Machine Learning Assisted Discovery of Interactions between Pesticides, Phthalates, Phenols, and Trace Elements in Child Neurodevelopment.

A growing body of literature suggests that developmental exposure to individual or mixtures of environmental chemicals (ECs) is associated with autism spectrum disorder (ASD). However, investigating the effect of interactions among these ECs can be challenging. We introduced a combination of the classical exposure-mixture Weighted Quantile Sum (WQS) regression and a machine-learning method termed Signed iterative Random Forest (SiRF) to discover synergistic interactions between ECs that are (1) associated with higher odds of ASD diagnosis, (2) mimic toxicological interactions, and (3) are present only in a subset of the sample whose chemical concentrations are higher than certain thresholds. In a case-control Childhood Autism Risks from Genetics and Environment (CHARGE) study, we evaluated multiordered synergistic interactions among 62 ECs measured in the urine samples of 479 children in association with increased odds for ASD diagnosis (yes vs no). WQS-SiRF identified two synergistic two-ordered interactions between (1) trace-element cadmium (Cd) and the organophosphate pesticide metabolite diethyl-phosphate (DEP); and (2) 2,4,6-trichlorophenol (TCP-246) and DEP. Both interactions were suggestively associated with increased odds of ASD diagnosis in the subset of children with urinary concentrations of Cd, DEP, and TCP-246 above the 75th percentile. This study demonstrates a novel method that combines the inferential power of WQS and the predictive accuracy of machine-learning algorithms to discover potentially biologically relevant chemical-chemical interactions associated with ASD.

A journey to 'tame a small metazoan organism', ‡ seen through the artistic eyes of C. elegans researchers.

In the following pages, we share a collection of photos, drawings, and mixed-media creations, most of them especially made for this JoN issue, manifesting C. elegans researchers' affection for their model organism and the founders of the field. This is a celebration of our community's growth, flourish, spread, and bright future. Descriptions provided by the contributors, edited for space. 1.

The role of the subgenual anterior cingulate cortex in dorsomedial prefrontal-amygdala neural circuitry during positive-social emotion regulation.

Positive-social emotions mediate one's cognitive performance, mood, well-being, and social bonds, and represent a critical variable within therapeutic settings. It has been shown that the upregulation of positive emotions in social situations is associated with increased top-down signals that stem from the prefrontal cortices (PFC) which modulate bottom-up emotional responses in the amygdala. However, it remains unclear if positive-social emotion upregulation of the amygdala occurs directly through the dorsomedial PFC (dmPFC) or indirectly linking the bilateral amygdala with the dmPFC via the subgenual anterior cingulate cortex (sgACC), an area which typically serves as a gatekeeper between cognitive and emotion networks. We performed functional MRI (fMRI) experiments with and without effortful positive-social emotion upregulation to demonstrate the functional architecture of a network involving the amygdala, the dmPFC, and the sgACC. We found that effortful positive-social emotion upregulation was associated with an increase in top-down connectivity from the dmPFC on the amygdala via both direct and indirect connections with the sgACC. Conversely, we found that emotion processes without effortful regulation increased network modulation by the sgACC and amygdala. We also found that more anxious individuals with a greater tendency to suppress emotions and intrusive thoughts, were likely to display decreased amygdala, dmPFC, and sgACC activity and stronger connectivity strength from the sgACC onto the left amygdala during effortful emotion upregulation. Analyzed brain network suggests a more general role of the sgACC in cognitive control and sheds light on neurobiological informed treatment interventions.

Lead Concentrations in Mexican Candy: A Follow-Up Report.

