Reporting Statistical Validity and Model Complexity in Machine Learning based Computational Studies

Background:: Statistical validity and model complexity are both important concepts to enhanced understanding and correctness assessment of computational models. However, information about these are often missing from publications applying machine learning. Aim: The aim of this study is to show the importance of providing details that can indicate statistical validity and complexity of models in publications. This is explored in the context of citation screening automation using machine learning techniques. Method: We built 15 Support Vector Machine (SVM) models, each developed using word2vec (average word) features --- and data for 15 review topics from the Drug Evaluation Review Program (DERP) of the Agency for Healthcare Research and Quality (AHRQ). Results: The word2vec features were found to be sufficiently linearly separable by the SVM and consequently we used the linear kernels. In 11 of the 15 models, the negative (majority) class used over 80% of its training data as support vectors (SVs) and approximately 45% of the positive training data. Conclusions: In this context, exploring the SVs revealed that the models are overly complex against ideal expectations of not more than 2%-5% (and preferably much less) of the training vectors

Non-d0d^0 Mn-driven ferroelectricity in antiferromagnetic BaMnO3_3

Using first-principles density functional theory we predict a ferroelectric ground state -- driven by off-centering of the magnetic Mn$^{4+}$ ion -- in perovskite-structure BaMnO$_3$. Our finding is surprising, since the competition between energy-lowering covalent bond formation, and energy-raising Coulombic repulsions usually only favors off-centering on the perovskite $B$-site for non-magnetic $d^0$ ions. We explain this tendency for ferroelectric off-centering by analyzing the changes in electronic structure between the centrosymmetric and polar states, and by calculating the Born effective charges; we find anomalously large values for Mn and O consistent with our calculated polarization of 12.8 $\mu$C/cm$^2$. Finally, we suggest possible routes by which the perovskite phase may be stabilized over the usual hexagonal phase, to enable a practical realization of a single-phase multiferroic.Comment: 6 pages, 3 figure

The TREC 2004 genomics track categorization task: classifying full text biomedical documents

BACKGROUND: The TREC 2004 Genomics Track focused on applying information retrieval and text mining techniques to improve the use of genomic information in biomedicine. The Genomics Track consisted of two main tasks, ad hoc retrieval and document categorization. In this paper, we describe the categorization task, which focused on the classification of full-text documents, simulating the task of curators of the Mouse Genome Informatics (MGI) system and consisting of three subtasks. One subtask of the categorization task required the triage of articles likely to have experimental evidence warranting the assignment of GO terms, while the other two subtasks were concerned with the assignment of the three top-level GO categories to each paper containing evidence for these categories. RESULTS: The track had 33 participating groups. The mean and maximum utility measure for the triage subtask was 0.3303, with a top score of 0.6512. No system was able to substantially improve results over simply using the MeSH term Mice. Analysis of significant feature overlap between the training and test sets was found to be less than expected. Sample coverage of GO terms assigned to papers in the collection was very sparse. Determining papers containing GO term evidence will likely need to be treated as separate tasks for each concept represented in GO, and therefore require much denser sampling than was available in the data sets. The annotation subtask had a mean F-measure of 0.3824, with a top score of 0.5611. The mean F-measure for the annotation plus evidence codes subtask was 0.3676, with a top score of 0.4224. Gene name recognition was found to be of benefit for this task. CONCLUSION: Automated classification of documents for GO annotation is a challenging task, as was the automated extraction of GO code hierarchies and evidence codes. However, automating these tasks would provide substantial benefit to biomedical curation, and therefore work in this area must continue. Additional experience will allow comparison and further analysis about which algorithmic features are most useful in biomedical document classification, and better understanding of the task characteristics that make automated classification feasible and useful for biomedical document curation. The TREC Genomics Track will be continuing in 2005 focusing on a wider range of triage tasks and improving results from 2004

