Automatic data processing

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Background-Cognitive and language impairments constitute the majority of disabilities observed in preterm infants. It remains unclear if diffuse excessive high signal intensity (DEHSI) on MRI at term represents delayed white matter maturation or pathology. Methods-We hypothesized that diffusion tensor imaging-based objectively quantified DEHSI measures at term will be strong predictors of cognitive and language development at 2 years in a cohort of 41 extremely low birth weight (ELBW; ≤1000g) infants. Using an automated probabilistic atlas, mean diffusivity maps were used to objectively segment and quantify DEHSI volume and mean, axial, and radial diffusivity measures. Standardized neurodevelopment was assessed at 2 years of age using the Bayley Scales of Infant Development, third edition. Results-Thirty-six of the 41 infants (88%) had complete developmental data at follow-up. Objectively quantified DEHSI volume correlated significantly with cognitive and language scores at 2 years (P<0.001 for both). The sum values of the three diffusivity measures in detected DEHSI regions also correlated significantly with the Bayley scores (R 2 34.7%; P<0.001 for each). Infants in the highest quartile for DEHSI volumes had scores between 19-24 points lower than infants in the lowest quartile (P<0.01). When diagnosed subjectively by neuroradiologists however, Bayley scores were not significantly lower in infants with extensive DEHSI. Conclusions-These findings lend further evidence that DEHSI is pathologic and that objectively quantified diffusion-based DEHSI volume at term is associated with cognitive and language impairments. Our approach could be utilized for risk stratification and early intervention for such high-risk extremely preterm infants.

Signatures of Bovine Spongiform Encephalopathy (BSE) have been identified in serum by means of ''Diagnostic Pattern Recognition (DPR)''. For DPR-analysis, mid-infrared spectroscopy of dried films of 641 serum samples was performed using disposable silicon sample carriers and a semi-automated DPR research system operating at room temperature. The combination of four mathematical classification approaches (principal component analysis plus linear discriminant analysis, robust linear discriminant analysis, artificial neural network, support vector machine) allowed for a reliable assignment of spectra to the class ''BSEpositive'' or ''BSE-negative''. An independent, blinded validation study was carried out on a second DPR research system at the Veterinary Laboratory Agency, Weybridge, UK. Out of 84 serum samples originating from terminally-ill, BSE-positive cattle, 78 were classified correctly. Similarly, 73 out of 76 BSE-negative samples were correctly identified by DPR such that, numerically, an accuracy of 94.4 % can be calculated. At a confidence level of 0.95 (a ~0.05) these results correspond to a sensitivity w 85% and a specificity w 90%. Identical class assignment by all four classifiers occurred in 75% of the cases while ambiguous results were obtained in only 8 of the 160 cases. With an area under the ROC (receiver operating charateristics) curve of 0.991, DPR may potentially supply a valuable surrogate marker for BSE even in cases in which a deliberate bias towards improved sensitivity or specificity is desired. To the best of our knowledge, DPR is the first andup to now-only method which has demonstrated its capability of detecting BSE-related signatures in serum.

The emergence of efficient fragmentation methods such as electron capture dissociation (ECD) or electron transfer dissociation (ETD) provide the opportunity for detailed structural characterization of heavily covalently modified large peptides and small proteins such as intact histones. Even with effective gas phase ion isolation so that a single molecular precursor ion is selected, the MS/MS spectrum of a heavily modified peptide may reveal the presence of a mixture of peptides with the same amino acid sequence and the same total number of PTM moieties (same PTM composition) but having different PTM configurations or site specific occupancy isoforms. Currently available data analysis methods depend on a deisotoping procedure, which becomes less effective when spectra (fragmentation patterns) contain many overlapping isotopic distributions. Peptide database search engines can only identify the most abundant PTM configuration (PTM arrangement on different residues) in such mixtures. In order to identify all the PTM configurations present in these mixtures and to estimate their relative abundances, we have extended our fragment assignment by visual assistance (FAVA) program to search for ions representing all possible configurations, subjected to the total PTM composition constraint. This results in the identification of PTM configurations supported by unique fragment ions, and their relative abundances are estimated by use of a non-negative least square procedure.

The U.S. Food, Drug, and Cosmetic Act prohibits the distribution of food that is adulterated, and the regulatory mission of the U.S. Food and Drug Administration (FDA) is to enforce this Act. FDA field laboratories have identified the 22 most common pests that contribute to the spread of foodborne disease (the “Dirty 22”). The current method of detecting filth and extraneous material (tails, legs, carcasses, etc.) is visual inspection using microscopy. Because microscopy can be time-consuming and may yield inaccurate and/or nonspecific results due to lack of expertise, an alternative method of detecting these adulterants is needed. In this study, we sequenced DNA from the 5′ region of the cytochrome oxidase I gene of these 22 common pests that contribute to the spread of foodborne pathogens. Here, we describe the generation of DNA barcodes for all 22 species. To date, this is the first attempt to develop a sequence-based regulatory database and systematic primer strategy to identify...

Background: Forensic odontology has evolved with the evolution of mankind. Since ages it has been of our interest to identify the dead. Because of events beyond our control many human beings may not die a natural death or in familiar surroundings. The task of identifying these individuals is of paramount importance in forensic odontology. Method: A Quick response code of minimum dimension was customized and incorporated into e max lithium disilicate restorations. Restorations are fabricated in such a way that it can scanned using mobile software and displays aadhar number of patient, which ultimately helps in forensic identification. Result: This coded prosthesis helps in the identification of individuals. Conclusion: Code used in present study was readable in most of the ceramic restorations and maintains its sustainability in all the conditions under which it was tested.

