of this ban on the number and density of vaping advertisements surrounding secondary schools. Additionally, we examined whether the number of vaping advertisements varied by school socio-demographic characteristics. Methods: This study used a pre-post design. Audits were conducted December 2019 (pre-ban) and again January to February 2020 (post-ban), to identify vaping advertisements within 800 m surrounding secondary schools (n = 18) in London, Ontario. Results: Prior to the ban, there were 266 vaping advertisements within 800 m of secondary schools. After the ban, this was reduced to 58, a 78.2% reduction. The mean number of vaping advertisements surrounding schools significantly decreased from 18.1 before the ban to 3.6 after the ban (p \u3c 0.001). A significant positive correlation was found, prior to the ban, between the number of vaping advertisements surrounding schools and school-level residential instability (r = 0.42, p = 0.02). After the ban, no significant correlations were found between the number of vaping advertisements and school socio-demographic characteristics. Conclusion: The provincial ban of vaping advertisements in select retail settings significantly reduced the number of vaping advertisements in the areas surrounding secondary schools in London, Ontario. The ban also reduced socio-demographic inequities in youths’ potential exposure to marketing of vaping products. Continued monitoring of the geographic accessibility and promotion of vaping products is warranted

Framing Scientific Analyses for Risk Management of Environmental Hazards by Communities: Case Studies with Seafood Safety Issues

Risk management provides a context for addressing environmental health hazards. Critical to this approach is the identification of key opportunities for participation. We applied a framework based on the National Research Council’s (NRC) analytic–deliberative risk management dialogue model that illustrates two main iterative processes: informing and framing. The informing process involves conveying information from analyses of risk issues, often scientific, to all parties so they can participate in deliberation. In the framing process, ideas and concerns from stakeholder deliberations help determine what and how scientific analyses will be carried out. There are few activities through which affected parties can convey their ideas from deliberative processes for framing scientific analyses. The absence of participation results in one-way communication. The analytic–deliberative dialogue, as envisioned by the NRC and promoted by the National Institute of Environmental Health Sciences (NIEHS), underscores the importance of two-way communication. In this article we present case studies of three groups—an Asian and Pacific Islander community coalition and two Native American Tribes—active in framing scientific analyses of health risks related to contaminated seafood. Contacts with these organizations were established or enhanced through a regional NIEHS town meeting. The reasons for concern, participation, approaches, and funding sources were different for each group. Benefits from their activities include increased community involvement and ownership, better focusing of analytical processes, and improved accuracy and appropriateness of risk management. These examples present a spectrum of options for increasing community involvement in framing analyses and highlight the need for increased support of such activities

The impact of using computer decision-support software in primary care nurse-led telephone triage:Interactional dilemmas and conversational consequences

Telephone triage represents one strategy to manage demand for face-to-face GP appointments in primary care. Although computer decision-support software (CDSS) is increasingly used by nurses to triage patients, little is understood about how interaction is organized in this setting. Specifically any interactional dilemmas this computer-mediated setting invokes; and how these may be consequential for communication with patients. Using conversation analytic methods we undertook a multi-modal analysis of 22 audio-recorded telephone triage nurse-caller interactions from one GP practice in England, including 10 video-recordings of nurses' use of CDSS during triage. We draw on Goffman's theoretical notion of participation frameworks to make sense of these interactions, presenting 'telling cases' of interactional dilemmas nurses faced in meeting patient's needs and accurately documenting the patient's condition within the CDSS. Our findings highlight troubles in the 'interactional workability' of telephone triage exposing difficulties faced in aligning the proximal and wider distal context that structures CDSS-mediated interactions. Patients present with diverse symptoms, understanding of triage consultations, and communication skills which nurses need to negotiate turn-by-turn with CDSS requirements. Nurses therefore need to have sophisticated communication, technological and clinical skills to ensure patients' presenting problems are accurately captured within the CDSS to determine safe triage outcomes. Dilemmas around how nurses manage and record information, and the issues of professional accountability that may ensue, raise questions about the impact of CDSS and its use in supporting nurses to deliver safe and effective patient care

A Functional Signature Ontology (FUSION) screen detects an AMPK inhibitor with selective toxicity toward human colon tumor cells

AMPK is a serine threonine kinase composed of a heterotrimer of a catalytic, kinase-containing α and regulatory β and γ subunits. Here we show that individual AMPK subunit expression and requirement for survival varies across colon cancer cell lines. While AMPKα1 expression is relatively consistent across colon cancer cell lines, AMPKα1 depletion does not induce cell death. Conversely, AMPKα2 is expressed at variable levels in colon cancer cells. In high expressing SW480 and moderate expressing HCT116 colon cancer cells, siRNA-mediated depletion induces cell death. These data suggest that AMPK kinase inhibition may be a useful component of future therapeutic strategies. We used Functional Signature Ontology (FUSION) to screen a natural product library to identify compounds that were inhibitors of AMPK to test its potential for detecting small molecules with preferential toxicity toward human colon tumor cells. FUSION identified 5′-hydroxy-staurosporine, which competitively inhibits AMPK. Human colon cancer cell lines are notably more sensitive to 5′-hydroxy-staurosporine than are non-transformed human colon epithelial cells. This study serves as proof-of-concept for unbiased FUSION-based detection of small molecule inhibitors of therapeutic targets and highlights its potential to identify novel compounds for cancer therapy development