Asymmetric Dark Matter from a GeV Hidden Sector

Asymmetric Dark Matter (ADM) models relate the dark matter density to the baryon asymmetry, so that a natural mass scale for ADM is around a few GeV. In existing models of ADM, this mass scale is unexplained; here we generate this GeV scale for dark matter (DM) from the weak scale via gauge kinetic mixing with a new Abelian dark force. In addition, this dark sector provides an efficient mechanism for suppressing the symmetric abundance of DM through annihilations to the dark photon. We augment this sector with a higher dimensional operator responsible for communicating the baryon asymmetry to the dark sector. Our framework also provides DM candidate for gauge mediation models. It results in a direct detection cross section of interest for current experiments: sigma less than or similar to 10^{-42} cm^2 for DM masses in the range 1 - 15 GeV.Comment: 21 pages, 4 figure

Bayesian Characterization of Main-Sequence Binaries in the Old Open Cluster NGC 188

The binary fractions of open and globular clusters yield powerful constraints on their dynamical state and evolutionary history. We apply publicly available Bayesian analysis tools to a UBV RIJHKS photometric catalog of the open cluster NGC 188 to detect and characterize photometric binaries along the cluster main sequence. This technique has the advantage of self-consistently handling photometric errors, missing data in various bandpasses, and star-by-star prior constraints on cluster membership. Simulations are used to verify uncertainties and quantify selection biases in our analysis, illustrating that among binaries with mass ratios \u3e0.5, we recover the binary fraction to better than 7% in the mean, with no significant dependence on binary fraction and a mild dependence on assumed mass-ratio distribution. Using our photometric catalog, we recover the majority (65% ± 11%) of spectroscopically identified main-sequence binaries, including eight of the nine with spectroscopically measured mass ratios. Accounting for incompleteness and systematics, we derive a mass-ratio distribution that rises toward lower mass ratios (within our q \u3e 0.5 analysis domain). We observe a raw binary fraction for solar-type main-sequence stars with mass ratios q \u3e 0.5 of 42% ± 4%, independent of the assumed mass-ratio distribution to within its uncertainties, consistent with literature values for old open clusters but significantly higher than the field solar-type binary fraction. We confirm that the binaries identified by our method are more concentrated than single stars, in agreement with previous studies, and we demonstrate that the binary nature of those candidates that remain unidentified spectroscopically is strongly supported by photometry from Gaia DR2

The Signature Center Initiative for the Cure of Glioblastoma

poster abstractGlioblastoma multiforme (GBM, World Health Organization/WHO grade IV) is the most common form of brain cancer in the central nervous system. Although conventional treatment-surgery, radiation, and temozolomide-is somewhat effective in adults, overall survival is still < 15 months. In pediatric patients, morbidity due to GBM is the highest among all pediatric cancers. In the context of brain cancers, new and existing therapeutics typically fail due to heterogeneity of genetic mutations within tumors, and because biologically effective doses of drug cannot be delivered to the primary site and invasive perimeter of the tumor due to the blood brain barrier. The Signature Center Initiative to Cure GBM is a funding mechanism that supports a research portal to foster investigations of the Brain Tumor Working Group for development of effective treatments for the eradication of GBM. The overall mission of the Signature Center Initiative is to: 1. Interrogate the molecular mechanisms of GBM biology and develop interventions that result in improved duration and quality of life for our patients. 2. Stimulate consistent and productive exchange of ideas between clinicians and basic scientists while employing bench-to-bedside and bedside-to-bench strategies to generate and prioritize scientific questions. 3. Provide infrastructure and mentorship needed to successfully compete for external funding. 4. Engage the community through patient advocacy to positively impact brain cancer patient outcomes and enhance philanthropic initiatives. The Brain Tumor Working Group brings together scientists committed to engaging in a team-based approach to study GBM biology. Infrastructure required to advance in vivo humanized intracranial tumor models, drug delivery, target validation, and development of new therapeutic strategies are in place. Additionally a patient sample pipeline to obtain, analyze, and distribute primary patient GBM specimens from the operating room to the research laboratory has been established. In year one of funding, over $70,000 in pilot project funding derived from the Signature Center Initiative and private donations has been distributed to the membership. The Brain Tumor Working Group meets in both small and large group formats to strategize experimental design and grant submissions. A network of basic scientists and clinicians has been developed that provides an effective forum for addressing clinically relevant questions related to GBM. A team-based approach, scientific expertise, and continued development of infrastructure provide our membership with a critical foundation to obtain new knowledge related to understanding how GBM cells evade therapy. In the future, this information can be applied to development of effective treatments that will cure GBM

