Gaussian Process-based prediction of memory performance and biomarker status in ageing and Alzheimer's disease-A systematic model evaluation

Neuroimaging markers based on Magnetic Resonance Imaging (MRI) combined with various other measures (such as genetic covariates, biomarkers, vascular risk factors, neuropsychological tests etc.) might provide useful predictions of clinical outcomes during the progression towards Alzheimer's disease (AD). The use of multiple features in predictive frameworks for clinical outcomes has become increasingly prevalent in AD research. However, many studies do not focus on systematically and accurately evaluating combinations of multiple input features. Hence, the aim of the present work is to explore and assess optimal combinations of various features for MR-based prediction of (1) cognitive status and (2) biomarker positivity with a multi-kernel learning Gaussian process framework. The explored features and parameters included (A) combinations of brain tissues, modulation, smoothing, and image resolution; (B) incorporating demographics & clinical covariates; (C) the impact of the size of the training data set; (D) the influence of dimensionality reduction and the choice of kernel types. The approach was tested in a large German cohort including 959 subjects from the multicentric longitudinal study of cognitive impairment and dementia (DELCODE). Our evaluation suggests the best prediction of memory performance was obtained for a combination of neuroimaging markers, demographics, genetic information (ApoE4) and CSF biomarkers explaining 57% of outcome variance in out-of-sample predictions. The highest performance for Aβ42/40 status classification was achieved for a combination of demographics, ApoE4, and a memory score while usage of structural MRI further improved the classification of individual patient's pTau status.

Prevalence and mean number of teeth with amalgam and nonamalgam restorations, United States, 2015 through 2018

BACKGROUND

Amalgam has been used for more than 150 years as a safe and reliable restorative material. The authors described the occurrence of amalgam and nonamalgam restorations in the United States in primary and permanent teeth across age groups and according to sociodemographic characteristics.

METHODS

The authors used clinical examination data from the National Health and Nutrition Examination Survey 2015-2018 for participants 2 years and older (n = 17,040). The authors estimated the prevalence and mean number of amalgam and nonamalgam restorations in primary and permanent teeth according to age groups (2-5 years, 6-11 years, 12-15 years, 16-19 years, 20-39 years, 40-59 years, 60-79 years, and ≥ 80 years), race and ethnicity, federal poverty guideline, education, and pregnancy status.

RESULTS

The prevalence of amalgam restorations ranged from 4% through 69%. Overall, amalgam restorations were more prevalent in children and adolescents from racial and ethnic minority groups and families at lower poverty levels and with lower education. The mean number of teeth with nonamalgam restorations was higher than those with amalgam restorations in primary teeth of children aged 6 through 11 years, permanent teeth of those 12 through 15 years and 20 through 39 years, and women aged 20 through 49 years, regardless of pregnancy status. The mean number of amalgam restorations was higher than that for nonamalgam restorations in older age groups.

CONCLUSIONS

Nonamalgam restorations were the most common in the primary teeth of children older than 5 years and in the permanent teeth of adults younger than 40 years. Amalgam restorations were more common in older adults. Amalgam and nonamalgam restorations were equally common in children younger than 5 years.

PRACTICAL IMPLICATIONS

The study findings suggest a shift from amalgam to alternative restorative materials in the United States.

Atrial-specific reduction of Kir2.1 channel pore diameter in addition to loss of inward-going rectification underlies inducible atrial fibrillation in a mouse model of short QT syndrome type 3

Introduction

Short QT Syndrome Type 3 (SQTS3) is an extremely rare arrhythmogenic disease caused by gain-of-function mutations in the KCNJ2 gene coding the inward rectifier potassium channel Kir2.1. We investigated arrhythmogenic mechanisms associated with a de-novo mutation (E299V) in Kir2.1 in an 11-year-old boy presenting an extremely abbreviated QT interval, paroxysmal atrial fibrillation, and mild left ventricular dysfunction. Amino acid E299 in the Kir2.1 sequence is necessary for polyamine binding induced inward rectification.

Purpose

Test the hypothesis that Kir2.1E299V induces reduced conductance and lack of rectification that causes electrical defects in atrial cardiomyocytes, predisposing patients to atrial arrhythmias.

Methods

We used intravenous adeno-associated virus-mediated gene transfer to generate mice expressing wild-type (WT) and the E299V mutant protein. We used ECG, intracardiac stimulation, patch-clamp, molecular biology and computational modelling to characterize the models and study arrhythmia mechanisms in the atria and ventricles.

