Drones and Butterflies : A Low-Cost UAV System for Rapid Detection and Identification of Unconventional Minefields

Aerially-deployed plastic landmines in post-conflict nations present unique detection and disposal challenges. Their small size, randomized distribution during deployment, and low-metal content make these mines more difficult to identify using traditional methods of electromagnetic mine detection. Perhaps the most notorious of these mines is the Sovietera PFM-1 “butterfly mine,” widely used during the decade-long Soviet-Afghan conflict between 1979 and 1989. Predominantly used by the Soviet forces to block otherwise inaccessible mountain passages, many PFM-1 minefields remain in place due to the high associated costs of access and demining. While the total number of deployed PFM-1 mines in Afghanistan is poorly documented, PFM-1 landmines make up a considerable percentage of the estimated 10 million landmines remaining in place across Afghanistan. Their detection and disposal presents a unique logistical challenge for largely the same reasons that their deployment was rationalized in inaccessible and sparsely populated areas of the country

Exosomes neutralize synaptic-plasticity-disrupting activity of Aβ assemblies in vivo

Background: Exosomes, small extracellular vesicles of endosomal origin, have been suggested to be involved in both the metabolism and aggregation of Alzheimer’s disease (AD)-associated amyloid β-protein (Aβ). Despite their ubiquitous presence and the inclusion of components which can potentially interact with Aβ, the role of exosomes in regulating synaptic dysfunction induced by Aβ has not been explored. Results: We here provide in vivo evidence that exosomes derived from N2a cells or human cerebrospinal fluid can abrogate the synaptic-plasticity-disrupting activity of both synthetic and AD brain-derived Aβ. Mechanistically, this effect involves sequestration of synaptotoxic Aβ assemblies by exosomal surface proteins such as PrPC rather than Aβ proteolysis. Conclusions: These data suggest that exosomes can counteract the inhibitory action of Aβ, which contributes to perpetual capability for synaptic plasticity

Identification of subjects with polycystic ovary syndrome using electronic health records

Background: Polycystic ovary syndrome (PCOS) is a heterogeneous disorder because of the variable criteria used for diagnosis. Therefore, International Classification of Diseases 9 (ICD-9) codes may not accurately capture the diagnostic criteria necessary for large scale PCOS identification. We hypothesized that use of electronic medical records text and data would more specifically capture PCOS subjects. Methods: Subjects with PCOS were identified in the Partners Healthcare Research Patients Data Registry by searching for the term “polycystic ovary syndrome” using natural language processing (n = 24,930). A training subset of 199 identified charts was reviewed and categorized based on likelihood of a true Rotterdam PCOS diagnosis, i.e. two out of three of the following: irregular menstrual cycles, hyperandrogenism and/or polycystic ovary morphology. Data from the history, physical exam, laboratory and radiology results were codified and extracted from notes of definite PCOS subjects. Thirty-two terms were used to build an algorithm for identifying definite PCOS cases and applied to the rest of the dataset. The positive predictive value cutoff was set at 76.8 % to maximize the number of subjects available for study. A true positive predictive value for the algorithm was calculated after review of 100 charts from subjects identified as definite PCOS cases with at least two documented Rotterdam criteria. The positive predictive value was compared to that calculated using 200 charts identified using the ICD-9 code for PCOS (256.4; n = 13,670). In addition, a cohort of previously recruited PCOS subjects was submitted for algorithm validation. Results: Chart review demonstrated that 64 % were confirmed as definitely PCOS using the algorithm, with a 9 % false positive rate. 66 % of subjects identified by ICD-9 code for PCOS could be confirmed as definitely PCOS, with an 8.5 % false positive rate. There was no significant difference in the positive predictive values using the two methods (p = 0.2). However, the number of charts that had insufficient confirmatory data was lower using the algorithm (5 % vs 11 %; p < 0.04). Of 477 subjects with PCOS recruited and examined individually and present in the database as patients, 451 were found within the algorithm dataset. Conclusions: Extraction of text parameters along with codified data improves the confidence in PCOS patient cohorts identified using the electronic medical record. However, the positive predictive value was not significantly different when using ICD-9 codes or the specific algorithm. Further studies are needed to determine the positive predictive value of the two methods in additional electronic medical record datasets. Electronic supplementary material The online version of this article (doi:10.1186/s12958-015-0115-z) contains supplementary material, which is available to authorized users

Genetic and Computational Identification of a Conserved Bacterial Metabolic Module