Most tools developed to visualize hierarchically clustered heatmaps generate static images. Clustergrammer is a web-based visualization tool with interactive features such as: zooming, panning, filtering, reordering, sharing, performing enrichment analysis, and providing dynamic gene annotations. Clustergrammer can be used to generate shareable interactive visualizations by uploading a data table to a web-site, or by embedding Clustergrammer in Jupyter Notebooks. The Clustergrammer core libraries can also be used as a toolkit by developers to generate visualizations within their own applications. Clustergrammer is demonstrated using gene expression data from the cancer cell line encyclopedia (CCLE), original post-translational modification data collected from lung cancer cells lines by a mass spectrometry approach, and original cytometry by time of flight (CyTOF) single-cell proteomics data from blood. Clustergrammer enables producing interactive web based visualizations for the ana...

BackgroundThis study describes the prevalence, associated anomalies, and demographic characteristics of cases of multiple congenital anomalies (MCA) in 19 population‐based European registries (EUROCAT) covering 959,446 births in 2004 and 2010.MethodsEUROCAT implemented a computer algorithm for classification of congenital anomaly cases followed by manual review of potential MCA cases by geneticists. MCA cases are defined as cases with two or more major anomalies of different organ systems, excluding sequences, chromosomal and monogenic syndromes.ResultsThe combination of an epidemiological and clinical approach for classification of cases has improved the quality and accuracy of the MCA data. Total prevalence of MCA cases was 15.8 per 10,000 births. Fetal deaths and termination of pregnancy were significantly more frequent in MCA cases compared with isolated cases (p &lt; 0.001) and MCA cases were more frequently prenatally diagnosed (p &lt; 0.001). Live born infants with MCA were m...

Different problems of generalization of outlier rejection exist depending of the context. In this study we firstly define three different problems depending of the outlier availability during the learning phase of the classifier. Then we propose different solutions to reject outliers with two main strategies: add a rejection class to the classifier or delimit its knowledge to better reject what it has not learned. These solutions are compared with ROC curves to recognize handwritten digits and reject handwritten characters. We show that delimiting knowledge of the classifier is important and that using only a partial subset of outliers do not perform a good reject option.

In this paper, the acoustic-phonetic characteristics of American English stop consonants are investigated. Features studied in the literature are evaluated for their information content and new features are proposed. A statistically guided, knowledge-based, acoustic-phonetic system for the automatic classification of stops, in speaker independent continuous speech, is proposed. The system uses a new auditory-based front-end processing and incorporates new algorithms for the extraction and manipulation of the acoustic-phonetic features that proved to be rich in their information content. Recognition experiments are performed using hard decision algorithms on stops extracted from the TIMIT database continuous speech of 60 speakers (not used in the design process) from seven different dialects of American English. An accuracy of 96% is obtained for voicing detection, 90% for place articulation detection and 86% for the overall classification of stops.

A central question in the study of LTP has been to determine what role it plays in memory formation and storage. One valuable form of learning for addressing this issue is associative fear conditioning. In this paradigm an animal learns to associate a tone and shock, such that subsequent presentation of a tone evokes a fear response (freezing behavior). Recent studies indicate that overlapping cellular processes underlie fear conditioning and LTP. The fear response has generally been scored manually which is both labor-intensive and subject to potential artifacts such as inconsistent or biased results. Here we describe a simple automated method that provides unbiased and rapid analysis of animal motion. We show that measured motion, in units termed significant motion pixels (SMPs), is both linear and robust over a wide range of animal speeds and detection thresholds and scores freezing in a quantitatively similar manner to trained human observers. By comparing the frequency distribution of motion during baseline periods and to the response to fox urine (which causes unconditioned fear), we suggest that freezing and non-freezing are distinct behaviors. Finally, we show how this algorithm can be applied to a fear conditioning paradigm yielding information on long and short-term associative memory as well as habituation. This automated analysis of fear conditioning will permit a more rapid and accurate assessment of the role of LTP in memory.

A central question in the study of LTP has been to determine what role it plays in memory formation and storage. One valuable form of learning for addressing this issue is associative fear conditioning. In this paradigm an animal learns to associate a tone and shock, such that subsequent presentation of a tone evokes a fear response (freezing behavior). Recent studies indicate that overlapping cellular processes underlie fear conditioning and LTP. The fear response has generally been scored manually which is both labor-intensive and subject to potential artifacts such as inconsistent or biased results. Here we describe a simple automated method that provides unbiased and rapid analysis of animal motion. We show that measured motion, in units termed significant motion pixels (SMPs), is both linear and robust over a wide range of animal speeds and detection thresholds and scores freezing in a quantitatively similar manner to trained human observers. By comparing the frequency distribution of motion during baseline periods and to the response to fox urine (which causes unconditioned fear), we suggest that freezing and non-freezing are distinct behaviors. Finally, we show how this algorithm can be applied to a fear conditioning paradigm yielding information on long and short-term associative memory as well as habituation. This automated analysis of fear conditioning will permit a more rapid and accurate assessment of the role of LTP in memory.

