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La sociedad de Obstetricia y Ginecología me dió una carta, firmada por el doctor Rafael Ramírez, Presidente en esa época y con ella me presenté a las Sociedades similares en los países de habla castellana, visitados durante el viaje que acabo de realizar.

Llámase desde la fecha Sociedad Colombiana de Obtetricia Sicosmática a la Sociedad científica cuya fundación fue propuesta en Bogotá el día 7 de febrero de 1959, por los participantes y asistentes al Primer Simposio Colombiano sobre Métodos Sicofísicos para el parto indoloro, reunido en el Salón de Conferencias de la Facultad de Medicina de la Universidad Javeriana.

Measurement(s) Cognition • Psychiatric Diagnosis • Development Technology Type(s) MRI • phenotypic battery • actigraphy • laboratory analysis Sample Characteristic - Organism Homo sapien Sample Characteristic - Environment Community-ascertained non-diagnostic sample Sample Characteristic - Location United States

Abstract Pancreas volume is reduced in individuals with diabetes and in autoantibody positive individuals at high risk for developing type 1 diabetes (T1D). Studies investigating pancreas volume are underway to assess pancreas volume in large clinical databases and studies, but manual pancreas annotation is time-consuming and subjective, preventing extension to large studies and databases. This study develops deep learning for automated pancreas volume measurement in individuals with diabetes. A convolutional neural network was trained using manual pancreas annotation on 160 abdominal magnetic resonance imaging (MRI) scans from individuals with T1D, controls, or a combination thereof. Models trained using each cohort were then tested on scans of 25 individuals with T1D. Deep learning and manual segmentations of the pancreas displayed high overlap (Dice coefficient = 0.81) and excellent correlation of pancreas volume measurements (R2 = 0.94). Correlation was highest when training data included individuals both with and without T1D. The pancreas of individuals with T1D can be automatically segmented to measure pancreas volume. This algorithm can be applied to large imaging datasets to quantify the spectrum of human pancreas volume.

Brain extraction (a.k.a. skull stripping) is a fundamental step in the neuroimaging pipeline as it can affect the accuracy of downstream preprocess such as image registration, tissue classification, etc. Most brain extraction tools have been designed for and applied to human data and are often challenged by non-human primates (NHP) data. Amongst recent attempts to improve performance on NHP data, deep learning models appear to outperform the traditional tools. However, given the minimal sample size of most NHP studies and notable variations in data quality, the deep learning models are very rarely applied to multi-site samples in NHP imaging. To overcome this challenge, we used a transfer-learning framework that leverages a large human imaging dataset to pretrain a convolutional neural network (i.e. U-Net Model), and then transferred this to NHP data using a small NHP training sample. The resulting transfer-learning model converged faster and achieved more accurate performance than a similar U-Net Model trained exclusively on NHP samples. We improved the generalizability of the model by upgrading the transfer-learned model using additional training datasets from multiple research sites in the Primate Data-Exchange (PRIME-DE) consortium. Our final model outperformed brain extraction routines from popular MRI packages (AFNI, FSL, and FreeSurfer) across a heterogeneous sample from multiple sites in the PRIME-DE with less computational cost (20 s~10 min). We also demonstrated the transfer-learning process enables the macaque model to be updated for use with scans from chimpanzees, marmosets, and other mammals (e.g. pig). Our model, code, and the skull-stripped mask repository of 136 macaque monkeys are publicly available for unrestricted use by the neuroimaging community at https://github.com/HumanBrainED/NHP-BrainExtraction.