Background: Lead is a neurotoxic metal potentially affecting the developing brain. Children are particularly susceptible since they can absorb between 50% and 100% of ingested lead. There is no safe level for lead, therefore preventing exposure is crucial. We previously reported a positive association between lead concentrations found in candy and concurrent blood lead levels in Mexican children. This first report garnered media and the general public's attention. Objective: To conduct a follow-up study to assess lead concentrations in candy brands that we previously reported with concentrations ≥0.1ppm the U.S. Food and Drug Administration's recommended maximum lead level in candy likely to be consumed frequently by small children. Methods: In 2018 we analyzed 50 additional candy samples. Lead concentrations were analyzed by an inductively coupled plasma mass spectrometer and lead content per candy unit was calculated. Findings: We found concentrations were typically low, with a marked decrease from prior levels (2008). Nevertheless two candy units had concentrations of 0.1 ppm of lead. Conclusions: Candy may have lead concentrations up to 0.1 ppm and 1.2 µg per unit. This is a concern because candies are exported and consumed in many countries worldwide potentially resulting in human exposure. Continued public health surveillance is needed to protect populations especially vulnerable to lead exposure, especially children.

Multiple Holdouts With Stability: Improving the Generalizability of Machine Learning Analyses of Brain-Behavior Relationships.

BACKGROUND: In 2009, the National Institute of Mental Health launched the Research Domain Criteria, an attempt to move beyond diagnostic categories and ground psychiatry within neurobiological constructs that combine different levels of measures (e.g., brain imaging and behavior). Statistical methods that can integrate such multimodal data, however, are often vulnerable to overfitting, poor generalization, and difficulties in interpreting the results. METHODS: We propose an innovative machine learning framework combining multiple holdouts and a stability criterion with regularized multivariate techniques, such as sparse partial least squares and kernel canonical correlation analysis, for identifying hidden dimensions of cross-modality relationships. To illustrate the approach, we investigated structural brain-behavior associations in an extensively phenotyped developmental sample of 345 participants (312 healthy and 33 with clinical depression). The brain data consisted of whole-brain voxel-based gray matter volumes, and the behavioral data included item-level self-report questionnaires and IQ and demographic measures. RESULTS: Both sparse partial least squares and kernel canonical correlation analysis captured two hidden dimensions of brain-behavior relationships: one related to age and drinking and the other one related to depression. The applied machine learning framework indicates that these results are stable and generalize well to new data. Indeed, the identified brain-behavior associations are in agreement with previous findings in the literature concerning age, alcohol use, and depression-related changes in brain volume. CONCLUSIONS: Multivariate techniques (such as sparse partial least squares and kernel canonical correlation analysis) embedded in our novel framework are promising tools to link behavior and/or symptoms to neurobiology and thus have great potential to contribute to a biologically grounded definition of psychiatric disorders.

Prenatal Omega-3 and Omega-6 Polyunsaturated Fatty Acids and Childhood Atopic Dermatitis.

BACKGROUND: Atopic dermatitis is a common childhood disease, potentially influenced by prenatal nutritional exposures such as polyunsaturated fatty acids (PUFAs). OBJECTIVE: In a racially diverse cohort, we hypothesized that childhood atopic dermatitis would be associated with higher prenatal omega-6 (n-6) and lower omega-3 (n-3) PUFAs. METHODS: We included mother-child dyads, births 2006 to 2011, enrolled in the University of Tennessee Health Sciences Center Conditions Affecting Neurocognitive Development in Early Childhood cohort. Primary exposures included second trimester plasma n-3 and n-6 PUFA status and the ratio of the two (n-6:n-3). We assessed child current atopic dermatitis symptoms in the previous 12 months at age approximately 4 to 6 years. We investigated the association between PUFA exposures and atopic dermatitis using multivariable logistic regression, adjusting for potential confounders. We assessed for effect modification by maternal prenatal smoking, atopic disease history, and child sex. RESULTS: Among 1131 women, 67% were African American and 42% had an atopic disease history; 17% of children had atopic dermatitis. Higher prenatal n-6 PUFAs were associated with increased relative odds of child atopic dermatitis (adjusted odds ratio: 1.25; confidence interval: 1.01-1.54 per interquartile range difference), and interaction models demonstrated that this association was seen in dyads in which the women had a history of atopic disease. Neither prenatal n-3 PUFAs nor n-6:n-3 were associated with child atopic dermatitis. CONCLUSION: In this racially diverse cohort, higher second trimester n-6 PUFAs were associated with atopic dermatitis in children of women with atopy. PUFAs may represent a modifiable risk factor for atopic dermatitis, particularly in individuals with a familial predisposition.