Results

We confirmed WT or mutant Kir2.1 gene expression specifically in the mouse heart. On ECG, the corrected QT (QTc) interval of Kir2.1E299V mice was significantly shorter than Kir2.1WT mice (p<0.0001). The PR interval in Kir2.1E299V was also significantly shorter than WT mice (p<0.0001). On intracardiac stimulation, the largest proportion of arrhythmic events occurred in the atria, as 7 out of 9 Kir2.1E299V mice presented >1 second atrial flutter/fibrillation, while only 2 out of 10 Kir2.1WT mice showed this type of arrhythmia (p=0.023). On patch clamping, both atrial and ventricular cardiomyocytes expressing Kir2.1E299V had extremely abbreviated action potential durations (APD90) at all frequencies studied (p<0.0001). The current/voltage relation of ventricular Kir2.1E299V cardiomyocytes revealed an absence of inward-going rectification and increased IK1 at voltages positive to −80 mV compared to Kir2.1WT cardiomyocytes (p<0.0001). In contrast, while in the atrial Kir2.1E299V cardiomyocytes the outward IK1 was increased at voltages positive to −80 mV with loss of rectification, IK1 was significantly reduced at voltages negative to −80 mV (p<0.0001), suggesting a loss of function leading to atrial arrhythmia inducibility. A higher proportion of Kir2.2 at atrial level and atomic in-silico 3D simulations suggested that the mutation impaired polyamine block of the Kir2.1E299V-Kir2.2 channel while reducing the pore diameter.

Conclusions

This first in-vivo mouse model of cardiac-specific SQTS3 recapitulates the electrophysiological phenotype of a patient with the Kir2.1E299V mutation. The mutation results in a Kir2.1 gain-of-function mediated by and absence of rectification. The predominant arrhythmias induced in these SQTS3 mice were supraventricular likely due to the combined lack of inward rectification and atrial-specific reduced pore diameter of the Kir2.1E299V-Kir2.2 channel.

Funding Acknowledgement

Type of funding sources: Private company. Main funding source(s): La Caixa FoundationLa Maratό TV3 Foundation

In vivo computer-aided diagnosis of colorectal polyps using white light endoscopy

Background and study aims  Artificial intelligence is currently able to accurately predict the histology of colorectal polyps. However, systems developed to date use complex optical technologies and have not been tested in vivo. The objective of this study was to evaluate the efficacy of a new deep learning-based optical diagnosis system, ATENEA, in a real clinical setting using only high-definition white light endoscopy (WLE) and to compare its performance with endoscopists. Methods  ATENEA was prospectively tested in real life on consecutive polyps detected in colorectal cancer screening colonoscopies at Hospital Clínic. No images were discarded, and only WLE was used. The in vivo ATENEA's prediction (adenoma vs non-adenoma) was compared with the prediction of four staff endoscopists without specific training in optical diagnosis for the study purposes. Endoscopists were blind to the ATENEA output. Histology was the gold standard. Results  Ninety polyps (median size: 5 mm, range: 2-25) from 31 patients were included of which 69 (76.7 %) were adenomas. ATENEA correctly predicted the histology in 63 of 69 (91.3 %, 95 % CI: 82 %-97 %) adenomas and 12 of 21 (57.1 %, 95 % CI: 34 %-78 %) non-adenomas while endoscopists made correct predictions in 52 of 69 (75.4 %, 95 % CI: 60 %-85 %) and 20 of 21 (95.2 %, 95 % CI: 76 %-100 %), respectively. The global accuracy was 83.3 % (95 % CI: 74%-90 %) and 80 % (95 % CI: 70 %-88 %) for ATENEA and endoscopists, respectively. Conclusion  ATENEA can accurately be used for in vivo characterization of colorectal polyps, enabling the endoscopist to make direct decisions. ATENEA showed a global accuracy similar to that of endoscopists despite an unsatisfactory performance for non-adenomatous lesions.

Effects of oral iodine supplementation in very low birth weight preterm infants for the prevention of thyroid function alterations during the neonatal period: results of a randomised assessor-blinded pilot trial and neurodevelopmental outcomes at 24 months

The trace element iodine (I) is essential for the synthesis of thyroid hormones. Parenteral nutrition solutions, formula milk, and human breast milk contain insufficient iodine to meet recommended intake for preterm infants. Iodine deficiency may affect thyroid function and may be associated with morbidity or neurological outcomes. The primary objective is to assess the evidence that dietary supplementation with iodine affects thyroid function during the neonatal period. The design was a randomised controlled pilot trial. Infants who met the inclusion criteria were enrolled through consecutive sampling and assigned to two different groups. The setting was a Spanish university hospital. Ninety-four patients with very low birth weight (under 1500 g) were included. Intervention group: 30 µg I/kg/day of iodine in oral drops given to 47 infants from their first day of life until hospital discharge. Control group: 47 infants without supplements. Formula and maternal milk samples for the determination of iodine content were collected at 1, 7, 15, 21, 30 days, and at discharge. Blood samples were collected for thyroid hormones. Neurological development was assessed at 2 years of age (Bayley III Test). Infants in the supplemented group reached the recommended levels from the first days of life. The researchers detected the effects of iodine balance on the plasma levels of thyroid hormones measured during the first 12 weeks of age. The trial assessed the impact of the intervention on neurodevelopmental morbidity.Conclusion: Thyroid function is related to iodine intake in preterm infants. Therefore, supplements should be added if iodine intake is found to be inadequate. The analyses found no effects of iodine supplementation on the composite scores for Bayley-III assessments in all major domains. The study results indicate potentially important effects on language development related to low iodine excretion during the first 4 weeks of life What is Known: • Thyroid function is related to iodine intake in preterm infants. • Preterm babies on formula preparations and with exclusive parenteral nutrition are at high risk of iodine deficiency. What is New: • Iodine intake should be monitored during the neonatal period. • Iodine supplements should be added if iodine intake is found to be inadequate.

Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method

BACKGROUND : Artificial intelligence (AI) research in colonoscopy is progressing rapidly but widespread clinical implementation is not yet a reality. We aimed to identify the top implementation research priorities. METHODS : An established modified Delphi approach for research priority setting was used. Fifteen international experts, including endoscopists and translational computer scientists/engineers, from nine countries participated in an online survey over 9 months. Questions related to AI implementation in colonoscopy were generated as a long-list in the first round, and then scored in two subsequent rounds to identify the top 10 research questions. RESULTS : The top 10 ranked questions were categorized into five themes. Theme 1: clinical trial design/end points (4 questions), related to optimum trial designs for polyp detection and characterization, determining the optimal end points for evaluation of AI, and demonstrating impact on interval cancer rates. Theme 2: technological developments (3 questions), including improving detection of more challenging and advanced lesions, reduction of false-positive rates, and minimizing latency. Theme 3: clinical adoption/integration (1 question), concerning the effective combination of detection and characterization into one workflow. Theme 4: data access/annotation (1 question), concerning more efficient or automated data annotation methods to reduce the burden on human experts. Theme 5: regulatory approval (1 question), related to making regulatory approval processes more efficient. CONCLUSIONS : This is the first reported international research priority setting exercise for AI in colonoscopy. The study findings should be used as a framework to guide future research with key stakeholders to accelerate the clinical implementation of AI in endoscopy.

Polyp Segmentation with Fully Convolutional Deep Neural Networks-Extended Evaluation Study

Analysis of colonoscopy images plays a significant role in early detection of colorectal cancer. Automated tissue segmentation can be useful for two of the most relevant clinical target applications-lesion detection and classification, thereby providing important means to make both processes more accurate and robust. To automate video colonoscopy analysis, computer vision and machine learning methods have been utilized and shown to enhance polyp detectability and segmentation objectivity. This paper describes a polyp segmentation algorithm, developed based on fully convolutional network models, that was originally developed for the Endoscopic Vision Gastrointestinal Image Analysis (GIANA) polyp segmentation challenges. The key contribution of the paper is an extended evaluation of the proposed architecture, by comparing it against established image segmentation benchmarks utilizing several metrics with cross-validation on the GIANA training dataset. Different experiments are described, including examination of various network configurations, values of design parameters, data augmentation approaches, and polyp characteristics. The reported results demonstrate the significance of the data augmentation, and careful selection of the method's design parameters. The proposed method delivers state-of-the-art results with near real-time performance. The described solution was instrumental in securing the top spot for the polyp segmentation sub-challenge at the 2017 GIANA challenge and second place for the standard image resolution segmentation task at the 2018 GIANA challenge.

Review of computational methods for the detection and classification of polyps in colonoscopy imaging

Computer-aided diagnosis (CAD) is a tool with great potential to help endoscopists in the tasks of detecting and histologically classifying colorectal polyps. In recent years, different technologies have been described and their potential utility has been increasingly evidenced, which has generated great expectations among scientific societies. However, most of these works are retrospective and use images of different quality and characteristics which are analysed off line. This review aims to familiarise gastroenterologists with computational methods and the particularities of endoscopic imaging, which have an impact on image processing analysis. Finally, the publicly available image databases, needed to compare and confirm the results obtained with different methods, are presented.

Polyp fingerprint: automatic recognition of colorectal polyps' unique features

BACKGROUND

Content-based image retrieval (CBIR) is an application of machine learning used to retrieve images by similarity on the basis of features. Our objective was to develop a CBIR system that could identify images containing the same polyp ('polyp fingerprint').

METHODS

A machine learning technique called Bag of Words was used to describe each endoscopic image containing a polyp in a unique way. The system was tested with 243 white light images belonging to 99 different polyps (for each polyp there were at least two images representing it in two different temporal moments). Images were acquired in routine colonoscopies at Hospital Clínic using high-definition Olympus endoscopes. The method provided for each image the closest match within the dataset.

RESULTS

The system matched another image of the same polyp in 221/243 cases (91%). No differences were observed in the number of correct matches according to Paris classification (protruded: 90.7% vs. non-protruded: 91.3%) and size (< 10 mm: 91.6% vs. > 10 mm: 90%).