New large neuroimaging studies, such as the Adolescent Brain Cognitive Development study (ABCD) and Human Connectome Project (HCP) Development studies are adopting a new T1-weighted imaging sequence with prospective motion correction (PMC) in favor of the more traditional 3-Dimensional Magnetization-Prepared Rapid Gradient-Echo Imaging (MPRAGE) sequence. Here, we used a developmental dataset (ages 5–21, N = 348) from the Healthy Brain Network (HBN) Initiative to directly compare two widely used MRI structural sequences: one based on the Human Connectome Project (MPRAGE) and another based on the ABCD study (MPRAGE+PMC). We aimed to determine if the morphometric measurements obtained from both protocols are equivalent or if one sequence has a clear advantage over the other. The sequences were also compared through quality control measurements. Inter- and intra-sequence reliability were assessed with another set of participants (N = 71) from HBN that performed two MPRAGE and two MPRAGE+PMC sequences within the same imaging session, with one MPRAGE (MPRAGE1) and MPRAGE+PMC (MPRAGE+PMC1) pair at the beginning of the session and another pair (MPRAGE2 and MPRAGE+PMC2) at the end of the session. Intraclass correlation coefficients (ICC) scores for morphometric measurements such as volume and cortical thickness showed that intra-sequence reliability is the highest with the two MPRAGE+PMC sequences and lowest with the two MPRAGE sequences. Regarding inter-sequence reliability, ICC scores were higher for the MPRAGE1 - MPRAGE+PMC1 pair at the beginning of the session than the MPRAGE1 - MPRAGE2 pair, possibly due to the higher motion artifacts in the MPRAGE2 run. Results also indicated that the MPRAGE+PMC sequence is robust, but not impervious, to high head motion. For quality control metrics, the traditional MPRAGE yielded better results than MPRAGE+PMC in 5 of the 8 measurements. In conclusion, morphometric measurements evaluated here showed high inter-sequence reliability between the MPRAGE and MPRAGE+PMC sequences, especially in images with low head motion. We suggest that studies targeting hyperkinetic populations use the MPRAGE+PMC sequence, given its robustness to head motion and higher reliability scores. However, neuroimaging researchers studying non-hyperkinetic participants can choose either MPRAGE or MPRAGE+PMC sequences, but should carefully consider the apparent tradeoff between relatively increased reliability, but reduced quality control metrics when using the MPRAGE+PMC sequence.

Data sharing is recognized as a way to promote scientific collaboration and reproducibility, but some are concerned over whether research based on shared data can achieve high impact. Here, the authors show that neuroimaging papers using shared data are no less likely to appear in top-ranked journals.

Summary: Complementing long-standing traditions centered on histology, fMRI approaches are rapidly maturing in delineating brain areal organization at the macroscale. The non-human primate (NHP) provides the opportunity to overcome critical barriers in translational research. Here, we establish the data requirements for achieving reproducible and internally valid parcellations in individuals. We demonstrate that functional boundaries serve as a functional fingerprint of the individual animals and can be achieved under anesthesia or awake conditions (rest, naturalistic viewing), though differences between awake and anesthetized states precluded the detection of individual differences across states. Comparison of awake and anesthetized states suggested a more nuanced picture of changes in connectivity for higher-order association areas, as well as visual and motor cortex. These results establish feasibility and data requirements for the generation of reproducible individual-specific parcellations in NHPs, provide insights into the impact of scan state, and motivate efforts toward harmonizing protocols. : Noninvasive fMRI in macaques is an essential tool in translation research. Xu et al. establish the individual functional parcellation of the macaque cortex and demonstrate that brain organization is unique, reproducible, and valid, serving as a fingerprint for an individual macaque. Keywords: macaque, parcellation, cortical areas, gradient, functional connectivity

The goal of the present study was to apply deep learning algorithms to identify autism spectrum disorder (ASD) patients from large brain imaging dataset, based solely on the patients brain activation patterns. We investigated ASD patients brain imaging data from a world-wide multi-site database known as ABIDE (Autism Brain Imaging Data Exchange). ASD is a brain-based disorder characterized by social deficits and repetitive behaviors. According to recent Centers for Disease Control data, ASD affects one in 68 children in the United States. We investigated patterns of functional connectivity that objectively identify ASD participants from functional brain imaging data, and attempted to unveil the neural patterns that emerged from the classification. The results improved the state-of-the-art by achieving 70% accuracy in identification of ASD versus control patients in the dataset. The patterns that emerged from the classification show an anticorrelation of brain function between anterior and posterior areas of the brain; the anticorrelation corroborates current empirical evidence of anterior-posterior disruption in brain connectivity in ASD. We present the results and identify the areas of the brain that contributed most to differentiating ASD from typically developing controls as per our deep learning model. Keywords: Autism, fMRI, ABIDE, Resting state, Deep learning