By facilitating bioliteracy, DNA barcoding has the potential to improve the way the world relates to wild biodiversity. Here we describe the early stages of the use of cox1 barcoding to supplement and strengthen the taxonomic platform underpinning the inventory of thousands of sympatric species of caterpillars in tropical dry forest, cloud forest and rain forest in northwestern Costa Rica. The results show that barcoding a biologically complex biota unambiguously distinguishes among 97% of more than 1000 species of reared Lepidoptera. Those few species whose barcodes overlap are closely related and not confused with other species. Barcoding also has revealed a substantial number of cryptic species among morphologically defined species, associated sexes, and reinforced identification of species that are difficult to distinguish morphologically. For barcoding to achieve its full potential, (i) ability to rapidly and cheaply barcode older museum specimens is urgent, (ii) museums need to address the opportunity and responsibility for housing large numbers of barcode voucher specimens, (iii) substantial resources need be mustered to support the taxonomic side of the partnership with barcoding, and (iv) hand-held field-friendly barcorder must emerge as a mutualism with the taxasphere and the barcoding initiative, in a manner such that its use generates a resource base for the taxonomic process as well as a tool for the user.

Objectives An increase in lung nodule volume on serial CT may represent true growth or measurement variation. In nodule guidelines, a 25% increase in nodule volume is frequently used to determine that growth has occurred; this is based on previous same-day, test–retest (coffee-break) studies examining metastatic nodules. Whether results from prior studies apply to small non-metastatic nodules is unknown. This study aimed to establish the interscan variability in the volumetric measurements of small-sized non-metastatic nodules. Methods Institutional review board approval was obtained for this study. Between March 2019 and January 2021, 45 adults (25 males; mean age 65 years, range 37–84 years) with previously identified pulmonary nodules (30–150 mm3) requiring surveillance, without a known primary tumour, underwent two same-day CT scans. Non-calcified solid nodules were measured using commercial volumetry software, and interscan variability of volume measurements was assessed using ...

The two goals of this technology transfer study were to: (1) increase the number and appropriateness of services received by substance abuse patients, and thereby (2) give clinical meaning and value to research-based assessment information. A software-based Resource Guide was developed to allow counselors to easily identify local resources for referral of their patients to additional clinical and social services. Two hours of training were provided on the use of the guide. It was hoped that this software and training would provide the counselors with a concrete method of linking the Addiction Severity Index (ASI) assessment information on patient problems to appropriate, available community services. We expected improved treatment planning, increased problem services matching, better patient-counselor rapport/satisfaction and better patient-performance during treatment. Data were analyzed from 131 patients of 33 counselors from 9 treatment programs, randomly assigned to 2 groups-Standard Assessment (SA) or Enhanced Assessment (EA). Patients of counselors in the EA group (1) had treatment plans that were better matched to their needs, (2) received significantly more and better-matched services than patients in the SA group, and (3) were less likely to leave treatment against medical advice and more likely to complete the full course of treatment than patients of counselors in the SA group. They did not have higher levels of patient satisfaction or helping alliance scores. These findings are discussed with regard to integrating empirically supported procedures into contemporary, community-based substance abuse treatment.

♦Corresponding Author: Ammar Alhasan, MSc College of Pharmacy, AlMuthanna University, 66001, Samawah, AL-Muthanna, Iraq Email: ammar@knights.ucf.edu Introduction Detection of cancer is one of the challenges in medicine. Lung cancer is the most common cancer worldwide. Most often, if the tumor is diagnosed earlier and treated, the patient will have a better prognosis and much greater opportunity for a full recovery. The initial diagnosis of lung cancer is often delayed Abstract Background: Diagnosis of lung cancer is often delayed because most of the patients are asymptomatic during the primary cancer stages. Infrared spectroscopy is an improved technique compared with the others for identifying abnormal tissue types because of its spatial and spectral capabilities. Therefore, this study is taking an advanced advantage of the physical and optical properties of the attenuated total reflection Fourier-transform infrared system. Methods: The attenuated total reflection Fourier-transform...

In this study, we describe our methods to automatically classify Twitter posts conveying events of adverse drug reaction (ADR). Based on our previous experience in tackling the ADR classification task, we empirically applied the vote-based undersampling ensemble approach along with linear support vector machine (SVM) to develop our classifiers as part of our participation in ACL 2019 Social Media Mining for Health Applications (SMM4H) shared task 1. The best-performed model on the test sets were trained on a merged corpus consisting of the datasets released by SMM4H 2017 and 2019. By using VUE, the corpus was randomly under-sampled with 2:1 ratio between the negative and positive classes to create an ensemble using the linear kernel trained with features including bag-of-word, domain knowledge, negation and word embedding. The best performing model achieved an F-measure of 0.551 which is about 5% higher than the average F-scores of 16 teams.

Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, includi...

Artificial neural networks is one of the most commonly used machine learning algorithms in medical applications. However, they are still not used in practice in the clinics partly due to their lack of explanatory capacity. We compare two case-based explanation methods to two trained physicians on analysis of electrocardiogram (ECG) data from patients with a suspected acute coronary syndrome (ACS). The median overlaps of the top 5 selected features between the two physicians, and a given physician and a method, were initially low. Using a correlation analysis of the features the median overlap increased to values typically in the range 2-3. In conclusion, both our case-based methods generate explanations somewhat similar to those of trained expert physicians on the problem of diagnosing ACS from ECG data.

