Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Aberrant Cortical Activity in Multiple GCaMP6-Expressing Transgenic Mouse Lines

Transgenic mouse lines are invaluable tools for neuroscience but, as with any technique, care must be taken to ensure that the tool itself does not unduly affect the system under study. Here we report aberrant electrical activity, similar to interictal spikes, and accompanying fluorescence events in some genotypes of transgenic mice expressing GCaMP6 genetically encoded calcium sensors. These epileptiform events have been observed particularly, but not exclusively, in mice with Emx1-Cre and Ai93 transgenes, of either sex, across multiple laboratories. The events occur at >0.1 Hz, are very large in amplitude (>1.0 mV local field potentials, >10% df/f widefield imaging signals), and typically cover large regions of cortex. Many properties of neuronal responses and behavior seem normal despite these events, although rare subjects exhibit overt generalized seizures. The underlying mechanisms of this phenomenon remain unclear, but we speculate about possible causes on the basis of diverse observations. We encourage researchers to be aware of these activity patterns while interpreting neuronal recordings from affected mouse lines and when considering which lines to study

Huntingtin mediates dendritic transport of β-actin mRNA in rat neurons

Transport of mRNAs to diverse neuronal locations via RNA granules serves an important function in regulating protein synthesis within restricted sub-cellular domains. We recently detected the Huntington's disease protein huntingtin (Htt) in dendritic RNA granules; however, the functional significance of this localization is not known. Here we report that Htt and the huntingtin-associated protein 1 (HAP1) are co-localized with the microtubule motor proteins, the KIF5A kinesin and dynein, during dendritic transport of β-actin mRNA. Live cell imaging demonstrated that β-actin mRNA is associated with Htt, HAP1, and dynein intermediate chain in cultured neurons. Reduction in the levels of Htt, HAP1, KIF5A, and dynein heavy chain by lentiviral-based shRNAs resulted in a reduction in the transport of β-actin mRNA. These findings support a role for Htt in participating in the mRNA transport machinery that also contains HAP1, KIF5A, and dynein

RNA localization in neurite morphogenesis and synaptic regulation: current evidence and novel approaches

It is now generally accepted that RNA localization in the central nervous system conveys important roles both during development and in the adult brain. Of special interest is protein synthesis located at the synapse, as this potentially confers selective synaptic modification and has been implicated in the establishment of memories. However, the underlying molecular events are largely unknown. In this review, we will first discuss novel findings that highlight the role of RNA localization in neurons. We will focus on the role of RNA localization in neurotrophin signaling, axon outgrowth, dendrite and dendritic spine morphogenesis as well as in synaptic plasticity. Second, we will briefly present recent work on the role of microRNAs in translational control in dendrites and its implications for learning and memory. Finally, we discuss recent approaches to visualize RNAs in living cells and their employment for studying RNA trafficking in neurons

Illuminating the life of GPCRs

The investigation of biological systems highly depends on the possibilities that allow scientists to visualize and quantify biomolecules and their related activities in real-time and non-invasively. G-protein coupled receptors represent a family of very dynamic and highly regulated transmembrane proteins that are involved in various important physiological processes. Since their localization is not confined to the cell surface they have been a very attractive "moving target" and the understanding of their intracellular pathways as well as the identified protein-protein-interactions has had implications for therapeutic interventions. Recent and ongoing advances in both the establishment of a variety of labeling methods and the improvement of measuring and analyzing instrumentation, have made fluorescence techniques to an indispensable tool for GPCR imaging. The illumination of their complex life cycle, which includes receptor biosynthesis, membrane targeting, ligand binding, signaling, internalization, recycling and degradation, will provide new insights into the relationship between spatial receptor distribution and function. This review covers the existing technologies to track GPCRs in living cells. Fluorescent ligands, antibodies, auto-fluorescent proteins as well as the evolving technologies for chemical labeling with peptide- and protein-tags are described and their major applications concerning the GPCR life cycle are presented

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research