Brain-behaviour modes of covariation in healthy and clinically depressed young people.

Understanding how variations in dimensions of psychometrics, IQ and demographics relate to changes in brain connectivity during the critical developmental period of adolescence and early adulthood is a major challenge. This has particular relevance for mental health disorders where a failure to understand these links might hinder the development of better diagnostic approaches and therapeutics. Here, we investigated this question in 306 adolescents and young adults (14-24 y, 25 clinically depressed) using a multivariate statistical framework, based on canonical correlation analysis (CCA). By linking individual functional brain connectivity profiles to self-report questionnaires, IQ and demographic data we identified two distinct modes of covariation. The first mode mapped onto an externalization/internalization axis and showed a strong association with sex. The second mode mapped onto a well-being/distress axis independent of sex. Interestingly, both modes showed an association with age. Crucially, the changes in functional brain connectivity associated with changes in these phenotypes showed marked developmental effects. The findings point to a role for the default mode, frontoparietal and limbic networks in psychopathology and depression.

Prenatal particulate air pollution exposure and sleep disruption in preschoolers: Windows of susceptibility.

BACKGROUND: The programming of sleep architecture begins in pregnancy and depends upon optimal in utero formation and maturation of the neural connectivity of the brain. Particulate air pollution exposure can disrupt fetal brain development but associations between fine particulate matter (PM2.5) exposure during pregnancy and child sleep outcomes have not been previously explored. METHODS: Analyses included 397 mother-child pairs enrolled in a pregnancy cohort in Mexico City. Daily ambient prenatal PM2.5 exposure was estimated using a validated satellite-based spatio-temporally resolved prediction model. Child sleep periods were estimated objectively using wrist-worn, continuous actigraphy over a 1-week period at age 4-5 years. Data-driven advanced statistical methods (distributed lag models (DLMs)) were employed to identify sensitive windows whereby PM2.5 exposure during gestation was significantly associated with changes in sleep duration or efficiency. Models were adjusted for maternal education, season, child's age, sex, and BMI z-score. RESULTS: Mother's average age was 27.7 years, with 59% having at least a high school education. Children slept an average of 7.7 h at night, with mean 80.1% efficiency. The adjusted DLM identified windows of PM2.5 exposure between 31 and 35 weeks gestation that were significantly associated with decreased sleep duration in children. In addition, increased PM2.5 during weeks 1-8 was associated with decreased sleep efficiency. In other exposure windows (weeks 39-40), PM2.5 was associated with increased sleep duration. CONCLUSION: Prenatal PM2.5 exposure is associated with altered sleep in preschool-aged children in Mexico City. Pollutant exposure during sensitive windows of pregnancy may have critical influence upon sleep programming.

Association of prenatal and early childhood stress with reduced lung function in 7-year-olds.