Background: The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Methods: Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Results: Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological systems do not have an external source for a map of their stored information or for an operational instruction set; rather, they must contain an organizational template conserved within their intra-nuclear architecture that "manipulates" the laws of chemistry and physics into a highly robust instruction set. We propose that the epigenetic structure of the intra-nuclear environment and the non-coding RNA may play the roles of a Biological File Allocation Table (BFAT) and biological operating system (Bio-OS) in eukaryotic cells.

In the past four years, automation for genomics has enabled a 43-fold increase in the total finished human genomic sequence in the world. This two-part noncomprehensive review will provide an overview of different types of automation equipment used in genome sequencing. Part One focuses on equipment involved in DNA preparation, DNA sequencing reactions, and other automated procedures for preparing DNA for running on sequencers or subsequent analysis; it also includes information on the development of these machines at various genome centers. Part Two, to be published in the next issue, will cover sequencing machinery and array technology, and conclude with a look at the future technologies that will revolutionize molecular biology. “Alternate” sequencing technologies (including mass spectrometry, biochips, and single-molecule analysis) will also be examined.

Dramatic progress has been made in the design and build phases of the design-build-test cycle for engineering cells. However, the test phase usually limits throughput, as many outputs of interest are not amenable to rapid analytical measurements. For example, phenotypes such as motility, morphology, and subcellular localization can be readily measured by microscopy, but analysis of these phenotypes is notoriously slow. To increase throughput, we developed microscopy-readable barcodes (MiCodes) composed of fluorescent proteins targeted to discernible organelles. In this system, a unique barcode can be genetically linked to each library member, making possible the parallel analysis of phenotypes of interest via microscopy. As a first demonstration, we MiCoded a set of synthetic coiled-coil leucine zipper proteins to allow an 8×8 matrix to be tested for specific interactions in micrographs consisting of mixed populations of cells. A novel microscopy-readable two-hybrid fluorescence localization assay for probing candidate interactions in the cytosol was also developed using a bait protein targeted to the peroxisome and a prey protein tagged with a fluorescent protein. This work introduces a generalizable, scalable platform for making

Dramatic progress has been made in the design and build phases of the design-build-test cycle for engineering cells. However, the test phase usually limits throughput, as many outputs of interest are not amenable to rapid analytical measurements. For example, phenotypes such as motility, morphology, and subcellular localization can be readily measured by microscopy, but analysis of these phenotypes is notoriously slow. To increase throughput, we developed microscopy-readable barcodes (MiCodes) composed of fluorescent proteins targeted to discernible organelles. In this system, a unique barcode can be genetically linked to each library member, making possible the parallel analysis of phenotypes of interest via microscopy. As a first demonstration, we MiCoded a set of synthetic coiled-coil leucine zipper proteins to allow an 8 × 8 matrix to be tested for specific interactions in micrographs consisting of mixed populations of cells. A novel microscopy-readable two-hybrid fluorescence l...

Distributions within a 12: 12 light: dark schedule of wakefulness (W), active sleep (AS), quiet sleep (QS) and of QS rich in delta (QSD) and in spindle (QSS) activities were evaluated for 52 days from 15 rats. Angular statistics were applied for each state by equating their hourly incidence to data distributed around a circle. Measures of location (mean angle, median angle, mode angle, maximum semicircle), dispersion (mean vector, standard deviation, quartile deviation), skewness and kurtosis were computed and their intra-and interindividual variabilities were compared. Mean angles (in hours and after lights-on) averaged 5.5 for QS, 8.6 for AS, 18.4 for W, 1.9 for QSD and 10.6 for QSS. Length of vectors, representing concentration around the mean angle, averaged 0.22 for QS, 0.36 for AS, 0.22 for W, 0.38 for QSD and 0.23 for QSS. Distributions of QS and W were closely related to the light-dark step function. QSD had a leptokurtic distribution, sharply rising at the beginning of the sleeppredominant phase, whereas AS and QSS had smoother distributions reaching maxima in its second half. In rodents as in humans, QSS and AS have opposite distributions to QSD. QSS may contribute to maintain sleep through the resting phase of the light-dark schedule after restorative function associated with delta activity has been fulfilled.

Preparing a systematic review can take hundreds of hours to complete, but the process of reconciling different results from multiple studies is the bedrock of evidence-based medicine. We introduce a two-step approach to automatically extract three facets -two entities (the agent and object) and the way in which the entities are compared (the endpoint) -from direct comparative sentences in full-text articles. The system does not require a user to predefine entities in advance and thus can be used in domains where entity recognition is difficult or unavailable. As with a systematic review, the tabular summary produced using the automatically extracted facets shows how experimental results differ between studies. Experiments were conducted using a collection of more than 2 million sentences from three journals Diabetes, Carcinogenesis and Endocrinology and two machine learning algorithms, support vector machines (SVM) and a general linear model (GLM). F 1 and accuracy measures for the SVM and GLM differed by only 0.01 across all three comparison facets in a randomly selected set of test sentences. The system achieved the best performance of 92% for objects, whereas the accuracy for both agent and endpoints was 73%. F 1 scores were higher for objects (0.77) than for endpoints (0.51) or agents (0.47). A situated evaluation of Metformin, a drug to treat diabetes, showed system accuracy of 95%, 83% and 79% for the object, endpoint and agent respectively. The situated evaluation had higher F 1 scores of 0.88, 0.64 and 0.62 for object, endpoint, and agent respectively. On average, only 5.31% of the sentences in a full-text article are direct comparisons, but the tabular summaries suggest that these sentences provide a rich source of currently underutilized information that can be used to accelerate the systematic review process and identify gaps where future research should be focused.