We have experimentally and computationally defined a set of genes that form a conserved metabolic module in the α-proteobacterium Caulobacter crescentus and used this module to illustrate a schema for the propagation of pathway-level annotation across bacterial genera. Applying comprehensive forward and reverse genetic methods and genome-wide transcriptional analysis, we (1) confirmed the presence of genes involved in catabolism of the abundant environmental sugar myo-inositol, (2) defined an operon encoding an ABC-family myo-inositol transmembrane transporter, and (3) identified a novel myo-inositol regulator protein and cis-acting regulatory motif that control expression of genes in this metabolic module. Despite being encoded from non-contiguous loci on the C. crescentus chromosome, these myo-inositol catabolic enzymes and transporter proteins form a tightly linked functional group in a computationally inferred network of protein associations. Primary sequence comparison was not sufficient to confidently extend annotation of all components of this novel metabolic module to related bacterial genera. Consequently, we implemented the Graemlin multiple-network alignment algorithm to generate cross-species predictions of genes involved in myo-inositol transport and catabolism in other α-proteobacteria. Although the chromosomal organization of genes in this functional module varied between species, the upstream regions of genes in this aligned network were enriched for the same palindromic cis-regulatory motif identified experimentally in C. crescentus. Transposon disruption of the operon encoding the computationally predicted ABC myo-inositol transporter of Sinorhizobium meliloti abolished growth on myo-inositol as the sole carbon source, confirming our cross-genera functional prediction. Thus, we have defined regulatory, transport, and catabolic genes and a cis-acting regulatory sequence that form a conserved module required for myo-inositol metabolism in select α-proteobacteria. Moreover, this study describes a forward validation of gene-network alignment, and illustrates a strategy for reliably transferring pathway-level annotation across bacterial species

NavWell: A simplified virtual-reality platform for spatial navigation and memory experiments

Being able to navigate, recall important locations, and find the way home are critical skills, essential for survival for both humans and animals. These skills can be examined in the laboratory using the Morris water maze, often considered the gold standard test of animal navigation. In this task, animals are required to locate and recall the location of an escape platform hidden in a pool filled with water. Because animals can not see the platform directly, they must use various landmarks in the environment to escape. With recent advances in technology and virtual reality (VR), many tasks originally used in the animal literature can now be translated for human studies. The virtual water maze task is no exception. However, a number of issues are associated with these mazes, including cost, lack of flexibility, and lack of standardization in terms of experimental designs and procedures. Here we present a virtual water maze system (NavWell) that is readily downloadable and free to use. The system allows for the easy design of experiments and the testing of participants on a desktop computer or fully immersive VR environment. The data from four independent experiments are presented in order to validate the software. From these experiments, a set of procedures for use with a number of well-known memory tests is suggested. This potentially can help with the standardization of navigational research and with navigational testing in the clinic or in an educational environment. Finally, we discuss the limitations of the software and plans for its development and future use

Screening pregnant women for suicidal behavior in electronic medical records: diagnostic codes vs. clinical notes processed by natural language processing

Background: We examined the comparative performance of structured, diagnostic codes vs. natural language processing (NLP) of unstructured text for screening suicidal behavior among pregnant women in electronic medical records (EMRs). Methods: Women aged 10–64 years with at least one diagnostic code related to pregnancy or delivery (N = 275,843) from Partners HealthCare were included as our “datamart.” Diagnostic codes related to suicidal behavior were applied to the datamart to screen women for suicidal behavior. Among women without any diagnostic codes related to suicidal behavior (n = 273,410), 5880 women were randomly sampled, of whom 1120 had at least one mention of terms related to suicidal behavior in clinical notes. NLP was then used to process clinical notes for the 1120 women. Chart reviews were performed for subsamples of women. Results: Using diagnostic codes, 196 pregnant women were screened positive for suicidal behavior, among whom 149 (76%) had confirmed suicidal behavior by chart review. Using NLP among those without diagnostic codes, 486 pregnant women were screened positive for suicidal behavior, among whom 146 (30%) had confirmed suicidal behavior by chart review. Conclusions: The use of NLP substantially improves the sensitivity of screening suicidal behavior in EMRs. However, the prevalence of confirmed suicidal behavior was lower among women who did not have diagnostic codes for suicidal behavior but screened positive by NLP. NLP should be used together with diagnostic codes for future EMR-based phenotyping studies for suicidal behavior. Electronic supplementary material The online version of this article (10.1186/s12911-018-0617-7) contains supplementary material, which is available to authorized users

Temporal Annotation in the Clinical Domain.