BACKGROUND: No prior study has examined associations between prenatal and early-life stress on childhood lung function or identified critical windows of exposure. OBJECTIVE: To prospectively examine associations between prenatal and early-life stress and childhood lung function. METHODS: Stress was indexed by a maternal negative life events (NLEs) score ascertained during pregnancy and between 1 and 2 years post partum. Spirometry was performed when children were a mean (SD) of 6.99 (0.89) years old. Associations of prenatal and early postnatal stress with spirometry z scores were examined in 199 children using linear regression. Effect modification by child sex was explored. RESULTS: Most mothers were minorities (65% Hispanic, 21% African American), had 12 years or less of education (67%), and did not smoke prenatally (78%). The highest level of prenatal stress (≥5 NLEs) was associated with lower levels of forced expiratory volume in 1 second (FEV1) (z score = -0.53, P = .03), forced vital capacity (FVC) (z score = -0.49, P = .04), and forced expiratory flow between 25% and 75% (FEF25%-75%) (z score = -0.68, P = .01) after covariate adjustment; effects were similar for postnatal stress considered separately. In sex-stratified analyses, high postnatal stress (≥5 NLEs) was associated with lower FEV1 (z score = -0.76, P = .01), FVC (z score = -0.77, P = .01), and FEF25%-75% (z score = -0.67, P = .02) in boys but not girls, although the interaction term was not significant (P for interaction >.10). CONCLUSION: These are the first prospective data that link perinatal stress with reduced child lung function. High levels of stress in the prenatal and postnatal periods were associated with symmetric reductions in FEV1 and FVC consistent with impaired lung growth. Given that lung function growth patterns are established by 7 years of age, these findings have lifelong implications.

Estimating multivariate similarity between neuroimaging datasets with sparse canonical correlation analysis: an application to perfusion imaging.

An increasing number of neuroimaging studies are based on either combining more than one data modality (inter-modal) or combining more than one measurement from the same modality (intra-modal). To date, most intra-modal studies using multivariate statistics have focused on differences between datasets, for instance relying on classifiers to differentiate between effects in the data. However, to fully characterize these effects, multivariate methods able to measure similarities between datasets are needed. One classical technique for estimating the relationship between two datasets is canonical correlation analysis (CCA). However, in the context of high-dimensional data the application of CCA is extremely challenging. A recent extension of CCA, sparse CCA (SCCA), overcomes this limitation, by regularizing the model parameters while yielding a sparse solution. In this work, we modify SCCA with the aim of facilitating its application to high-dimensional neuroimaging data and finding meaningful multivariate image-to-image correspondences in intra-modal studies. In particular, we show how the optimal subset of variables can be estimated independently and we look at the information encoded in more than one set of SCCA transformations. We illustrate our framework using Arterial Spin Labeling data to investigate multivariate similarities between the effects of two antipsychotic drugs on cerebral blood flow.

Sparse network-based models for patient classification using fMRI.

Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from healthy participants. However, predictive patterns obtained from whole-brain voxel-based features are difficult to interpret in terms of the underlying neurobiology. Many psychiatric disorders, such as depression and schizophrenia, are thought to be brain connectivity disorders. Therefore, pattern recognition based on network models might provide deeper insights and potentially more powerful predictions than whole-brain voxel-based approaches. Here, we build a novel sparse network-based discriminative modeling framework, based on Gaussian graphical models and L1-norm regularized linear Support Vector Machines (SVM). In addition, the proposed framework is optimized in terms of both predictive power and reproducibility/stability of the patterns. Our approach aims to provide better pattern interpretation than voxel-based whole-brain approaches by yielding stable brain connectivity patterns that underlie discriminative changes in brain function between the groups. We illustrate our technique by classifying patients with major depressive disorder (MDD) and healthy participants, in two (event- and block-related) fMRI datasets acquired while participants performed a gender discrimination and emotional task, respectively, during the visualization of emotional valent faces.

Children's urinary phthalate metabolites and fractional exhaled nitric oxide in an urban cohort.