A data processing system designed to improve the management and usage of blood and blood products has been developed as a pilot for general application throughout the West Midlands Regional Health Authority. The package provides for the routine clerical, patient record, and stock management aspects of a hospital blood bank laboratory. It can be tailored to the individual requirements of different laboratories and may be implemented in a variety of ways on a family of computer systems of differing power and capacity, thus accommodating widely varying workloads and archiving requirements. Bar code readers are included in the system design, and may be used for data input where standard Codabar labels are affixed to blood products by blood transfusion centres. The system has been installed in one hospital laboratory and preliminary results indicate a high degree of acceptability at all levels. Further refinement of the software to meet minor deficiencies and the requirements of the recent DHSS Health Circular BLD/2/13 are currently being specified.

In this paper, a comprehensive method using symmetric normal inverse Gaussian (NIG) parameters of the sub-bands of EEG signals calculated in the dual-tree complex wavelet transformation domain is proposed for classifying EEG data. The suitability of the NIG probability distribution function is illustrated using statistical measures. A support vector machine is employed as the classifier of the EEG signals, wherein the NIG parameters are used as features. The performance of the proposed method is studied using a publicly available benchmark EEG database for various classification cases that include healthy, inter-ictal (seizure-free interval) and ictal (seizure), non-seizure and seizure, healthy and seizure, and inter-ictal and ictal, and compared with that of several recent methods. It is shown that in almost all the cases, the proposed method can provide 100 % accuracy with 100 % sensitivity and 100 % specificity while being faster as compared to the time-frequency analysis-based and EMD techniques.

1. The cuticular stress detector (CSD2) is coupled to a patch of compliant cuticle in the ischiopodite. It is excited when the compliant cuticle is deformed directly or by deformation of the surrounding stiffer cuticle. 2. Sinusoidal force (lHz) directly applied to the compliant cuticle revealed sensory units with thresholds as low as 0-03 mN, The thresholds of most units are higher by up to 40 dB. The stimulus-response curves of the CSD2 units in all preparations have an activity peak between 10 and 30 Hz. 3. In some units (on-units) the spike frequency is high while the force on the cuticle increases. The activity of other units (off-units) declines with rising force. The phase relationship between stimulus and response and the magnitude of the response depend on the exact site of force application. 4. The sensory units of CSD2 can supply the CNS with detailed information about the forces acting on the surrounding cuticle.

In recent years the amount of biological data has exploded to the point where much useful information can only be extracted by complex computational analyses. Such analyses are greatly facilitated by metadata standards, both in terms of the ability to compare data originating from different sources, and in terms of exchanging data in standard forms, e.g. when running processes on a distributed computing infrastructure. However, standards thrive on stability whereas science tends to constantly move, with new methods being developed and old ones modified. Therefore maintaining both metadata standards, and all the code that is required to make them useful, is a non-trivial problem. Memops is a framework that uses an abstract definition of the metadata (described in UML) to generate internal data structures and subroutine libraries for data access (application programming interfaces -APIs -currently in Python, C and Java) and data storage (in XML files or databases). For the individual project these libraries obviate the need for writing code for input parsing, validity checking or output. Memops also ensures that the code is always internally consistent, massively reducing the need for code reorganisation. Across a scientific domain a Memops-supported data model makes it easier to support complex standards that can capture all the data produced in a scientific area, share them among all programs in a complex software pipeline, and carry them forward to deposition in an archive. The principles behind the Memops generation code will be presented, along with example applications in Nuclear Magnetic Resonance (NMR) spectroscopy and structural biology.

This paper presents a comparative study of five supervised evaluation criteria for image segmentation. The different criteria have been tested on a selection of hundred images extracted from the c Corel database for which manual segmentation results provided by experts are available. Nine segmentation algorithms have been considered, most of which are based on threshold selection. In order to compare the behavior of the different criteria towards over- and undersegmentation, three thresholds have been taken into account, for each selected image, to simulate the various situations. Experimental results permit to reveal the advantages and limitations of the studied criteria.

Computerized charting and pointof-care testing came together in December 2007 on our nursing unit. When E-charting was implemented, results from glucometer readings went into cyberspace if the medical record numbers (MRNs) were not entered correctly. Consequently, managers spent valuable time correcting the daily logs of glucometer entry data, finding it very difficult to track the data that previous paper charting saved. Nurses spent time trying to track glucose results before giving insulin to the patients.

different than trials 2,3 and 4 (F(3,47) = 4.60, p < 0.01, Tukey HSD p < 0.05) while the mTBI group showed no significant difference in time between trials. During testing individuals with mTBI were less likely to complete the multiple test trials or required additional rest between trials than HCs (χ 2 = 10.78, p < 0.01). Small but significant correlations were seen with two neurocognitive tests of attention and RRA performance time. While observational scores were not sensitive to group differences, inertial sensor data showed motor performance on the forward run, combat roll, and backward run differed significantly between groups. The RRA task appeared challenging and provoked symptoms in the mTBI group, causing 8 of 33 mTBI participants to stop the task or require additional rest between trials while none of the HC participants had to stop. Individuals with mTBI demonstrated slower learning of the complex motor sequence compared to HCs who had significant improvement after one trial of RRA. Complex novel training maneuvers like RRA may aid clinicians in informing return to duty decisions.