Naturalistic viewing paradigms such as movies have been shown to reduce participant head motion and improve arousal during fMRI scanning relative to task-free rest, and have been used to study both functional connectivity and stimulus-evoked BOLD-signal changes. These task-based hemodynamic changes are synchronized across subjects and involve large areas of the cortex, and it is unclear whether individual differences in functional connectivity are enhanced or diminished under such naturalistic conditions. This work first aims to characterize variability in BOLD-signal based functional connectivity (FC) across 2 distinct movie conditions and eyes-open rest (n=31 healthy adults, 2 scan sessions each). We found that movies have higher within- and between-subject correlations in cluster-wise FC relative to rest. The anatomical distribution of inter-individual variability was similar across conditions, with higher variability occurring at the lateral prefrontal lobes and temporoparietal junctions. Second, we used an unsupervised test-retest matching algorithm that identifies individual subjects from within a group based on FC patterns, quantifying the accuracy of the algorithm across the three conditions. The movies and resting state all enabled identification of individual subjects based on FC matrices, with accuracies between 61% and 100%. Overall, pairings involving movies outperformed rest, and the social, faster-paced movie attained 100% accuracy. When the parcellation resolution, scan duration, and number of edges used were increased, accuracies improved across conditions, and the pattern of movies>rest was preserved. These results suggest that using dynamic stimuli such as movies enhances the detection of FC patterns that are unique at the individual level.

Table of contents I1 Introduction to the 2015 Brainhack Proceedings R. Cameron Craddock, Pierre Bellec, Daniel S. Margules, B. Nolan Nichols, Jörg P. Pfannmöller A1 Distributed collaboration: the case for the enhancement of Brainspell’s interface AmanPreet Badhwar, David Kennedy, Jean-Baptiste Poline, Roberto Toro A2 Advancing open science through NiData Ben Cipollini, Ariel Rokem A3 Integrating the Brain Imaging Data Structure (BIDS) standard into C-PAC Daniel Clark, Krzysztof J. Gorgolewski, R. Cameron Craddock A4 Optimized implementations of voxel-wise degree centrality and local functional connectivity density mapping in AFNI R. Cameron Craddock, Daniel J. Clark A5 LORIS: DICOM anonymizer Samir Das, Cécile Madjar, Ayan Sengupta, Zia Mohades A6 Automatic extraction of academic collaborations in neuroimaging Sebastien Dery A7 NiftyView: a zero-footprint web application for viewing DICOM and NIfTI files Weiran Deng A8 Human Connectome Project Minimal Preprocessing Pipelines to Nipype Eric Earl, Damion V. Demeter, Kate Mills, Glad Mihai, Luka Ruzic, Nick Ketz, Andrew Reineberg, Marianne C. Reddan, Anne-Lise Goddings, Javier Gonzalez-Castillo, Krzysztof J. Gorgolewski A9 Generating music with resting-state fMRI data Caroline Froehlich, Gil Dekel, Daniel S. Margulies, R. Cameron Craddock A10 Highly comparable time-series analysis in Nitime Ben D. Fulcher A11 Nipype interfaces in CBRAIN Tristan Glatard, Samir Das, Reza Adalat, Natacha Beck, Rémi Bernard, Najmeh Khalili-Mahani, Pierre Rioux, Marc-Étienne Rousseau, Alan C. Evans A12 DueCredit: automated collection of citations for software, methods, and data Yaroslav O. Halchenko, Matteo Visconti di Oleggio Castello A13 Open source low-cost device to register dog’s heart rate and tail movement Raúl Hernández-Pérez, Edgar A. Morales, Laura V. Cuaya A14 Calculating the Laterality Index Using FSL for Stroke Neuroimaging Data Kaori L. Ito, Sook-Lei Liew A15 Wrapping FreeSurfer 6 for use in high-performance computing environments Hans J. Johnson A16 Facilitating big data meta-analyses for clinical neuroimaging through ENIGMA wrapper scripts Erik Kan, Julia Anglin, Michael Borich, Neda Jahanshad, Paul Thompson, Sook-Lei Liew A17 A cortical surface-based geodesic distance package for Python Daniel S Margulies, Marcel Falkiewicz, Julia M Huntenburg A18 Sharing data in the cloud David O’Connor, Daniel J. Clark, Michael P. Milham, R. Cameron Craddock A19 Detecting task-based fMRI compliance using plan abandonment techniques Ramon Fraga Pereira, Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi A20 Self-organization and brain function Jörg P. Pfannmöller, Rickson Mesquita, Luis C.T. Herrera, Daniela Dentico A21 The Neuroimaging Data Model (NIDM) API Vanessa Sochat, B Nolan Nichols A22 NeuroView: a customizable browser-base utility Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi A23 DIPY: Brain tissue classification Julio E. Villalon-Reina, Eleftherios Garyfallidis