RATIONALE: Phthalates are used widely in consumer products. Exposure to several phthalates has been associated with respiratory symptoms and decreased lung function. Associations between children's phthalate exposures and fractional exhaled nitric oxide (Fe(NO)), a biomarker of airway inflammation, have not been examined. OBJECTIVES: We hypothesized that urinary concentrations of four phthalate metabolites would be positively associated with Fe(NO) and that these associations would be stronger among children with seroatopy or wheeze. METHODS: In an urban ongoing birth cohort, 244 children had phthalate metabolites determined in urine collected on the same day as Fe(NO) measurement. Repeated sampling gathered 313 observations between ages 4.9 and 9.1 years. Seroatopy was assessed by specific IgE. Wheeze in the past year was assessed by validated questionnaire. Regression models used generalized estimating equations. MEASUREMENTS AND MAIN RESULTS: Log-unit increases in urinary concentrations of metabolites of diethyl phthalate (DEP) and butylbenzyl phthalate (BBzP) were associated with a 6.6% (95% confidence interval [CI] 0.5-13.1%) and 8.7% (95% CI, 1.9-16.0%) increase in Fe(NO), respectively, adjusting for other phthalate metabolites and potential covariates/confounders. There was no association between concentrations of metabolites of di(2-ethylhexyl) phthalate or di-n-butyl phthalate and Fe(NO). There was no significant interaction by seroatopy. The BBzP metabolite association was significantly stronger among children who wheeze (P = 0.016). CONCLUSIONS: Independent associations between exposures to DEP and BBzP and Fe(NO) in a cohort of inner-city children were observed. These results suggest that these two ubiquitous phthalates, previously shown to have substantial contributions from inhalation, are positively associated with airway inflammation in children.

Study protocol: using the Q-STEPS to assess and improve the quality of physical activity programmes for the elderly.

BACKGROUND: Aging is one of the most important and obvious phenomenon observed in our society. In the past years, there has been a growing concern in designing physical activity (PA) programmes for elderly people, because evidence suggests that such health promotion interventions may reduce the deleterious effects of the ageing process. Accordingly, a growing body of literature points to the importance of a sound approach to planning and evaluation in order to improve the quality of PA programmes. However, while numerous PA programmes have been designed for the elderly in recent years, their evaluation has been scarce. Quality management processes and tools provide a practical way for organisations to assess, identify and shed light on the areas requiring improvement. The Quality Self-assessment Tool for Exercise Programmes for Seniors (Q-STEPS) seems to provide a framework tailored to evaluate PA programmes for the elderly. FINDINGS: The primary purpose of this study is 1) to determine feasibility, acceptability and usability of the Q-STEPS. Secondary purposes of the study are: 2) to examine the quality of the PA programmes for elderly people developed by the Portuguese Local Administration over a three-year period of self-assessments in terms of: a) Enabler domains (Leadership, Policy and Strategy, People, Partnership and Resources, Processes); b) Result domains (Customer Results, People Results, Society Results and Key Performance Results); 3) to estimate the association between the use of Q-STEPS and some indicators relating to the elderly participants, during the three self-assessments, such as: attendance rates, physical fitness, health-related quality of life and the elderly's perceived quality of the programme. The study will be conducted in PA programmes for elderly adults from mainland Portuguese municipalities over a three-year period. The project will adopt a participative quality improvement approach that features annual learning cycles of: 1) self-assessment with the Q-STEPS; 2) feedback to and interpretation of results involving programme's staff; 3) action planning to achieve system changes; 4) implementation of strategies for change; and 5) review process through further self-assessment. The study will collect a range of process and outcome data that will be used to achieve the research aims. DISCUSSION: It is our understanding that the results of the Q-STEPS study will contribute directly to the evidence based on effectiveness of continuous quality improvement approaches, in order to improve customer satisfaction and adherence to PA programmes targeting the ageing population. This comprehensive evaluation will also add significant new knowledge regarding the characteristics associated with a sustainable public service.

Bayesian comparison of neurovascular coupling models using EEG-fMRI.