This paper describes the steps followed in the creation of a local Interface Terminology to SNOMED CT (as reference terminology) with a strong focus on user acceptability. The resulting list of terms is used for clinical data input by physicians and nurses at the Hospital Italiano in Buenos Aires, Argentina. Description includes data model, mappings to SNOMED CT and classifications, subsets definitions and extensibility mechanisms. The Interface Terminology is currently used in the recording of diagnosis and procedures in inpatient discharge summaries and its coverage is improving from user feedback. Its current size is 24,800 concepts, 67% of them needed post-coordination for appropriate semantic representation, due to a very flexible policy that allows the use of any number of modifiers on concepts.

Objective-The principal MRI features of hippocampal sclerosis are volume loss and increased T2 weighted signal intensity. Minor and localised abnormalities may be overlooked without careful quantitation. Hippocampal T2 relaxation time (HT2) can be quantified, but previously has only been measured on a few thick coronal slices with interslice gaps. In this study HT2 was measured along the entire length of the hippocampus on contiguous slices and used, with quantitative measures of hippocampal volume (HV) and distribution of atrophy, to better define the range of hippocampal sclerosis. Methods-Thirty patients with temporal lobe epilepsy, 10 patients with extratemporal localisation related epilepsy and extratemporal lesions, and 20 control subjects were studied using MRI T2 relaxometry and volumetry. Results-In controls and patients, HT2 was higher in the anterior than the posterior hippocampus. Using HV, morphometric, and HT2 data, patients with temporal lobe epilepsy were classified as unilateral diVuse hippocampal sclerosis (n=16), unilateral focal (n=6), bilaterally aVected (n=6), and normal (n=2). In patients with unilateral hippocampal sclerosis, the anterior hippocampus was always aVected. In three patients with normal HV, HT2 measurements disclosed unilateral focal abnormalities that corresponded to the EEG lateralisation of epileptic activity. Patients with bilateral hippocampal involvement had an earlier onset of epilepsy than patients with unilateral hippocampal sclerosis. Conclusions-Measurement of regional abnormalities of HT2 along the length of the hippocampus provides further refinement to the MRI assessment of the hippocampi in patients with temporal lobe epilepsy and is complementary to volumetric and morphological data.

Cellulose microfibrils represent the major scaffold of plant cell walls. Different packing and orientation of the microfibrils at the microscopic scale determines the macroscopic properties of cell walls and thus affect their functions with a profound effect on plant survival. We developed a polarized Raman microspectroscopic method to determine cellulose microfibril orientation within rice plant cell walls. Employing an array of point measurements as well as area imaging and subsequent Matlab-assisted data processing, we were able to characterize the distribution of cellulose microfibril orientation in terms of director angle and anisotropy magnitude. Using this approach we detected differences between wild type rice plants and the rice brittle culm mutant, which shows a more disordered cellulose microfibril arrangement, and differences between different tissues of a wild type rice plant. This novel non-invasive Raman imaging approach allows for quantitative assessment of cellulose...

Ilio-psoas abscess (IPA) is rare in children and exceptional in the neonate. However, we recently managed two consecutive male neonates with right-sided IPA. The first baby was born two days after rupture of the membranes and had thick meconium-stained amniotic fluid. There was no such high risk factor in the second child. Diagnosis was made by ultrasonography in both the patients. Extraperitoneal surgical drainage was done and systemic antibiotics were given. Delay in presentation and uncontrolled sepsis, led to mortality in the first case. On the contrary, relatively early presentation, prompt drainage of the abscess and good response to higher antibiotics, lead to successful salvage of the second baby.

We have extended the functionality of the Central Proteomics Facilities Pipeline (CPFP) to allow use of remote cloud and high performance computing (HPC) resources for shotgun proteomics data processing. CPFP has been modified to include modular local and remote scheduling for data processing jobs. The pipeline can now be run on a single PC or server, a local cluster, a remote HPC cluster, and/or the Amazon Web Services (AWS) cloud. We provide public images that allow easy deployment of CPFP in its entirety in the AWS cloud. This significantly reduces the effort necessary to use the software, and allows proteomics laboratories to pay for compute time ad hoc, rather than obtaining and maintaining expensive local server clusters. Alternatively the Amazon cloud can be used to increase the throughput of a local installation of CPFP as necessary. We demonstrate that cloud CPFP allows users to process data at higher speed than local installations but with similar cost and lower staff requirements. In addition to the computational improvements, the web interface to CPFP is simplified, and other functionalities are enhanced. The software is under active development at two leading institutions and continues to be released under an open-source license at .