This article discusses the requirements of a formal specification for the annotation of temporal information in clinical narratives. We discuss the implementation and extension of ISO-TimeML for annotating a corpus of clinical notes, known as the THYME corpus. To reflect the information task and the heavily inference-based reasoning demands in the domain, a new annotation guideline has been developed, "the THYME Guidelines to ISO-TimeML (THYME-TimeML)". To clarify what relations merit annotation, we distinguish between linguistically-derived and inferentially-derived temporal orderings in the text. We also apply a top performing TempEval 2013 system against this new resource to measure the difficulty of adapting systems to the clinical domain. The corpus is available to the community and has been proposed for use in a SemEval 2015 task

Temporal Annotation in the Clinical Domain.

This article discusses the requirements of a formal specification for the annotation of temporal information in clinical narratives. We discuss the implementation and extension of ISO-TimeML for annotating a corpus of clinical notes, known as the THYME corpus. To reflect the information task and the heavily inference-based reasoning demands in the domain, a new annotation guideline has been developed, "the THYME Guidelines to ISO-TimeML (THYME-TimeML)". To clarify what relations merit annotation, we distinguish between linguistically-derived and inferentially-derived temporal orderings in the text. We also apply a top performing TempEval 2013 system against this new resource to measure the difficulty of adapting systems to the clinical domain. The corpus is available to the community and has been proposed for use in a SemEval 2015 task

Leveraging electronic health records data to predict multiple sclerosis disease activity

Abstract Objective No relapse risk prediction tool is currently available to guide treatment selection for multiple sclerosis (MS). Leveraging electronic health record (EHR) data readily available at the point of care, we developed a clinical tool for predicting MS relapse risk. Methods Using data from a clinic‐based research registry and linked EHR system between 2006 and 2016, we developed models predicting relapse events from the registry in a training set (n = 1435) and tested the model performance in an independent validation set of MS patients (n = 186). This iterative process identified prior 1‐year relapse history as a key predictor of future relapse but ascertaining relapse history through the labor‐intensive chart review is impractical. We pursued two‐stage algorithm development: (1) L1‐regularized logistic regression (LASSO) to phenotype past 1‐year relapse status from contemporaneous EHR data, (2) LASSO to predict future 1‐year relapse risk using imputed prior 1‐year relapse status and other algorithm‐selected features. Results The final model, comprising age, disease duration, and imputed prior 1‐year relapse history, achieved a predictive AUC and F score of 0.707 and 0.307, respectively. The performance was significantly better than the baseline model (age, sex, race/ethnicity, and disease duration) and noninferior to a model containing actual prior 1‐year relapse history. The predicted risk probability declined with disease duration and age. Conclusion Our novel machine‐learning algorithm predicts 1‐year MS relapse with accuracy comparable to other clinical prediction tools and has applicability at the point of care. This EHR‐based two‐stage approach of outcome prediction may have application to neurological disease beyond MS

Elevated International Normalized Ratio Is Associated With Ruptured Aneurysms

Background and Purpose- The effects of anticoagulation therapy and elevated international normalized ratio (INR) values on the risk of aneurysmal subarachnoid hemorrhage are unknown. We aimed to investigate the association between anticoagulation therapy, elevated INR values, and rupture of intracranial aneurysms. Methods- We conducted a case-control study of 4696 patients with 6403 intracranial aneurysms, including 1198 prospective patients, diagnosed at the Massachusetts General Hospital and the Brigham and Women's Hospital between 1990 and 2016 who were on no anticoagulant therapy or on warfarin for anticoagulation. Patients were divided into ruptured and nonruptured groups. Univariable and multivariable logistic regression analyses were performed to evaluate the association of anticoagulation therapy, INR values, and presentation with a ruptured intracranial aneurysm, taking into account the interaction between anticoagulant use and INR. Inverse probability weighting using propensity scores was used to minimize differences in baseline demographics characteristics. The marginal effects of anticoagulant use on rupture risk stratified by INR values were calculated. Results- In unweighted and weighted multivariable analyses, elevated INR values were significantly associated with rupture status among patients who were not anticoagulated (unweighted odds ratio, 22.78; 95% CI, 10.85-47.81 and weighted odds ratio, 28.16; 95% CI, 12.44-63.77). In anticoagulated patients, warfarin use interacts significantly with INR when INR ≥1.2 by decreasing the effects of INR on rupture risk. Conclusions- INR elevation is associated with intracranial aneurysm rupture, but the effects may be moderated by warfarin. INR values should, therefore, be taken into consideration when counseling patients with intracranial aneurysms