Functional magnetic resonance imaging (fMRI), with blood oxygenation level-dependent (BOLD) contrast, is a widely used technique for studying the human brain. However, it is an indirect measure of underlying neuronal activity and the processes that link this activity to BOLD signals are still a topic of much debate. In order to relate findings from fMRI research to other measures of neuronal activity it is vital to understand the underlying neurovascular coupling mechanism. Currently, there is no consensus on the relative roles of synaptic and spiking activity in the generation of the BOLD response. Here we designed a modelling framework to investigate different neurovascular coupling mechanisms. We use Electroencephalographic (EEG) and fMRI data from a visual stimulation task together with biophysically informed mathematical models describing how neuronal activity generates the BOLD signals. These models allow us to non-invasively infer the degree of local synaptic and spiking activity in the healthy human brain. In addition, we use Bayesian model comparison to decide between neurovascular coupling mechanisms. We show that the BOLD signal is dependent upon both the synaptic and spiking activity but that the relative contributions of these two inputs are dependent upon the underlying neuronal firing rate. When the underlying neuronal firing is low then the BOLD response is best explained by synaptic activity. However, when the neuronal firing rate is high then both synaptic and spiking activity are required to explain the BOLD signal.

Evaluation of physical activity programmes for elderly people - a descriptive study using the EFQM' criteria.

BACKGROUND: In the past years, there has been a growing concern in designing physical activity (PA) programmes for elderly people, because evidence suggests that such health promotion interventions may reduce the deleterious effects of the ageing process. Quality is an important issue when designing a PA programme for older people. Some studies support the Excellence Model of the European Foundation for Quality Management (EFQM) as an operational framework for evaluating the quality of an organization. Within this context, the aim of this study was to characterize the quality management models of the PA programmes developed by Portuguese Local Administration to enhance quality of life for elderly people, according to the criteria of the EFQM Excellence Model. METHODS: A methodological triangulation was conducted in 26 PA programmes using questionnaire surveys, semi-structured interviews and document analysis. We used standard approaches to the statistical analysis of data including frequencies and percentages for the categorical data. RESULTS: Results showed that Processes (65,38%), Leadership (61,03%), Customer results (58,46) and People (51,28%) had high percentage occurrences of quality practices. In contrast, Partnerships and resources (45,77%), People results (41,03%), Policy and strategy (37,91%), Key performance results (19,23%) and Society results (19,23%) had lower percentage occurrences. CONCLUSIONS: Our findings suggest that although there are some good practices in PA programmes, there are still relevant areas that require improvement.

Comparing families of dynamic causal models.

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This "best model" approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data.

Key roles of hydrophobic rings of TM2 in gating of the alpha9alpha10 nicotinic cholinergic receptor.

We have performed a systematic mutagenesis of three hydrophobic rings (17', 13' and 9') within transmembrane region (TM) 2 of the alpha9alpha10 nicotinic cholinergic receptor (nAChR) to a hydrophilic (threonine) residue and compared the properties of mutant receptors reconstituted in Xenopus laevis oocytes. Phenotypic changes in alpha9alpha10 mutant receptors were evidenced by a decrease in the desensitization rate, an increase in both the EC(50) for ACh as well as the efficacy of partial agonists and the reduction of the allosteric modulation by extracellular Ca(2+). Mutated receptors exhibited spontaneous openings and, at the single-channel level, an increased apparent mean open time with no major changes in channel conductance, thus suggesting an increase in gating of the channel as the underlying mechanism. Overall, the degrees of the phenotypes of mutant receptors were more overt in the case of the centrally located V13'T mutant. Based on the atomic model of the pore of the electric organ of the Torpedo ray, we can propose that the interactions of side chains at positions 13' and 9' are key ones in creating an energetic barrier to ion permeation. In spite of the fact that the roles of the TM2 residues are mostly conserved in the distant alpha9alpha10 member of the nAChR family, their mechanistic contributions to channel gating show significant differences when compared to other nAChRs. These differences might be originated from slight differential intramolecular rearrangements during gating for the different receptors and might lead each nAChR to be in tune with their physiological roles.

[Cardiac tumors. Experience with two cases]. / Tumores intrapericárdicos.

