Application of microarrays (phylochips) for analysis of community diversity by species identification

Abstract Molecular probe-based methods (Fluorescent in-situ hybridisation or FISH, Next Generation Sequencing or NGS) have proved successful in improving both the efficiency and accuracy of the identification of microorganisms, especially those that lack distinct morphological features, such as picoplankton. However, FISH methods have the major drawback that they can only identify one or just a few species at a time because of the reduced number of available fluorochromes that can be added to the probe. Although the length of sequence that can be obtained is continually improving, NGS still requires a great deal of handling time, its analysis time is still months and with a PCR step it will always be sensitive to natural enzyme inhibitors. With the use of DNA microarrays, it is possible to identify large numbers of taxa on a single-glass slide, the so-called phylochip, which can be semi-quantitative. This review details the major steps in probe design, design and production of a phylochip and validation of the array. Finally, major microarray studies in the phytoplankton community are reviewed to demonstrate the scope of the method.

Application of microarrays (phylochips) for analysis of community diversity by species identification

Abstract Molecular probe-based methods (Fluorescent in-situ hybridisation or FISH, Next Generation Sequencing or NGS) have proved successful in improving both the efficiency and accuracy of the identification of microorganisms, especially those that lack distinct morphological features, such as picoplankton. However, FISH methods have the major drawback that they can only identify one or just a few species at a time because of the reduced number of available fluorochromes that can be added to the probe. Although the length of sequence that can be obtained is continually improving, NGS still requires a great deal of handling time, its analysis time is still months and with a PCR step it will always be sensitive to natural enzyme inhibitors. With the use of DNA microarrays, it is possible to identify large numbers of taxa on a single-glass slide, the so-called phylochip, which can be semi-quantitative. This review details the major steps in probe design, design and production of a phylochip and validation of the array. Finally, major microarray studies in the phytoplankton community are reviewed to demonstrate the scope of the method.

STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies

Incomplete reporting has been identified as a major source of avoidable waste in biomedical research.
Essential information is often not provided in study reports, impeding the identification, critical
appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy
studies, the Standards for Reporting Diagnostic Accuracy (STARD) statement was developed. Here
we present STARD 2015, an updated list of 30 essential items that should be included in every
report of a diagnostic accuracy study. This update incorporates recent evidence about sources of
bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such,
STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy
studies.

Entropy feature extraction of EEG signals for automatic person identification

The use of human brain electroencephalography (EEG) signals for automatic person identi cation has been investigated for a decade. It has been found that the performance of an EEG-based person identication system highly depends on what feature to be extracted from multi-channel EEG signals. Linear methods such as Power Spectral Density and Autoregressive Model have been used to extract EEG features. However these methods assumed that EEG signals are stationary. In fact, EEG signals are complex, non-linear, non-stationary, and random in nature. In addition, other factors such as brain condition or human characteristics may have impacts on the performance, however these factors have not been investigated and evaluated in previous studies. It has been found in the literature that entropy is used to measure the randomness of non-linear time series data. Entropy is also used to measure the level of chaos of braincomputer interface systems. Therefore, this thesis proposes to study the role of entropy in non-linear analysis of EEG signals to discover new features for EEG-based person identi- cation. Five dierent entropy methods including Shannon Entropy, Approximate Entropy, Sample Entropy, Spectral Entropy, and Conditional Entropy have been proposed to extract entropy features that are used to evaluate the performance of EEG-based person identication systems and the impacts of epilepsy, alcohol, age and gender characteristics on these systems. Experiments were performed on the Australian EEG and Alcoholism datasets. Experimental results have shown that, in most cases, the proposed entropy features yield very fast person identication, yet with compatible accuracy because the feature dimension is low. In real life security operation, timely response is critical. The experimental results have also shown that epilepsy, alcohol, age and gender characteristics have impacts on the EEG-based person identication systems.

Combining Leaf Shape and Texture for Costa Rican Plant Species Identification

In the last decade, research in Computer Vision has developed several algorithms to help botanists and non-experts to classify plants based on images of their leaves. LeafSnap is a mobile application that uses a multiscale curvature model of the leaf margin to classify leaf images into species. It has achieved high levels of accuracy on 184 tree species from Northeast US. We extend the research that led to the development of LeafSnap along two lines. First, LeafSnap’s underlying algorithms are applied to a set of 66 tree species from Costa Rica. Then, texture is used as an additional criterion to measure the level of improvement achieved in the automatic identification of Costa Rica tree species. A 25.6% improvement was achieved for a Costa Rican clean image dataset and 42.5% for a Costa Rican noisy image dataset. In both cases, our results show this increment as statistically significant. Further statistical analysis of visual noise impact, best algorithm combinations per species, and best value of , the minimal cardinality of the set of candidate species that the tested algorithms render as best matches is also presented in this research

