Development of LactaPedia: A lactation glossary for science and medicine

During the last decade, there have been several publications highlighting the need for consistent terminology in breastfeeding research. Standard terms and definitions are essential for the comparison and interpretation of scientific studies that, in turn, support evidence‐based education, consistency of health care, and breastfeeding policy. Inconsistent advice is commonly reported by mothers to contribute to early weaning. A standard language is the fundamental starting point required for the provision of consistent advice. LactaPedia ( www.lactapedia.com ) is a comprehensive lactation glossary of over 500 terms and definitions created during the development of LactaMap ( www.lactamap.com ), an online lactation care support system. This paper describes the development of LactaPedia, a website that is accessible free of charge to anyone with access to the Internet. Multiple methodological frameworks were incorporated in LactaPedia's development in order to meet the needs of a glossary to support both consistent health care and scientific research. The resulting LactaPedia methodology is a six‐stage process that was developed inductively and includes framework to guide vetting and extension of its content using public feedback via discussion forums. The discussion forums support ongoing usability and refinement of the glossary. The development of LactaPedia provides a fundamental first step towards improving breastfeeding outcomes that are currently well below World Health Organisation recommendations globally.     

Automated classification of depression from structural brain measures across two independent community‐based cohorts

Major depressive disorder (MDD) has been the subject of many neuroimaging case–control classification studies. Although some studies report accuracies ≥80%, most have investigated relatively small samples of clinically‐ascertained, currently symptomatic cases, and did not attempt replication in larger samples. We here first aimed to replicate previously reported classification accuracies in a small, well‐phenotyped community‐based group of current MDD cases with clinical interview‐based diagnoses (from STratifying Resilience and Depression Longitudinally cohort, ‘STRADL’). We performed a set of exploratory predictive classification analyses with measures related to brain morphometry and white matter integrity. We applied three classifier types—SVM, penalised logistic regression or decision tree—either with or without optimisation, and with or without feature selection. We then determined whether similar accuracies could be replicated in a larger independent population‐based sample with self‐reported current depression (UK Biobank cohort). Additional analyses extended to lifetime MDD diagnoses—remitted MDD in STRADL, and lifetime‐experienced MDD in UK Biobank. The highest cross‐validation accuracy (75%) was achieved in the initial current MDD sample with a decision tree classifier and cortical surface area features. The most frequently selected decision tree split variables included surface areas of bilateral caudal anterior cingulate, left lingual gyrus, left superior frontal, right precentral and paracentral regions. High accuracy was not achieved in the larger samples with self‐reported current depression (53.73%), with remitted MDD (57.48%), or with lifetime‐experienced MDD (52.68–60.29%). Our results indicate that high predictive classification accuracies may not immediately translate to larger samples with broader criteria for depression, and may not be robust across different classification approaches.     

Incorporating Informatics for Integrating Biology and the Bedside (i2b2) into Predoctoral Trainee Curriculum to Evaluate Student‐Generated Hypotheses

As part of the Clinical and Translational Science Institute predoctoral TL1 training program at the Pennsylvania State University, a multidisciplinary team of predoctoral trainees representing the Chemistry, Neurosurgery, Nutritional Sciences, and Public Health Sciences departments were introduced to the NIH‐sponsored Informatics for Integrating Biology and the Bedside (i2b2) database to test the following student‐generated hypothesis: children with iron deficiency anemia (IDA) are at increased risk of attention deficit‐hyperactivity disorder (ADHD). Children aged 4–12 and 4–17 years were categorized into IDA and control groups. De‐identified medical records from the Penn State Milton S. Hershey Medical Center (HMC) and the Virginia Commonwealth University Medical Center (VCUMC) were used for the analysis. Overall, ADHD prevalence at each institution was lower than 2011 state estimates. There was a significant association between IDA and ADHD in the 4–17‐year‐old age group for all children (OR: 1.902 [95% CI: 1.363–2.656]), Caucasian children (OR: 1.802 [95% CI: 1.133–2.864]), and African American children (OR: 1.865 [95% CI: 1.152–3.021]). Clinical and Translational Science Award (CTSA) infrastructure is particularly useful for trainees to answer de novo scientific questions with minimal additional training and technical expertise. Moreover, projects can be expanded by collaborating within the CTSA network.     

Grading Facial Nerve Function Following Combined Static and Mimetic Surgical Techniques

Objective To present a grading scale to assess the functional recovery of the facial nerve in patients who have undergone mimetic and static surgical techniques for facial reanimation. Study design This is a proposed new facial nerve grading system that will be demonstrated with specific case presentations. All patients underwent a variety of neural grafting, microvascular free-flap reconstruction, or surgical static procedures. Results The proposed facial nerve grading scale is one that has not been described previously in the literature and is applicable to a unique patient population. Its ease of use in this patient population will allow otolaryngologists to assess facial recovery accurately and quickly in cases where the facial nerve is not anatomically intact. Conclusion The proposed facial recovery grading scale provides an efficient means of grading facial recovery for a unique group of patients who previously could not be followed. The proposed scale is practical and easy to use in a clinical setting.     

Functionally distinct amygdala subregions identified using DTI and high-resolution fMRI

Although the amygdala is often directly linked with fear and emotion, amygdala neurons are activated by a wide variety of emotional and non-emotional stimuli. Different subregions within the amygdala may be engaged preferentially by different aspects of emotional and non-emotional tasks. To test this hypothesis, we measured and compared the effects of novelty and fear on amygdala activity. We used high-resolution blood oxygenation level-dependent (BOLD) imaging and streamline tractography to subdivide the amygdala into three distinct functional subunits. We identified a laterobasal subregion connected with the visual cortex that responds generally to visual stimuli, a non-projecting region that responds to salient visual stimuli, and a centromedial subregion connected with the diencephalon that responds only when a visual stimulus predicts an aversive outcome. We provide anatomical and functional support for a model of amygdala function where information enters through the laterobasal subregion, is processed by intrinsic circuits in the interspersed tissue, and is then passed to the centromedial subregion, where activation leads to behavioral output.