Working memory (WM) is central to the acquisition of knowledge and skills throughout childhood and adolescence. While numerous behavioral and task-based functional magnetic resonance imaging (fMRI) studies have examined WM development, few have used resting-state fMRI (R-fMRI). Here, we present a systematic R-fMRI examination of age-related differences in the neural indices of verbal WM performance in a cross-sectional pediatric sample (ages: 7–17; n = 68), using data-driven approaches. Verbal WM capacity was measured with the digit span task, a commonly used educational and clinical assessment. We found distinct neural indices of digit span forward (DSF) and backward (DSB) performance, reflecting their unique neuropsychological demands. Regardless of age, DSB performance was related to intrinsic properties of brain areas previously implicated in attention and cognitive control, while DSF performance was related to areas less commonly implicated in verbal WM storage (precuneus, lateral visual areas). From a developmental perspective, DSF exhibited more robust age-related differences in brain–behavior relationships than DSB, and implicated a broader range of networks (ventral attention, default, somatomotor, limbic networks) – including a number of regions not commonly associated with verbal WM (angular gyrus, subcallosum). These results highlight the importance of examining the neurodevelopment of verbal WM and of considering regions beyond the “usual suspects”.

This paper broadly reviews the study of mild traumatic brain injury (mTBI), across the spectrum of neuroimaging modalities. Among the range of imaging methods, however, magnetic resonance imaging (MRI) is unique in its applicability to studying both structure and function. Thus we additionally performed meta-analyses of MRI results to examine 1) the issue of anatomical variability and consistency for functional MRI (fMRI) findings, 2) the analogous issue of anatomical consistency for white-matter findings, and 3) the importance of accounting for the time post injury in diffusion weighted imaging reports. As we discuss, the human neuroimaging literature consists of both small and large studies spanning acute to chronic time points that have examined both structural and functional changes with mTBI, using virtually every available medical imaging modality. Two key commonalities have been used across the majority of imaging studies. The first is the comparison between mTBI and control populations. The second is the attempt to link imaging results with neuropsychological assessments. Our fMRI meta-analysis demonstrates a frontal vulnerability to mTBI, demonstrated by decreased signal in prefrontal cortex compared to controls. This vulnerability is further highlighted by examining the frequency of reported mTBI white matter anisotropy, in which we show a strong anterior-to-posterior gradient (with anterior regions being more frequently reported in mTBI). Our final DTI meta-analysis examines a debated topic arising from inconsistent anisotropy findings across studies. Our results support the hypothesis that acute mTBI is associated with elevated anisotropy values and chronic mTBI complaints are correlated with depressed anisotropy. Thus, this review and set of meta-analyses demonstrate several important points about the ongoing use of neuroimaging to understand the functional and structural changes that occur throughout the time course of mTBI recovery. Based on the complexity of mTBI, however, much more work in this area is required to characterize injury mechanisms and recovery factors and to achieve clinically-relevant capabilities for diagnosis.

Blood oxygenation level dependent (BOLD)–based functional MRI is a widely utilized neuroimaging technique for mapping brain function. Hematocrit (HCT), a global hematologic marker of the amount of hemoglobin in blood, is known to impact task-evoked BOLD activation. Yet, its impact on resting-state fMRI (R-fMRI) measures has not been characterized. We address this gap by testing for associations between HCT level and inter-individual variation in commonly employed R-fMRI indices of intrinsic brain function from 45 healthy adults. Given known sex differences in HCT, we also examined potential sex differences. Variation in baseline HCT among individuals were associated with regional differences in four of the six intrinsic brain indices examined. Portions of the default (anterior cingulate cortex/medial prefrontal cortex: ACC/MPFC), dorsal attention (intraparietal sulcus), and salience network (insular and opercular cortex) showed relationships with HCT for two measures. The relationships within MPFC, as well as visual and cerebellar networks, were modulated by sex. These results suggest that inter-individual variations in HCT can serve as a source of variations in R-fMRI derivatives at a regional level. Future work is needed to delineate whether this association is attributable to neural or non-neuronal source of variations and whether these effects are related to acute or chronic differences in HCT level.

