Rethinking PICO in the Machine Learning Era: ML-PICO

Background  Machine learning (ML) has captured the attention of many clinicians who may not have formal training in this area but are otherwise increasingly exposed to ML literature that may be relevant to their clinical specialties. ML papers that follow an outcomes-based research format can be assessed using clinical research appraisal frameworks such as PICO (Population, Intervention, Comparison, Outcome). However, the PICO frameworks strain when applied to ML papers that create new ML models, which are akin to diagnostic tests. There is a need for a new framework to help assess such papers. Objective  We propose a new framework to help clinicians systematically read and evaluate medical ML papers whose aim is to create a new ML model: ML-PICO (Machine Learning, Population, Identification, Crosscheck, Outcomes). We describe how the ML-PICO framework can be applied toward appraising literature describing ML models for health care. Conclusion  The relevance of ML to practitioners of clinical medicine is steadily increasing with a growing body of literature. Therefore, it is increasingly important for clinicians to be familiar with how to assess and best utilize these tools. In this paper we have described a practical framework on how to read ML papers that create a new ML model (or diagnostic test): ML-PICO. We hope that this can be used by clinicians to better evaluate the quality and utility of ML papers.     

The relationship between childhood maltreatment and psychopathology in adults undergoing bariatric surgery

Background

A history of childhood maltreatment and psychopathology are common in adults with obesity.

Assessment of toxicity using dehydrogenases activity and mathematical modeling

Dehydrogenase activity is frequently used to assess the general condition of microorganisms in soil and activated sludge. Many studies have investigated the inhibition of dehydrogenase activity by various compounds, including heavy metal ions. However, the time after which the measurements are carried out is often chosen arbitrarily. Thus, it can be difficult to estimate how the toxic effects of compounds vary during the reaction and when the maximum of the effect would be reached. Hence, the aim of this study was to create simple and useful mathematical model describing changes in dehydrogenase activity during exposure to substances that inactivate enzymes. Our model is based on the Lagergrens pseudo-first-order equation, the rate of chemical reactions, enzyme activity, and inactivation and was created to describe short-term changes in dehydrogenase activity. The main assumption of our model is that toxic substances cause irreversible inactivation of enzyme units. The model is able to predict the maximum direct toxic effect (MDTE) and the time to reach this maximum (T_MDTE). In order to validate our model, we present two examples: inactivation of dehydrogenase in microorganisms in soil and activated sludge. The model was applied successfully for cadmium and copper ions. Our results indicate that the predicted MDTE and T_MDTE are more appropriate than EC₅₀ and IC₅₀ for toxicity assessments, except for long exposure times.     

Adolescent neighborhood quality predicts adult dACC response to social exclusion

Neuroimaging studies using the social-exclusion paradigm Cyberball indicate increased dorsal anterior cingulate cortex (dACC) and right insula activity as a function of exclusion. However, comparatively less work has been done on how social status factors may moderate this finding. This study used the Cyberball paradigm with 85 (45 females) socio-economically diverse participants from a larger longitudinal sample. We tested whether neighborhood quality during adolescence would predict subsequent neural responding to social exclusion in young adulthood. Given previous behavioral studies indicating greater social vigilance and negative evaluation as a function of lower status, we expected that lower adolescent neighborhood quality would predict greater dACC activity during exclusion at young adulthood. Our findings indicate that young adults who lived in low-quality neighborhoods in adolescence showed greater dACC activity to social exclusion than those who lived in higher quality neighborhoods. Lower neighborhood quality also predicted greater prefrontal activation in the superior frontal gyrus, dorsal medial prefrontal cortex and the middle frontal gyrus, possibly indicating greater regulatory effort. Finally, this effect was not driven by subsequent ratings of distress during exclusion. In sum, adolescent neighborhood quality appears to potentiate neural responses to social exclusion in young adulthood, effects that are independent of felt distress.     

Natural Variant of Collagen-Like Protein A in Serotype M3 Group A Streptococcus Increases Adherence and Decreases Invasive Potential

Group A Streptococcus (GAS) predominantly exists as a colonizer of the human oropharynx that occasionally breaches epithelial barriers to cause invasive diseases. Despite the frequency of GAS carriage, few investigations into the contributory molecular mechanisms exist. To this end, we identified a naturally occurring polymorphism in the gene encoding the streptococcal collagen-like protein A (SclA) in GAS carrier strains. All previously sequenced invasive serotype M3 GAS possess a premature stop codon in the sclA gene truncating the protein. The carrier polymorphism is predicted to restore SclA function and was infrequently identified by targeted DNA sequencing in invasive strains of the same serotype. We demonstrate that a strain with the carrier sclA allele expressed a full-length SclA protein, while the strain with the invasive sclA allele expressed a truncated variant. An isoallelic mutant invasive strain with the carrier sclA allele exhibited decreased virulence in a mouse model of invasive disease and decreased multiplication in human blood. Further, the isoallelic invasive strain with the carrier sclA allele persisted in the mouse nasopharynx and had increased adherence to cultured epithelial cells. Repair of the premature stop codon in the invasive sclA allele restored the ability to bind the extracellular matrix proteins laminin and cellular fibronectin. These data demonstrate that a mutation in GAS carrier strains increases adherence and decreases virulence and suggest selection against increased adherence in GAS invasive isolates.