A Fuzzy Decision Strategy for Topic Identification and Dynamic Selection of Language Models

International audience

Accuracy of ASGE criteria for the prediction of choledocholithiasis

Background/aims: Few studies have validated the performance of guidelines for the prediction of choledocholithiasis (CL). Our objective was to prospectively assess the accuracy of the American Society for Gastrointestinal Endoscopy (ASGE) guidelines for the identification of CL. Methods: A two-year prospective evaluation of patients with suspected CL was performed. We evaluated the ASGE guidelines and its component variables in predicting CL. Results: A total of 256 patients with suspected CL were analyzed. Of the 208 patients with high-probability criteria for CL, 124 (59.6%) were found to have a stone/sludge at endoscopic retrograde cholangiopancreatography (ERCP). Among 48 patients with intermediate-probability criteria, 21 (43.8%) had a stone/sludge. The performance of ASGE high- and intermediate-probability criteria in our population had an accuracy of 59.0% (85.5% sensitivity, 24.3% specificity) and 41.0% (14.4% sensitivity, 75.6% specificity), respectively. The mean ERCP delay time was 6.1 days in the CL group and 6.4 days in the group without CL, p = 0.638. The presence of a common bile duct (CBD) > 6 mm (OR 2.21; 95% CI, 1.20-4.10), ascending cholangitis (OR 2.37; 95% CI, 1.01-5.55) and a CBD stone visualized on transabdominal US (OR 3.33; 95% CI, 1.48-7.52) were stronger predictors of CL. The occurrence of biliary pancreatitis was a strong protective factor for the presence of a retained CBD stone (OR 0.30; 95% CI, 0.17-0.55). Conclusions: Irrespective of a patient's ASGE probability for CL, the application of current guidelines in our population led to unnecessary performance of ERCPs in nearly half of cases.

Automatic identification of whole-part relations in Portuguese

Dissertação de Mestrado, Ciências da Linguagem, Faculdade de Ciências Humanas e Sociais, Universidade do Algarve, 2014

The Impact of the "Not Sure" Option on Lineup Identification Decisions

Law enforcement officials routinely rely on eyewitness identification evidence to solve crimes. Nonetheless, this form of evidence is prone to errors. Researchers have previously attempted to examine conditions under which such errors can be reduced. The present study examines whether giving witnesses an explicit not sure response option increases the accuracy of lineup identification decisions. 251 participants watched a mock crime video before viewing a lineup that either included the perpetrator, or was made up of innocent suspects. Results indicated that witnesses provided with a not sure option made fewer false identifications, fewer filler identifications, and a similar number of correct identifications as witnesses who were not provided with this option. Furthermore, these benefits occurred regardless of whether witnesses received otherwise biased or unbiased instructions. Results suggest that the inclusion of an explicit not sure response option is a simple procedure that can increase the quality of eyewitness lineup decisions.

The creation and evaluation of novel canine training aids for cocaine using molecularly encapsulated sol-gel polymers and an investigation of canine field accuracy

Biological detectors, such as canines, are valuable tools used for the rapid identification of illicit materials. However, recent increased scrutiny over the reliability, field accuracy, and the capabilities of each detection canine is currently being evaluated in the legal system. For example, the Supreme Court case, State of Florida v. Harris, discussed the need for continuous monitoring of canine abilities, thresholds, and search capabilities. As a result, the fallibility of canines for detection was brought to light, as well as a need for further research and understanding of canine detection. This study is two-fold, as it looks to not only create new training aids for canines that can be manipulated for dissipation control, but also investigates canine field accuracy to objects with similar odors to illicit materials. ^ It was the goal of this research to improve upon current canine training aid mimics. Sol-gel polymer training aids, imprinted with the active odor of cocaine, were developed. This novel training aid improved upon the longevity of currently existing training aids, while also provided a way to manipulate the polymer network to alter the dissipation rate of the imprinted active odors. The manipulation of the polymer network could allow handlers to control the abundance of odors presented to their canines, familiarizing themselves to their canine’s capabilities and thresholds, thereby increasing the canines’ strength in court.^ The field accuracy of detection canines was recently called into question during the Supreme Court case, State of Florida v. Jardines, where it was argued that if cocaine’s active odor, methyl benzoate, was found to be produced by the popular landscaping flower, snapdragons, canines will false alert to said flowers. Therefore, snapdragon flowers were grown and tested both in the laboratory and in the field to determine the odors produced by snapdragon flowers; the persistence of these odors once flowers have been cut; and whether detection canines will alert to both growing and cut flowers during a blind search scenario. Results revealed that although methyl benzoate is produced by snapdragon flowers, certified narcotics detection canines can distinguish cocaine’s odor profile from that of snapdragon flowers and will not alert.^