Effective visualization is central to the exploration and comprehension of brain imaging data. While MRI data are acquired in three-dimensional space, the methods for visualizing such data have rarely taken advantage of three-dimensional stereoscopic technologies. We present here results of stereoscopic visualization of clinical data, as well as an atlas of whole-brain functional connectivity. In comparison with traditional 3D rendering techniques, we demonstrate the utility of stereoscopic visualizations to provide an intuitive description of the exact location and the relative sizes of various brain landmarks, structures and lesions. In the case of resting state fMRI, stereoscopic 3D visualization facilitated comprehension of the anatomical position of complex large-scale functional connectivity patterns. Overall, stereoscopic visualization improves the intuitive visual comprehension of image contents, and brings increased dimensionality to visualization of traditional MRI data, as well as patterns of functional connectivity.

Graph theoretical explorations of functional interactions within the human connectome, are rapidly advancing our understanding of brain architecture. In particular, global and regional topological parameters are increasingly being employed to quantify and characterize inter-individual differences in human brain function. Head motion remains a significant concern in the accurate determination of resting-state fMRI based assessments of the connectome, including those based on graph theoretical analysis (e.g., motion can increase local efficiency, while decreasing global efficiency and small-worldness). This study provides a comprehensive examination of motion correction strategies on the relationship between motion and commonly used topological parameters. At the individual-level, we evaluated different models of head motion regression and scrubbing, as well as the potential benefits of using partial correlation (estimated via graphical lasso) instead of full correlation. At the group-level, we investigated the utility of regression of motion and mean intrinsic functional connectivity before topological parameters calculation and/or after. Consistent with prior findings, none of the explicit motion-correction approaches at individual-level were able to remove motion relationships for topological parameters. Global signal regression (GSR) emerged as an effective means of mitigating relationships between motion and topological parameters; though at the risk of altering the connectivity structure and topological hub distributions when higher densities graphs are employed (e.g., > 6%). Group-level analysis correction for motion was once again found to be a crucial step. Finally, similar to recent work, we found a constellation of findings suggestive of the possibility that some of the motion-relationships detected may reflect neural or trait signatures of motion, rather than simply motion-induced artifact.

The aim was to test the use of eye-tracking methodology for the early detection of ASD in a task of association between unfamiliar objects and pseudowords. Significant differences were found between ASD (n = 57) and TD (n = 57) Spanish speaking toddlers in the number and time of fixation. The TD children showed more and longer fixations on eyes and mouth while the ASD children attended almost exclusively to objects, making it difficult to integrate lexical and phonological information. Moreover, the TD toddlers looked at the mouth when the pseudoword was produced while the ASD toddlers did not. Gaze fixation on eyes and mouth during word learning recorded by eye-tracking may be used as a biomarker for the early diagnosis of ASD., (© 2023. The Author(s).)

Background : Children with autism spectrum disorder (ASD) show certain characteristics in visual attention. These may generate differences with non-autistic children in the integration of relevant social information to set the basis of communication. Reliable and objective measurement of these characteristics in a language learning context could contribute to a more accurate early diagnosis of ASD. Gaze following and pupil dilation are being studied as possible reliable measures of visual attention for the early detection of ASD. The eye-tracking methodology allows objective measurement of these biomarkers. The aim of this study is to determine whether measurements of gaze following and pupillary dilation in a linguistic interaction task are potential objective biomarkers for the early diagnosis of ASD. Method : A group of 20 children between 17 and 24 months of age, made up of 10 neurotypical children (NT) and 10 children with an increased likelihood of developing ASD were paired together according to chronological age. A human face on a monitor pronounced pseudowords associated with pseudo-objects. Gaze following and pupil dilation were registered during the task These measurements were captured using eye-tracking methodology. Results : Significant statistical differences were found in the time of gaze fixation on the human face and on the object, as well as in the number of gazes. Children with an increased possibility of developing ASD showed a slightly higher pupil dilation than NT children. However, this difference was not statistically significant. Nevertheless, their pupil dilation was uniform throughout the different periods of the task while NT participants showed greater dilation on hearing the pseudoword. Conclusions : The fixing and the duration of gaze, objectively measured by a Tobii eye-tracking system, could be considered as potential biomarkers for early detection of ASD. Additionally, pupil dilation measurement could reflect differential activation patterns during word processing in possible ASD toddlers and NT toddlers.

