Heuristics as Bayesian inference under extreme priors

Simple heuristics are often regarded as tractable decision strategies because they ignore a great deal of information in the input data. One puzzle is why heuristics can outperform full-information models, such as linear regression, which make full use of the available information. These "less-is-more" effects, in which a relatively simpler model outperforms a more complex model, are prevalent throughout cognitive science, and are frequently argued to demonstrate an inherent advantage of simplifying computation or ignoring information. In contrast, we show at the computational level (where algorithmic restrictions are set aside) that it is never optimal to discard information. Through a formal Bayesian analysis, we prove that popular heuristics, such as tallying and take-the-best, are formally equivalent to Bayesian inference under the limit of infinitely strong priors. Varying the strength of the prior yields a continuum of Bayesian models with the heuristics at one end and ordinary regression at the other. Critically, intermediate models perform better across all our simulations, suggesting that down-weighting information with the appropriate prior is preferable to entirely ignoring it. Rather than because of their simplicity, our analyses suggest heuristics perform well because they implement strong priors that approximate the actual structure of the environment. We end by considering how new heuristics could be derived by infinitely strengthening the priors of other Bayesian models. These formal results have implications for work in psychology, machine learning and economics

Evidence-Based Skin Champion Program Reduces Pressure Injuries in a Pediatric Hospital

Prevention of pressure injuries (PIs) in pediatric patients is an important nurse-sensitive quality goal. The PI rate at a large urban pediatric hospital triggered a call to action by the Chief Nursing Officer to establish a Hospital Acquired PI (HAPI) Task Force which identified the Skin Champion program as a key improvement strategy. The goals of the Skin Champion program are to lower the rate of HAPIs, empower front line care providers to implement evidence-based care bundles, achieve consistency of practice, and provide resource availability at the point of care. The implementation of the Skin Champion quality improvement program achieved an 85% reduction in severe harm and “reportable HAPI incidence, which is lower than the HAPI national average in pediatric patients (Solutions for Patient Safety, 2018), and an increase in nurse compliance with the HAPI prevention bundle. The HAPI incidence rate has remained near 0.05 per 1000 patient days

Robust priors for regularized regression

Induction benefits from useful priors. Penalized regression approaches, like ridge regression, shrink weights toward zero but zero association is usually not a sensible prior. Inspired by simple and robust decision heuristics humans use, we constructed non-zero priors for penalized regression models that provide robust and interpretable solutions across several tasks. Our approach enables estimates from a constrained model to serve as a prior for a more general model, yielding a principled way to interpolate between models of differing complexity. We successfully applied this approach to a number of decision and classification problems, as well as analyzing simulated brain imaging data. Models with robust priors had excellent worst-case performance. Solutions followed from the form of the heuristic that was used to derive the prior. These new algorithms can serve applications in data analysis and machine learning, as well as help in understanding how people transition from novice to expert performance

Regenerative medicine for childhood gastrointestinal diseases

Several paediatric gastrointestinal diseases result in life-shortening organ failure. For many of these conditions, current therapeutic options are suboptimal and may not offer a cure. Regenerative medicine is an inter-disciplinary field involving biologists, engineers, and clinicians that aims to produce cell and tissue-based therapies to overcome organ failure. Exciting advances in stem cell biology, materials science, and bioengineering bring engineered gastrointestinal cell and tissue therapies to the verge of clinical trial. In this review, we summarise the requirements for bioengineered therapies, the possible sources of the various cellular and non-cellular components, and the progress towards clinical translation of oesophageal and intestinal tissue engineering to date

Paediatric gastric organoids as a tool for disease modelling and clinical translation

Purpose: Knowledge of gastric epithelial homeostasis remains incomplete, lacking human-specific models for study. This study establishes a protocol for deriving gastric epithelial organoids from paediatric gastric biopsies, providing a platform for modelling disease and developing translational therapies. Methods: Full-thickness surgical samples and endoscopic mucosal biopsies were obtained from six patients. Gastric glands were isolated by a chemical chelation protocol and then plated in 3D culture in Matrigel® droplets in chemically defined medium. After formation, organoids were passaged by single cell dissociation or manual disaggregation. Cell composition and epithelial polarity of organoids were assessed by bright field microscopy and immunofluorescence analysis, comparing them to native paediatric gastric tissue. Results: Gastric glands were successfully isolated from all six patients who were aged 4 months to 16 years. Gastric glands from all patients sealed to form spherical gastric organoids. These organoids could be passaged by manual disaggregation or single cell dissociation, remaining proliferative up to 1 year in culture. Organoids retained normal epithelial cell polarity, with the apical surface orientated towards the central lumen. Organoids expressed markers of mature gastric epithelial cell types, except for parietal cells. Conclusion: Gastric organoids can be reliably generated from paediatric biopsies and are a representative in vitro model for studying gastric epithelium

Investigation of phase separation within the generalized Lin-Taylor model for a binary liquid mixture of large hexagonal and small triangular particles

The generalized Lin-Taylor model defined on the hexagonal lattice is used to investigate the phase separation in an asymmetric binary liquid mixture consisting of large A (hexagons) and small B (triangles) particles. By considering interaction energies between A-A and A-B pairs of particles that occupy nearest-neighbour cells of the hexagonal lattice, we have derived an exact solution for the considered model system having established a mapping correspondence with the two-dimensional Ising model on its dual triangular lattice. Altogether, six different types of coexistence curves including those with reentrant miscibility regions (i.e. closed-loop coexistence curves) were found in dependence on the relative strength between both coupling constants.Comment: 8 pages, 4 figures, presented at 7th Liblice conference on the Statistical Mechanics of Liquids to be held in Lednice on June 11-16, 200

An Evaluation of the Healthiness of the Indian Packaged Food and Beverage Supply

Availability of less-healthy packaged food and beverage products has been implicated as an important driver of obesity and diet-related disease. An increasing number of packaged foods and beverages are sold in India. Our objective was to evaluate the healthiness of packaged foods sold by India’s largest manufacturers. Healthiness was assessed using the Australian Health Star Rating (HSR) system and the World Health Organization’s European Regional Office (WHO Euro) Nutrient Profile Model. Sales-value-weighted mean healthiness and the proportions of “healthy” products (using a validated HSR cut-off of ≥3.5, and products meeting WHO Euro criteria as healthy enough to market to children) were calculated overall, by company and by food category. Nutrient information for 943 products sold by the 11 largest Indian manufacturers was obtained from nutrient labels, company websites or directly from the manufacturer. Healthiness was low overall (mean HSR 1.8 out of 5.0 stars) with a low proportion defined as “healthy” by both HSR (17%) and also by WHO Euro criteria (8%). There were marked differences in the healthiness of similar products within food categories. Substantial variation between companies (minimum sales-value-weighted mean HSR 0.5 for Company G, versus maximum HSR 3.0 for Company F) was a result of differences in the types of products sold and the nutritional composition of individual products. There are clear opportunities for India’s largest food companies to improve both the nutritional quality of individual products and to improve their product mix to include a greater proportion of healthy products

The Full Two-Loop R-parity Violating Renormalization Group Equations for All Minimal Supersymmetric Standard Model Couplings

We present the full two-loop $\beta$-functions for the minimal supersymmetric standard model couplings, extended to include R-parity violating couplings through explicit R-parity violation