CONCLUSIONS

A CBIR system can match accurately two images containing the same polyp, which could be a helpful aid for polyp image recognition.

Computer-aided prediction of polyp histology on white light colonoscopy using surface pattern analysis

BACKGROUND

This study aimed to evaluate a new computational histology prediction system based on colorectal polyp textural surface patterns using high definition white light images.

METHODS

Textural elements (textons) were characterized according to their contrast with respect to the surface, shape, and number of bifurcations, assuming that dysplastic polyps are associated with highly contrasted, large tubular patterns with some degree of bifurcation. Computer-aided diagnosis (CAD) was compared with pathological diagnosis and the diagnosis made by endoscopists using Kudo and Narrow-Band Imaging International Colorectal Endoscopic classifications.

RESULTS

Images of 225 polyps were evaluated (142 dysplastic and 83 nondysplastic). The CAD system correctly classified 205 polyps (91.1 %): 131/142 dysplastic (92.3 %) and 74/83 (89.2 %) nondysplastic. For the subgroup of 100 diminutive polyps (≤ 5 mm), CAD correctly classified 87 polyps (87.0 %): 43/50 (86.0 %) dysplastic and 44/50 (88.0 %) nondysplastic. There were no statistically significant differences in polyp histology prediction between the CAD system and endoscopist assessment.

CONCLUSION

A computer vision system based on the characterization of the polyp surface in white light accurately predicted colorectal polyp histology.

Towards a Computed-Aided Diagnosis System in Colonoscopy: Automatic Polyp Segmentation Using Convolution Neural Networks

Early diagnosis is essential for the successful treatment of bowel cancers including colorectal cancer (CRC), and capsule endoscopic imaging with robotic actuation can be a valuable diagnostic tool when combined with automated image analysis. We present a deep learning rooted detection and segmentation framework for recognizing lesions in colonoscopy and capsule endoscopy images. We restructure established convolution architectures, such as VGG and ResNets, by converting them into fully-connected convolution networks (FCNs), fine-tune them and study their capabilities for polyp segmentation and detection. We additionally use shape-from-shading (SfS) to recover depth and provide a richer representation of the tissue’s structure in colonoscopy images. Depth is incorporated into our network models as an additional input channel to the RGB information and we demonstrate that the resulting network yields improved performance. Our networks are tested on publicly available datasets and the most accurate segmentation model achieved a mean segmentation interception over union (IU) of 47.78% and 56.95% on the ETIS-Larib and CVC-Colon datasets, respectively. For polyp detection, the top performing models we propose surpass the current state-of-the-art with detection recalls superior to 90% for all datasets tested. To our knowledge, we present the first work to use FCNs for polyp segmentation in addition to proposing a novel combination of SfS and RGB that boosts performance.

A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images

Colorectal cancer (CRC) is the third cause of cancer death worldwide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for polyps and colonoscopy is the screening tool of choice. The main limitations of this screening procedure are polyp miss rate and the inability to perform visual assessment of polyp malignancy. These drawbacks can be reduced by designing decision support systems (DSS) aiming to help clinicians in the different stages of the procedure by providing endoluminal scene segmentation. Thus, in this paper, we introduce an extended benchmark of colonoscopy image segmentation, with the hope of establishing a new strong benchmark for colonoscopy image analysis research. The proposed dataset consists of 4 relevant classes to inspect the endoluminal scene, targeting different clinical needs. Together with the dataset and taking advantage of advances in semantic segmentation literature, we provide new baselines by training standard fully convolutional networks (FCNs). We perform a comparative study to show that FCNs significantly outperform, without any further postprocessing, prior results in endoluminal scene segmentation, especially with respect to polyp segmentation and localization.

Comparative Validation of Polyp Detection Methods in Video Colonoscopy: Results From the MICCAI 2015 Endoscopic Vision Challenge

Colonoscopy is the gold standard for colon cancer screening though some polyps are still missed, thus preventing early disease detection and treatment. Several computational systems have been proposed to assist polyp detection during colonoscopy but so far without consistent evaluation. The lack of publicly available annotated databases has made it difficult to compare methods and to assess if they achieve performance levels acceptable for clinical use. The Automatic Polyp Detection sub-challenge, conducted as part of the Endoscopic Vision Challenge (http://endovis.grand-challenge.org) at the international conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2015, was an effort to address this need. In this paper, we report the results of this comparative evaluation of polyp detection methods, as well as describe additional experiments to further explore differences between methods. We define performance metrics and provide evaluation databases that allow comparison of multiple methodologies. Results show that convolutional neural networks are the state of the art. Nevertheless, it is also demonstrated that combining different methodologies can lead to an improved overall performance.