The use of the task-evoked pupillary responses (TEPRs) methodology is emerging in the psycholinguistics literature, as a sensitive, reliable and dynamic psychophysiological measure of the cognitive effort produced by various aspects of language processing. This preliminary study aimed to assess the functionality and effectiveness of a TEPRs design for measuring the cognitive effort required for the processing and spontaneous (non-explicitly prompted) short-term retention of novel phonological forms presented auditorily. Twenty-four young adult participants (aged 19-28 years, M = 20.3, SD = 2.13) were auditorily presented with a series of pseudowords differing in their number of syllables and their syllabic complexity. Then, they were asked to produce a response to a delayed pseudoword-color matching task aimed to induce the short-term retention of the novel forms. Results on the size and timing of the TEPRs reveal a significant pupillary activation, starting immediately after the presentation of the auditory stimuli, peaking at 1080 ms and not subsiding significantly during the protracted retention period. Moreover, the differential complexity of the novel words phonology significantly affected pupillary activation. Overall, these preliminary results point to the effectiveness of pupillometry as a technique for capturing the cognitive effort entailed in the short-term maintenance of novel word forms in the phonological loop, a process deemed crucial in the everyday novel word learning process. Results are discussed in view of future research that could establish and extend their implications.

A novel and rapid approach to quantify chloride concentration in sweat for early detection of cystic fibrosis (CF) is shown in this work. Disposable screen-printed sensor (SPS) devices capable to induce sweat and measure the chloride concentration are presented. Pilocarpine, which was forced into de skin by means of iontophoresis, has been used to stimulate the sweat glands. Chloride concentration has been directly measured on the skin by potentiometry. The performance of the devices has been tested in synthetic samples, obtaining good agreement with the Nernst equation. Sensors reproducibility has been analyzed in terms of residual standard deviation (RSD), obtaining a value of 8% (n=6 and alpha=0.05). Finally, the application of these sensors in several volunteers has been carried out. The results were compared with the method generally used in hospitals, obtaining deviations minor than 8%.

Two hundred and sixty-eight Cucumis melo and wild relative accessions were evaluated for resistance to Cucumber mosaic virus (CMV), Papaya ringspot virus strain W (PRSV-W), Watermelon mosaic virus (WMV), and Zucchini yellow mosaic virus (ZYMV). Symptom development and systemic infection based on double antibody sandwich enzyme-linked immunosorbent assays were monitored. Sources of resistance were scarce. However, a number of them were found among the C. melo accessions tested. Thus, the accession C-189 behaved similarly to PI 161375 and showed resistance to "common" CMV strains although it was infected by a "song" type CMV. For WMV, the accessions C-768 and C-425, although infected, exhibited very mild symptoms, and recovery from infection occurred in some occasions in the former. A similar trait was also found in C-105, although in this case symptoms rarely appear and part of the plants are not infected. In addition, C-105 was highly resistant to virus transmission by Aphis gossypii, similarly to PI 161375. Accessions C-885 and C-769 exhibited resistance to PRSV-W, WMV, and ZYMV; therefore they are potential sources of multiple resistance. Resistance traits were also found in wild relatives that could be exploited when interspecific barriers with C. melo can be circumvented.

Since 1997, yellowing disease outbreaks have occurred in tomato (Lycopersicon esculentum) crops in southern Spain. The outbreaks were associated with high populations of the whitefly Bemisia tabaci. Symptoms consisted mainly of interveinal yellowing that developed initially on lower leaves and then progressed to the upper part of the plant. Affected plants were less vigorous and yielded less due to reduced fruit growth and delayed ripening. During 1998 and 1999, the yellowing disease was widespread and occurred at high incidences in the Málaga province. The disease agent was readily transmissible from tomato to tomato by B. tabaci biotype Q. Samples from symptomatic tomato plants were analyzed and shown to be infected with Tomato chlorosis virus (ToCV) (genus Crinivirus, family Closteroviridae). This is the first report of ToCV epidemics in Europe.