Background Computerized decision support systems (CDSSs) are believed to enhance patient care and reduce healthcare costs; however the current evidence is limited and the cost-effectiveness remains unknown. Objective To estimate the long-term cost-effectiveness of a CDSS linked to evidence-based treatment recommendations for type 2 diabetes. Methods Using the Ontario Diabetes Economic Model, changes in factors (eg, HbA1c) from a randomized controlled trial were used to estimate cost-effectiveness. The cost of implementation, development, and maintenance of the core dataset, and projected diabetesrelated complications were included. The base case assumed a 1-year treatment effect, 5% discount rate, and 40-year time horizon. Univariate, one-way sensitivity analyses were carried out by altering different parameter values. The perspective was the Ontario Ministry of Health and costs were in 2010 Canadian dollars. Results The cost of implementing the intervention was $483 699. The one-year intervention reduced HbA1c by 0.2 and systolic blood pressure by 3.95 mm Hg, but increased body mass index by 0.02 kg/m 2 , resulting in a relative risk reduction of 14% in the occurrence of amputation. The model estimated that the intervention resulted in an additional 0.0117 quality-adjusted life year; the incremental cost-effectiveness ratio was $160 845 per quality-adjusted life-year. Conclusion The web-based prototype decision support system slightly improved short-term risk factors. The model predicted moderate improvements in long-term health outcomes. This disease management program will need to develop considerable efficiencies in terms of costs and processes or improved effectiveness to be considered a cost-effective intervention for treating patients with type 2 diabetes.

Chinese language has enormous number of characters and complicated stroke structures. So it is very difficult to efficiently and accurately identify a Chinese writer from his/ her handwritings. This paper proposes a novel writer identification method for Chinese characters commonly used in Japan which can be used in peer-to-peer (P2P) systems. As a preliminary task, we have analyzed the shapes of strokes and the types of block division structures in Chinese characters and selected some characters for writer identification. The method consists of two efficient algorithms, i.e. the Hidden-feature analysis and the Block-type model, which respectively utilize intra-stroke and inter-stroke features of handwritings to enhance the writer identification accuracy. The Hidden-feature analysis makes template classes of reference characters with online features of training samples such as pen-pressure, penspeed, pen-altitude, and pen-azimuth of each stroke. The Block-type model also creates such classes for writer identification based on offline features, i.e. the positional information about blocks of sample characters. The experimental results show that the Hidden-feature analysis requires eight Chinese characters while the Block-type model requires only four characters and four ones to achieve writer identification accuracy over 98%. Additionally, the results also demonstrate that any eight Chinese characters are enough to achieve an identification accuracy over 99.9% when the combination of the two algorithms is applied.

Congenital anomalies (CA) are an important cause of morbidity and mortality in infants and children. More than 100,000 children with CA are born in EU each year. The European Surveillance of Congenital Anomalies (EUROCAT) is a network of population based congenital anomaly registries in Europe currently surveying 31% of EU birth population. EUROCAT has been awarded funding for 2011-2013 as a Joint Action between EU and member states. The Joint Action EUROCAT aims to use harmonised data on CA across EU to assess prevalence of all birth outcomes, the impact of primary prevention, and developments in prenatal screening. Joint Action EUROCAT will serve as an early warning of teratogen exposures, and act as an information centre regarding clusters, and exposures to risk factors of concern, including new medicine used in pregnancy, ail pollution, swine flu vaccination, and chronic maternal diseases as obesity and diabetes.

Background: Accurate assessment of medication adherence has been difficult to achieve but is essential to drug evaluation in clinical trials and improved outcomes in clinical care. Objective: This study was conducted to compare four adherence assessment methods: child report, mother report, canister weight, and electronic measurements of metered dose inhaler (MDI) actuation. Methods: Participants included 27 children with mild-to-moderate asthma who were followed prospectively for 6 months. All patients used an MDI equipped with an electronic Doser attached to their inhaled steroid. At each 2-month follow-up visit, Doser and canister weight data were recorded, while child and mother were interviewed separately regarding medication use. Results: Children and mothers reported, on average, over 80% adherence with the prescribed inhaled steroid. Canister weight revealed, on average, adherence of 69%, significantly lower than self-report. When adherence recorded by the electronic Doser was truncated to no more than 100% of prescribed daily use, average adherence was 50%. Older children and adolescents, nonwhite children, and those from poorer functioning families were least adherent. Conclusions: Electronic adherence monitoring was significantly more accurate than self-report or canister weight measures. Such accuracy is an essential prerequisite to increasing understanding of the treatment, setting, and patient factors that influence adherence, and to the consequent design of effective intervention strategies.

OBJECTIVE Insulin resistance and type 2 diabetes are associated with an increased risk of neurodegenerative diseases. Brain-derived neurotrophic factor (BDNF) regulates neuronal differentiation and synaptic plasticity, and its decreased levels are supposed to play a role in the pathogenesis of Alzheimer’s disease and other disorders. The aim of the current study was to estimate the effects of hyperinsulinemia and serum free fatty acids (FFA) elevation on circulating BDNF concentration in humans. RESEARCH DESIGN AND METHODS We studied 18 healthy male subjects (mean age 25.6 ± 3.0 years; mean BMI 26.6 ± 4.8 kg/m2). Serum and plasma BDNF concentration was measured in the baseline state and in the 120 and 360 min of euglycemic hyperinsulinemic clamp with or without intralipid/heparin infusion. Furthermore, plasma BDNF was measured in 20 male subjects (mean age 22.7 ± 2.3 years; mean BMI 24.9 ± 1.5 kg/m2) 360 min after a high-fat meal. RESULTS Insulin sensitivity was reduced by ∼40% afte...

This paper examines the seasonal duty cycle variation of meteor and nonmeteor propagation at 45 MHz on two high‐latitude links. Software techniques for automatic data processing and analysis of the data are discussed. It is shown that for large portions of the year nonmeteoric propagation, most likely sporadic E, is the dominant propagation mechanism. Consequently, protocols for an operational meteor scatter communication network must be designed to cope with a situation in which close to an entire network may be connected for long periods of time. System duty cycles at 45 MHz in excess of 20% are common during the summer months in the high‐latitude region.