Intraoperative assessment of tumor margins during glioma resection by desorption electrospray ionization-mass spectrometry

Gliomas infiltrate into surrounding healthy brain tissue. Microsurgical resection aims for maximal tumor resection while minimizing morbidity. Surgical margins are defined based on the surgeon’s experience, visual observation, and neuronavigation. Surgical margin assessment is rarely undertaken intraoperatively due to time constraints and unreliability of such evaluation. Routine, pathologic intraoperative examination provides no molecular information. Molecular measurements using mass spectrometry can be made rapidly on tissue during surgery to identify tissue types, estimate tumor infiltration, and recognize the presence of prognostic mutations by monitoring oncometabolites and phospholipids. This intraoperative study demonstrates the power of mass spectrometry in assessing diagnostic and prognostic information on discrete surgeon-defined points along the resection margins to improve tumor resection, even in regions without MRI contrast enhancement., Intraoperative desorption electrospray ionization-mass spectrometry (DESI-MS) is used to characterize tissue smears by comparison with a library of DESI mass spectra of pathologically determined tissue types. Measurements are performed in the operating room within 3 min. These mass spectra provide direct information on tumor infiltration into white or gray brain matter based on N-acetylaspartate (NAA) and on membrane-derived complex lipids. The mass spectra also indicate the isocitrate dehydrogenase mutation status of the tumor via detection of 2-hydroxyglutarate, currently assessed postoperatively on biopsied tissue using immunohistochemistry. Intraoperative DESI-MS measurements made at surgeon-defined positions enable assessment of relevant disease state of tissue within the tumor mass and examination of the resection cavity walls for residual tumor. Results for 73 biopsies from 10 surgical resection cases show that DESI-MS allows detection of glioma and estimation of high tumor cell percentage (TCP) at surgical margins with 93% sensitivity and 83% specificity. TCP measurements from NAA are corroborated by indirect measurements based on lipid profiles. Notably, high percentages (>50%) of unresected tumor were found in one-half of the margin biopsy smears, even in cases where postoperative MRI suggested gross total tumor resection. Unresected tumor causes recurrence and malignant progression, as observed within a year in one case examined in this study. These results corroborate the utility of DESI-MS in assessing surgical margins for maximal safe tumor resection. Intraoperative DESI-MS analysis of tissue smears, ex vivo, can be inserted into the current surgical workflow with no alterations. The data underscore the complexity of glioma infiltration

External cortical landmarks for localization of the hippocampus: Application for temporal lobectomy and amygdalohippocampectomy

Background: Accessing the hippocampus for amygdalohippocampectomy and minimally invasive procedures, such as depth electrode placement, require an accurate knowledge regarding the location of the hippocampus. Methods: The authors removed 10 human cadaveric brains from the cranium and observed the relationships between the lateral temporal neocortex and the underlying hippocampus. They then measured the distance between the hippocampus and superficial landmarks. The authors also validated their study using magnetic resonance imaging (MRI) scans of 10 patients suffering from medial temporal lobe sclerosis where the distance from the hippocampal head to the anterior temporal tip was measured. Results: In general, the length of the hippocampus was along the inferior temporal sulcus and inferior aspect of the middle temporal gyrus. Although the hippocampus tended to be more superiorly located in female specimens and on the left side, this did not reach statistical significance. The length of the hippocampus tended to be shorter in females, but this too failed to reach statistical significance. The mean distance from the anterior temporal tip to the hippocampal head was identical in the cadavers and MRIs of patients with medial temporal lobe sclerosis. Conclusions: Additional landmarks for localizing the underlying hippocampus may be helpful in temporal lobe surgery. Based on this study, there are relatively constant anatomical landmarks between the hippocampus and overlying temporal cortex. Such landmarks may be used in localizing the hippocampus during amygdalohippocampectomy and depth electrode implantation in verifying the accuracy of image-guided methods and as adjuvant methodologies when these latter technologies are not used or are unavailable