ABSTRACT A progressive displacement of tomato yellow leaf curl virus (TYLCV)-Sr by TYLCV-Is was observed in tomato epidemics in southern Spain based on incidence data of both virus species obtained during surveys conducted between 1996 and 1998. Ecological factors that might be involved in such a displacement, such as competition of TYLCV-Sr and TYLCV-Is in tomato, transmission by local biotypes (B and Q) of Bemisia tabaci, and presence in weeds and alternate crops, have been analyzed. No selective advantage is observed for TYLCV-Sr or TYLCV-Is in tomato plants either infected via Agrobacterium tumefaciens or via B. tabaci. However, TYLCV-Is is more efficiently vectored by local biotypes of B. tabaci; and common bean, a bridge crop between tomato crops, is a host for TYLCV-Is but not TYLCV-Sr. Therefore, common bean acts as a reservoir for TYLCV-Is. These two factors are probably responsible for the displacement of TYLCV-Sr by TYLCV-Is as the causative agent of epidemics in tomato in southern Spain.

Introduction and Objectives: Because left ventricular mass is associated with an increase in the risk of morbidity and mortality of cardiovascular diseases in the general population having the electrocardiogram as an accessible and inexpensive method for the diagnosis of left ventricular hypertrophy, we decided to calculate the sensitivity and specificity of 5 electrocardiographic criteria for the diagnosis of left ventricular hypertrophy and to compare the results of the original authors to ours., Patients and Methods: 135 patients were evaluated; 46 patients were excluded by the following criteria: chronic obstructive pulmonary disease, complete left or right bundle branch block, cardiovascular ischemic disease or Wolf-Parkinson-White Syndrome. 89 patients remained and had an electrocardiogram performed applying the following criteria: Romhilt-Estes Point-Score system. Sokolow-Lyon (SV1 + RV5 or V6 > 3.5 mV) and (RaVL > 1.1 mV), Cornell and Rodríguez Padial. Left ventricular hypertrophy was defined by the Penn Convention Criteria., Results: In our study we obtained the following results: a) Romhilt-Estes had a sensitivity of 12% and a specificity of 87%; b) Sokolow-Lyon (SV1 + RV5 or V6) had a sensitivity of 22% and a specificity of 79%; c) Sokolow-Lyon (RaVL) has a sensitivity of 18% and a specificity of 92%; d) Cornel had a sensitivity of 31% and a specificity of 87%, and e) Rodríguez Padial had a sensitivity of 82% and a specificity of 8%. There are similarities between our results and the authors's original ones. However, there are significant statistical differences between them (p < or = 0.01)., Conclusion: Our conclusion is that these criteria have a low diagnostic value in the isolated interpretation of patients with left ventricular hypertrophy, and we need to integrate them with the whole medical history and physical examination.

Systolic blood pressure (SBP), diastolic blood pressure (DBP), norepinephrine (NE), cortisol (CRT), growth hormone (GH), and prolactin (PRL) plasma levels were investigated in 46 normal subjects, 28 high intestinal tone (high IT) and 18 low intestinal tone (low IT), before and after the administration of a single intramuscular dose of clonidine (2.5 micrograms/kg). High IT subjects had lower mean values of DBP than low IT subjects, and basal NE was significantly greater in low IT than in high IT subjects. A negative correlation between NE and IT values was found for the high IT, but not for the low IT group, during the preclonidine periods. The drug reduced SBP in high IT, whereas it reduced SBP plus DBP and NE in low IT subjects. Clonidine induced significant reductions of CRT and increases of GH in both groups; furthermore, a slight but significant reduction of PRL was registered in high IT group. The drug also induced increase of distal colon tone in high IT subjects and suppressed phasic activity (waves) in low IT subjects. While a significant positive correlation was found between NE and DBP in low IT subjects during postclonidine periods, no correlation was found between the two parameters in high IT subjects. Other significant positive (+) and negative (-) correlations during postclonidine periods were: CRT/GH (-), CRT/PRL (+), and GH/PRL (-) in high IT subjects; NE/CRT (+), NE/GH (-), CRT/GH (-), CRT/DBP (+), and GH/DBP (-) in low IT subjects. Finally, significant negative correlation was found between NE and distal colon tone during postclonidine periods in high IT subjects.(ABSTRACT TRUNCATED AT 250 WORDS)