The comprehensive and stress-free assessment of various aspects of learning and memory is a prerequisite to evaluate mouse models for neuropsychiatric disorders such as Alzheimer's disease or attention deficit/hyperactivity disorder (ADHD). COGITAT is an automated holeboard system allowing simultaneous assessment of spatial working and reference-memory performance which we have adapted in this study to enable its usage with mice. The holeboard apparatus consists of an open-field chamber with a 25-hole floor insert, each hole being monitored by infrared light beams, located on three different levels, allowing the distinction between visits of holes, i.e. the animal reaches the bottom of the hole, or inspections, which means only superficial exploration of the hole. Across trials, animals learn a pattern of five baited holes. Here, we show that C57BL/6 mice readily acquire this task within 5 days when submitted to six trials per day. A number of individual parameters -overall exploratory activity, number of visits into or inspections of holes, number of baited, unbaited, or previously baited holes visited or inspected, reinspections of or revisits into any holes, number of pellets eaten, time to find pellets, and reference and working memory errors-are obtained simultaneously and results are immediately available after the end of each experiment. The muscarinic antagonist scopolamine impaired task performance, while the cognitive enhancer metrifonate (an acetylcholinesterase inhibitor) reduced error rates. Overall, our data indicate that this spatial learning task will be useful to characterize spatial memory in various genetic or pharmacological mouse models.

Accurately detecting emotional expression in women with primary breast cancer participating in support groups may be important for therapists and researchers. In 2 small studies (N ϭ 20 and N ϭ 16), the authors examined whether video coding, human text coding, and automated text analysis provided consistent estimates of the level of emotional expression. In Study 1, the authors compared coding from videotapes and text transcripts of face-to-face groups. In Study 2, the authors examined transcripts of online synchronous groups. The authors found that human text coding significantly overestimated Positive Affect and underestimated Defensive/Hostile Affect compared with video coding. They found correlations were low for Positive Affect but moderate for negative affect between Linguistic Inquiry Word Count (LIWC) and video coding. The implications of utilizing text-only detection of emotion are discussed.

Digital peripheral arterial tonometry (PAT) is an emerging, noninvasive method to assess vascular function. The physiology underlying this phenotype, however, remains unclear. Therefore, we evaluated the relation between digital PAT and established brachial artery ultrasound measures of vascular function under basal conditions and after reactive hyperemia. Using a cross-sectional study design, digital PAT and brachial artery ultrasonography with pulsed wave Doppler were simultaneously completed at baseline and after reactive hyperemia in both those with established coronary artery disease (n ‫؍‬ 99) and healthy volunteers with low cardiovascular disease risk (n ‫؍‬ 40). Under basal conditions, the digital pulse volume amplitude demonstrated a significant positive correlation with the brachial artery velocity-time integral that was independent of the arterial diameter, in both the healthy volunteer (r s ‫؍‬ 0.64, p <0.001) and coronary artery disease (r s ‫؍‬ 0.63, p <0.001) cohorts. Similar positive relations were observed with the baseline brachial artery blood flow velocity and blood flow. In contrast, no relation between the reactive hyperemia-evoked digital PAT ratio and either brachial artery flow-mediated dilation or shear stress was observed in either cohort (p ‫؍‬ NS). In conclusion, these findings demonstrate that the digital PAT measures of vascular function more closely reflect basal blood flow in the brachial artery than reactive hyperemia-induced changes in the arterial diameter or flow velocity, and the presence of vascular disease does not modify the physiology underlying the digital PAT phenotype.

Background: Prior studies demonstrate the suitability of natural language processing (NLP) for identifying pneumonia in chest radiograph (CXR) reports, however, few evaluate this approach in intensive care unit (ICU) patients. Methods: From a total of 194,615 ICU reports, we empirically developed a lexicon to categorize pneumonia-relevant terms and uncertainty profiles. We encoded lexicon items into unique queries within an NLP software application and designed an algorithm to assign automated interpretations ('positive', 'possible', or 'negative') based on each report's query profile. We evaluated algorithm performance in a sample of 2,466 CXR reports interpreted by physician consensus and in two ICU patient subgroups including those admitted for pneumonia and for rheumatologic/ endocrine diagnoses. Results: Most reports were deemed 'negative' (51.8%) by physician consensus. Many were 'possible' (41.7%); only 6.5% were 'positive' for pneumonia. The lexicon included 105 terms and uncertainty profiles that were encoded into 31 NLP queries. Queries identified 534,322 'hits' in the full sample, with 2.7 ± 2.6 'hits' per report. An algorithm, comprised of twenty rules and probability steps, assigned interpretations to reports based on query profiles. In the validation set, the algorithm had 92.7% sensitivity, 91.1% specificity, 93.3% positive predictive value, and 90.3% negative predictive value for differentiating 'negative' from 'positive'/'possible' reports. In the ICU subgroups, the algorithm also demonstrated good performance, misclassifying few reports (5.8%). Conclusions: Many CXR reports in ICU patients demonstrate frank uncertainty regarding a pneumonia diagnosis. This electronic tool demonstrates promise for assigning automated interpretations to CXR reports by leveraging both terms and uncertainty profiles.