ChRIS--A web-based neuroimaging and informatics system for collecting, organizing, processing, visualizing and sharing of medical data

The utility of web browsers for general purpose computing, long anticipated, is only now coming into fruition. In this paper we present a web-based medical image data and information management software platform called ChRIS ([Boston] Children's Research Integration System). ChRIS' deep functionality allows for easy retrieval of medical image data from resources typically found in hospitals, organizes and presents information in a modern feed-like interface, provides access to a growing library of plugins that process these data - typically on a connected High Performance Compute Cluster, allows for easy data sharing between users and instances of ChRIS and provides powerful 3D visualization and real time collaboration.

Effects of different surface modifying agents on the cytotoxic and antimicrobial properties of ZnO nanoparticles

Zinc oxide (ZnO) nanoparticles (NPs) have received considerable attention in the medical field because of their antibacterial properties, primarily for killing and reducing the activity of numerous microorganisms. The purpose of this study was to determine whether surface-modified ZnO NPs exhibit different properties compared with unmodified ZnO. The antimicrobial and cytotoxic properties of modified ZnO NPs as well as their effects on inflammatory cytokine production were evaluated. ZnO NPs were prepared using a wet chemical method. Then, the surfaces of these NPs were modified using 3-aminopropyltriethoxysilane (APTES) and dimethyl sulfoxide (DMSO) as modifying agents via a chemical hydrolysis method. According to infrared spectroscopy analysis (FTIR), the structure of the ZnO remained unchanged after modification. Antibacterial assays demonstrated that APTES modification is more effective at inducing an antimicrobial effect against Gram-negative bacteria than against Gram-positive bacteria. Cytotoxicity studies showed that cell viability was dose-dependent; moreover, pristine and APTES-modified ZnO exhibited low cytotoxicity, whereas DMSO-modified ZnO exhibited toxicity even at a low NP concentration. An investigation of inflammatory cytokine production demonstrated that the extent of stimulation was related to the ZnO NP concentration but not to the surface modification, except for IFN-γ and IL-10, which were not detected even at high NP concentrations.

Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps

BACKGROUND AND AIMS

Polyp miss-rate is a drawback of colonoscopy that increases significantly for small polyps. We explored the efficacy of an automatic computer-vision method for polyp detection.

METHODS

Our method relies on a model that defines polyp boundaries as valleys of image intensity. Valley information is integrated into energy maps that represent the likelihood of the presence of a polyp.

RESULTS

In 24 videos containing polyps from routine colonoscopies, all polyps were detected in at least one frame. The mean of the maximum values on the energy map was higher for frames with polyps than without (P < 0.001). Performance improved in high quality frames (AUC = 0.79 [95 %CI 0.70 - 0.87] vs. 0.75 [95 %CI 0.66 - 0.83]). With 3.75 set as the maximum threshold value, sensitivity and specificity for the detection of polyps were 70.4 % (95 %CI 60.3 % - 80.8 %) and 72.4 % (95 %CI 61.6 % - 84.6 %), respectively.

CONCLUSION

Energy maps performed well for colonic polyp detection, indicating their potential applicability in clinical practice.

Actividad reproductiva después del anestro inducido con altrenogest en hembras de <i>Tursiops truncatus</i> en cautiverio en ambiente marino

<p>La necesidad de reproducir delfín nariz de botella (<em>Tursiops truncatus</em>) en cautiverio se ha incrementado debido a las restricciones internacionales para su comercialización y por el riesgo y dificultad logística para el traslado de ejemplares. Por lo anterior, se hace importante conocer su biología reproductiva en cautiverio. El objetivo de este trabajo, fue conocer los indicadores post tratamiento con altrenogest (Regumate^®), de citología vaginal, niveles de estradiol y reinicio de la actividad reproductiva en cautiverio de hembras de <em>T truncatus</em> en ambiente marino. Por un año, 12 hembras recibieron diariamente una dosis de 0,07mg kg^-1 de altrenogest. Se realizaron un total 420 citologías vaginales, una diaria de cada hembra, para determinar el porcentaje de células cornificadas.  También se obtuvieron de la red vascular, 60 muestras  sanguíneas, en las que se determinó los niveles de estradiol. En cuanto a la citología vaginal, al cuarto día de retirar la administración de altrenogest, el porcentaje total de células cornificadas incrementó del 60% a 70% hasta el día nueve y continuó ascendiendo al 80% entre los días 12 al 19. Los niveles de estradiol, presentaron un rango de 16 a 114pg ml^-1. Se encontró una correlación (r = 0,7062 P&lt;0.05) positiva entre estos indicadores. Se concluye que es posible la manipulación con altrenogest y el monitoreo del ciclo estral de las hembras mediante técnicas simples como la citología vaginal para el diseño de protocolos de reproducción asistida específicos para grupos en cautiverio de <em>T truncatus.</em></p>

Impact of image preprocessing methods on polyp localization in colonoscopy frames

In this paper we present our image preprocessing methods as a key part of our automatic polyp localization scheme. These methods are used to assess the impact of different endoluminal scene elements when characterizing polyps. More precisely we tackle the influence of specular highlights, blood vessels and black mask surrounding the scene. Experimental results prove that the appropriate handling of these elements leads to a great improvement in polyp localization results.

WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians

We introduce in this paper a novel polyp localization method for colonoscopy videos. Our method is based on a model of appearance for polyps which defines polyp boundaries in terms of valley information. We propose the integration of valley information in a robust way fostering complete, concave and continuous boundaries typically associated to polyps. This integration is done by using a window of radial sectors which accumulate valley information to create WM-DOVA (Window Median Depth of Valleys Accumulation) energy maps related with the likelihood of polyp presence. We perform a double validation of our maps, which include the introduction of two new databases, including the first, up to our knowledge, fully annotated database with clinical metadata associated. First we assess that the highest value corresponds with the location of the polyp in the image. Second, we show that WM-DOVA energy maps can be comparable with saliency maps obtained from physicians' fixations obtained via an eye-tracker. Finally, we prove that our method outperforms state-of-the-art computational saliency results. Our method shows good performance, particularly for small polyps which are reported to be the main sources of polyp miss-rate, which indicates the potential applicability of our method in clinical practice.

Re-emergence of leishmaniasis in Spain: community outbreak in Madrid, Spain, 2009 to 2012

Since July 2009, there has been a community outbreak of leishmaniasis in the south-west area of the Madrid autonomous community, Spain, affecting residents from four towns that are geographically close together and share extensive park areas. As of December 2012, 446 cases were reported (6 in 2009, 97 in 2010, 196 in 2011 and 147 in 2012), a mean incidence rate of 22.2 per 100,000 inhabitants during July 2009 and December 2012. The mean age was 44 years (range: 2 months to 95 years); 61.0% were male. A total of 68 (15.2%) had immunosuppressive conditions; 160 (35.9%) had visceral leishmaniasis and 286 (64.1%) cutaneous. A total of 421 (94.4%) cases were confirmed. Leishmania infantum was identified as the agent. Monitoring revealed high densities of the vector Phlebotomus perniciosus. The surveillance system for canine leishmaniasis did not detect any increase in prevalence during the period. Environmental control measures have been taken, such as improvements in sanitation and disinsection in the risk areas and control of the overpopulation of Leporidae, as xenodiagnosis studies have shown that hares play a role as active reservoirs. This is the largest reported community outbreak of leishmaniasis in Europe. The discovery of the new reservoir stands out in the multifactorial aetiology of the outbreak. Epidemiological research and environmental intervention measures are continuing.

Late maternal hypothyroidism alters the expression of Camk4 in neocortical subplate neurons: a comparison with Nurr1 labeling

Maternal thyroid hormones (THs) are essential for normal offspring's neurodevelopment even after onset of fetal thyroid function. This is particularly relevant for preterm children who are deprived of maternal THs following birth, are at risk of suffering hypothyroxinemia, and develop attention-deficit/hyperactivity disorder. Expression of neocortical Ca(2+)/calmodulin kinase IV (Camk4), a genomic target of thyroid hormone, and nuclear receptor-related 1 protein (Nurr1), a postnatal marker of cortical subplate (SP) cells, was studied in euthyroid fetuses and in pups born to dams thyroidectomized in late gestation (LMH group, a model of prematurity), and compared with control and developmentally hypothyroid pups (C and MMI groups, respectively). In LMH pups, the extinction of heavy Camk4 expression in an SP was 1-2 days delayed postnatally compared with C pups. The heavy Camk4 and Nurr1 expression in the SP was prolonged in MMI pups, whereas heavy Camk4 and Nurr1 expression in layer VIb remains at P60. The abnormal expression of Camk4 in the cortical SP and in layer VIb might cause altered cortical connectivity affecting neocortical function.

The hare (Lepus granatensis) as potential sylvatic reservoir of Leishmania infantum in Spain

Xenodiagnosis of Leishmania infection in hares (Lepus granatensis) from a focus of human leishmaniasis in Fuenlabrada at southwestern Madrid region (Spain) proved that they are infective to Phlebotomus perniciosus. Molecular characterization of isolates obtained from sand flies infected after xenodiagnosis demonstrates that hares were infected by Leishmania infantum. This is the first evidence of the transmission of L. infantum from hares to sand flies. Moreover the results confirm the role that these animals can play as wild reservoirs of leishmaniasis for the recent outbreak of visceral leishmaniasis in Madrid.