Assessment of MALDI-TOF MS as Alternative Tool for Streptococcus suis Identification

The accuracy of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) for identifying Streptococcus suis isolates obtained from pigs, wild animals, and humans was evaluated using a PCR-based identification assay as the gold standard. In addition, MALDI-TOF MS was compared with the commercial multi-tests Rapid ID 32 STREP system. From the 129 S. suis isolates included in the study and identified by the molecular method, only 31 isolates (24.03%) had score values ≥2.300 and 79 isolates (61.24%) gave score values between 2.299 and 2.000. After updating the currently available S. suis MALDI Biotyper database with the spectra of three additional clinical isolates of serotypes 2, 7, and 9, most isolates had statistically significant higher score values (mean score: 2.65) than those obtained using the original database (mean score: 2.182). Considering the results of the present study, we suggest using a less restrictive threshold score of ≥2.000 for reliable species identification of S. suis. According to this cut-off value, a total of 125 S. suis isolates (96.9%) were correctly identified using the updated database. These data indicate an excellent performance of MALDI-TOF MS for the identification of S. suis.

Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

Mucopolysaccharidosis Type Ii: Identification Of 30 Novel Mutations Among Latin American Patients.

In this study, 103 unrelated South-American patients with mucopolysaccharidosis type II (MPS II) were investigated aiming at the identification of iduronate-2-sulfatase (IDS) disease causing mutations and the possibility of some insights on the genotype-phenotype correlation The strategy used for genotyping involved the identification of the previously reported inversion/disruption of the IDS gene by PCR and screening for other mutations by PCR/SSCP. The exons with altered mobility on SSCP were sequenced, as well as all the exons of patients with no SSCP alteration. By using this strategy, we were able to find the pathogenic mutation in all patients. Alterations such as inversion/disruption and partial/total deletions of the IDS gene were found in 20/103 (19%) patients. Small insertions/deletions/indels (<22 bp) and point mutations were identified in 83/103 (88%) patients, including 30 novel mutations; except for a higher frequency of small duplications in relation to small deletions, the frequencies of major and minor alterations found in our sample are in accordance with those described in the literature.

Identification Of Target Genes Using Gene Expression Profile Of Granulocytes From Patients With Chronic Myeloid Leukemia Treated With Tyrosine Kinase Inhibitors.

Differential gene expression analysis by suppression subtractive hybridization with correlation to the metabolic pathways involved in chronic myeloid leukemia (CML) may provide a new insight into the pathogenesis of CML. Among the overexpressed genes found in CML at diagnosis are SEPT5, RUNX1, MIER1, KPNA6 and FLT3, while PAN3, TOB1 and ITCH were decreased when compared to healthy volunteers. Some genes were identified and involved in CML for the first time, including TOB1, which showed a low expression in patients with CML during tyrosine kinase inhibitor treatment with no complete cytogenetic response. In agreement, reduced expression of TOB1 was also observed in resistant patients with CML compared to responsive patients. This might be related to the deregulation of apoptosis and the signaling pathway leading to resistance. Most of the identified genes were related to the regulation of nuclear factor κB (NF-κB), AKT, interferon and interleukin-4 (IL-4) in healthy cells. The results of this study combined with literature data show specific gene pathways that might be explored as markers to assess the evolution and prognosis of CML as well as identify new therapeutic targets.

High Diagnostic Accuracy And Reproducibility Of Fine-needle Aspiration Cytology For Diagnosing Salivary Gland Tumors: Cytohistologic Correlation In 182 Cases.

The purpose of this study was to assess the efficacy and reproducibility of the cytologic diagnosis of salivary gland tumors (SGTs) using fine-needle aspiration cytology (FNAC). The study aimed to determine diagnostic accuracy, sensitivity, and specificity and to evaluate the extent of interobserver agreement. We retrospectively evaluated SGTs from the files of the Division of Pathology at the Clinics Hospital of São Paulo and Piracicaba Dental School between 2000 and 2006. We performed cytohistologic correlation in 182 SGTs. The sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were 94%, 100%, 100%, 100%, and 99%, respectively. The interobserver cytologic reproducibility showed significant statistical concordance (P < .0001). FNAC is an effective tool for performing a reliable preoperative diagnosis in SGTs and shows high diagnostic accuracy and consistent interobserver reproducibility. Further FNAC studies analyzing large samples of malignant SGTs and reactive salivary lesions are needed to confirm their accuracy.