Liquid chromatography coupled to ion trap-tandem mass spectrometry to evaluate juvenile hormone III levels in bee hemolymph from Nosema spp. infected colonies

It has been described a fast, simple and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to measure juvenile hormone III (JH III), which was used to study of the effects of Nosema spp. infection on JH III levels in bee hemolymph. Honey bee hemolymph was extracted by centrifugation and mixed with a solution of phenylthiourea in methanol. This mixture was then centrifuged and the supernatant removed and evaporated to dryness. The residue was reconstituted in methanol containing the internal standard (methoprene) and injected onto an LC-MS/MS (ion-trap) system coupled to electrospray ionization (ESI) in positive mode. Chromatography was performed on a Synergi Hydro-RP column (4 μm, 30 mm × 4.60 mm i.d.) using a mobile phase of 20 mM ammonium formate and methanol in binary gradient elution mode. The method was fully validated and it was found to be selective, linear from 15 to 14,562 pg/μL, precise and accurate, with %RSD values below 5%. The limits of detection and quantification were: LOD, 6 pg/μL; LOQ, 15 pg/μL. Finally, the proposed LC-MS/MS method was used to analyze JH III levels in the hemolymph of worker honey bees (Apis mellifera iberiensis) experimentally infected with different Nosema spp. (Nosema apis, Spanish and Dutch Nosema ceranae strains). The highest concentrations of JH III were detected in hemolymph from bees infected with Spanish N. ceranae.

Identification of novel GH-regulated genes in C2C12 cells

Growth hormone (GH) is the main regulator of longitudinal growth before puberty, and treatment with human recombinant (rh) GH can increase muscle strength. Nevertheless, molecular mechanisms responsible remain mostly unknown. Many physiological effects of GH require hormone-mediated changes in gene expression. In an attempt to gain insight into the mechanism of GH action in muscle cells we evaluated the effects of rhGH on gene expression profile in a murine skeletal muscle cell line C2C12. The objective of the work was to identify changes in gene expression in the murine skeletal muscle cell line C2C12 after rGH treatment using microarray assays. C2C12 murine skeletal muscle cell cultures were differentiated during 4 days. After 16 h growing in serum-free medium, C2C12 myotubes were stimulated during 6 h with 500 ng/ml rhGH. Four independent sets of experiments were performed to identify GH-regulated genes. Total RNA was isolated and subjected to analysis. To validate changes candidate genes were analyzed by real-time quantitative polymerase chain reaction. One hundred and fifty-four differentially expressed genes were identified; 90 upregulated and 64 downregulated. Many had not been previously identified as GH-responsive. Real-time PCR in biological replicates confirmed the effect of rGH on 15 genes: Cish, Serpina3g, Socs2, Bmp4, Tnfrsf11b, Rgs2, Tgfbr3, Ugdh, Npy1r, Gbp6, Tgfbi, Tgtp, Btc, Clec3b, and Bcl6. This study shows modifications in the gene expression profile of the C2C12 cell line after rhGH exposure. In vitro and gene function analysis revealed genes involved in skeletal and muscle system as well as cardiovascular system development and function.

Determination of tylosins A, B, C and D in bee larvae by liquid chromatography coupled to ion trap-tandem mass spectrometry

A LC-MS/MS method has been developed to simultaneously quantify tylosins A, B, C and D in bee larvae, compounds currently used to treat one of the most lethal diseases affecting honey bees around the world, American Foulbrood (AFB). The influence of different aqueous media, temperature and light exposure on the stability of these four compounds was studied. The analytes were extracted from bee larvae with methanol and chromatographic separation was achieved on a Luna C(18) (150 × 4.6 mm i.d.) using a ternary gradient composed of a diluted formic acid, methanol and acetonitrile mobile phase. To facilitate sampling, bee larvae were initially dried at 60°C for 4h and afterwards, they were diluted to avoid problems of pressure. MSD-Ion Trap detection was employed with electrospray ionization (ESI). The calibration curves were linear over a wide range of concentrations and the method was validated as sensitive, precise and accurate within the limits of quantification (LOQ, 1.4-4.0 ng/g). The validated method was successfully employed to study bee larvae in field tests of bee hives treated with two formulations containing tylosin. In both cases it was evident that the minimal inhibitory concentration (MIC) had been reached.

Overview of pesticide residues in stored pollen and their potential effect on bee colony (Apis mellifera) losses in Spain

In the last decade, an increase in honey bee (Apis mellifera L.) colony losses has been reported in several countries. The causes of this decline are still not clear. This study was set out to evaluate the pesticide residues in stored pollen from honey bee colonies and their possible impact on honey bee losses in Spain. In total, 1,021 professional apiaries were randomly selected. All pollen samples were subjected to multiresidue analysis by gas chromatography-mass spectrometry (MS) and liquid chromatography-MS; moreover, specific methods were applied for neonicotinoids and fipronil. A palynological analysis also was carried out to confirm the type of foraging crop. Pesticide residues were detected in 42% of samples collected in spring, and only in 31% of samples collected in autumn. Fluvalinate and chlorfenvinphos were the most frequently detected pesticides in the analyzed samples. Fipronil was detected in 3.7% of all the spring samples but never in autumn samples, and neonicotinoid residues were not detected. More than 47.8% of stored pollen samples belonged to wild vegetation, and sunflower (Heliantus spp.) pollen was only detected in 10.4% of the samples. A direct relation between pesticide residues found in stored pollen samples and colony losses was not evident accordingly to the obtained results. Further studies are necessary to determine the possible role of the most frequent and abundant pesticides (such as acaricides) and the synergism among them and with other pathogens more prevalent in Spain.

Development and validation of a liquid chromatography-fluorescence-mass spectrometry method to measure glyphosate and aminomethylphosphonic acid in rat plasma

A simple and fast method has been developed and validated to measure glyphosate (GLYP) and aminomethylphosphonic acid (AMPA) in rat plasma based on reversed-phase high performance liquid chromatography (RP-HPLC) coupled to fluorescence (FLD) and electrospray ionization mass spectrometry (ESI-MS) detection. After protein precipitation with acetonitrile, GLYP and AMPA were derivatized with 9-fluorenylmethylchloroformate (FMOC-Cl) and then separated on a C(12) column (250mm×4.60mm i.d.) using a gradient of an ammonium formate (20mM, pH 8.5) and acetonitrile mobile phase. Selected ion monitoring (SIM) mode of the MS was used to obtain maximum sensitivity when quantifying GLYP and AMPA. The validation shows the method to be consistent and reliable, with an intra- and inter-day precision for GLYP and AMPA>9% for both detectors. For both compounds the accuracy ranged from 2.1% to 7.8% for the intra-day readings, and from 4.1% to 8.6% for the inter-day values. The efficacy of GLYP extraction ranged from 87% to 93% and it was between 76% and 88% for AMPA. Moreover, the limits of quantification (LOQ) for GLYP and AMPA were 5 and 10ng/mL, respectively with FLD, and 0.4 and 2ng/mL with ESI-MS. The method was successfully applied to simultaneously measure both compounds in rat plasma samples several days after oral administration of glyphosate.

Coronary artery perforations in the contemporary interventional era

BACKGROUND

Coronary perforations represent a serious complication of percutaneous coronary intervention (PCI).

METHODS

We performed a retrospective analysis of documented coronary perforations at Massachusetts General Hospital from 2000 to 2008. Medical records review and detailed angiographic analysis were performed in all patients.

RESULTS

Sixty-eight cases of coronary perforation were identified from a total of 14,281 PCIs from March 2000 to March 2008 representing an overall incidence of 0.48%. The study cohort was predominantly male (61.8%), mean age 71+/-11 years with 78% representing acute cases (unstable angina: 36.8%, NSTEMI: 30.9%, STEMI: 10.3%). Coronary artery perforation occurred as a complication of wire manipulation in 45 patients (66.2%) with 88.9% of this group being hydrophilic wires, of coronary stenting in 11 (16.2%), of angioplasty alone in 6 (8.8%), and of rotational atherectomy in 8 (11.8%). The perforation was sealed with an angioplasty balloon alone in 16 patients (23.5%), and with stents in 14 patients (20.6%) (covered stents: 11.8% and noncovered stents: 8.8%). Emergency CABG was performed in 2 patients (2.9%). Five patients (7.4%) developed periprocedural MI. The in-hospital mortality rate was 5.9% in the study cohort.

CONCLUSION

Coronary artery perforation as a complication of PCI is still rare as demonstrated in our series with an incidence of 0.48%. The predominant cause of coronary perforations in the current era of PCI is wire injury.

Generation of J(0) Bessel beams with controlled spatial coherence features

An alternative method to generate J(0) Bessel beams with controlled spatial partial coherence properties is introduced. Far field diffraction from a discrete number of source points on an annular region is calculated. The average for different diffracted fields produced at several rotation angles is numerically calculated and experimentally detected. Theoretical and experimental results show that for this particular case, the J(0) Bessel beam is a limit when the number of points tends towards infinity and the associated complex degree of coherence is also a function of the number of points.

Profile and relative concentrations of fatty acids in corn and soybean seeds from transgenic and isogenic crops

In this work 44 fatty acids, which were analyzed as methyl esters by GC/MS in scan mode, have been determined in genetically modified corn and soybean seeds. Their relative concentrations have been compared with those of isogenic lines grown in the same conditions. Studied compounds comprised saturated and unsaturated fatty acids, including cis/trans isomers and minor fatty acids. A classical soxhlet extraction and an accelerated solvent extraction have been assayed to extract the fatty compounds from seeds and the GC separation has been carried out on a biscyanopropylpolysiloxane chromatographic column. Soxhlet extraction was selected as the most convenient and applied to compare the samples. Specific compounds, which could denote the origin of the crop have not been observed, but for some sample pairs, significant differences have been found in relation to the percentage of certain acids; the highest differences for major acids were 4.1% in corn and 4.8% in soybean. The concentrations of long chain acids such as 24:0, 26:0 and 28:0 were higher in some isogenic lines whereas the concentrations of short chain acids such as 6:0, 8:0, 9:0, 10:0 and 12:0 were higher in their transgenic counterparts.