Cardiac tumors are rare neoplasms with an incidence of 0.027 cases per 100. Up to 90 % of these tumors are benign but, because of their location, they can be lethal, despite their histology. Most appear in infants aged less than 1 year. Teratomas, which are relatively frequent in the pediatric age group, are usually located in the ovaries, sacrococcygeal area, thorax, and retroperitoneal area. Intrapericardial location is less frequent. In this localization, the clinical manifestation depends on compression of adjacent structures and determines the therapeutic attitude in each case. Imaging studies should be performed and the definitive diagnosis is obtained after surgical resection, which is the treatment of choice. The differential diagnosis should include other tumors of the anterior mediastinum, thymus hypertrophy, pericardial effusion and primary cardiac disorders such as pericardial mesothelioma, Ebstein malformation, and intrapericardial bronchogenic cysts. We present two patients who were diagnosed in the first year of life in our hospital. Both children developed pericardial tumours. In one patient, the mass decreased and disappeared while in the other, who received a later diagnosis, surgical treatment was required.

Antibiotic resistance profile of the subgingival microbiota following systemic or local tetracycline therapy.

BACKGROUND: Tetracyclines have been extensively used as adjunctives to conventional periodontal therapy. Emergence of resistant strains, however, has been reported. This study evaluated longitudinally the tetracycline resistance patterns of the subgingival microbiota of periodontitis subjects treated with systemic or local tetracycline therapy+scaling and root planing (SRP). METHODS: Thirty chronic periodontitis patients were randomly assigned to three groups: SRP+500 mg of systemic tetracycline twice/day for 14 days; SRP alone and SRP+tetracycline fibers (Actsite) at four selected sites for 10 days. Subgingival plaque samples were obtained from four sites with probing pocket depths (PPD)> or =6 mm in each patient at baseline, 1 week, 3, 6 and 12 months post-therapy. Samples were dispersed and diluted in pre-reduced anaerobically sterilized Ringer's solution, plated on Trypticase Soy Agar (TSA)+5% blood with or without 4 microg/ml of tetracycline and incubated anaerobically for 10 days. The percentage of resistant microorganisms were determined and the isolates identified by DNA probes and the checkerboard method. Significance of differences among and within groups over time was sought using the Kruskal-Wallis and Friedman tests, respectively. RESULTS: The percentage of resistant microorganisms increased significantly at 1 week in the tetracycline groups, but dropped to baseline levels over time. The SRP+Actsite group presented the lowest proportions of resistant species at 6 and 12 months. No significant changes were observed in the SRP group. The predominant tetracycline-resistant species included Streptococcus spp., Veillonela parvula, Peptostreptococcus micros, Prevotella intermedia, Gemella morbillorum and Actinobacillus actinomycetemcomitans (Aa). A high percentage of sites with resistant Aa, Porphyromonas gingivalis and Tanerella forsythensis was observed in all groups at baseline. However, T. forsythensis was not detected in any group and P. gingivalis was not present in the SRP+Actsite group at 1 year post-therapy. Aa was still frequently detected in all groups after therapy. However, the greatest reduction was observed in the SRP+Actsite group. CONCLUSION: Local or systemically administered tetracycline results in transitory selection of subgingival species intrinsically resistant to this drug. Although the percentage of sites harboring periodontal pathogens resistant to tetracycline were quite elevated in this population, both therapies were effective in reducing their prevalence over time.

Detection of IgM antibodies to Schistosoma mansoni gut-associated antigens for the study of the dynamics of schistosomiasis transmission in an endemic area with low worm burden

Dados de prevalencia e incidencia da esquistossomose foram estimados, acompanhando-se um grupo de escolares residentes em area rural do municipio de Itariri (Sao Paulo, Brasil), por um periodo de 2 anos, com cinco inqueritos, um a cada semestre, realizados no primeiro semestre de cada ano entre marco e abril e no segundo, entre setembro e outubro. O hospedeiro intermediario do Schistosoma mansoni na area e a Biomphalaria tenagophila. A infeccao pelo S. mansoni foi determinada pelo metodo parasitologico de Kato-Katz, atraves do exame de tres laminas, e os resultados analisados comparativamente aos da reacao de imunofluorescencia para deteccao de anticorpos IgM (RIF-IgM). Foram encontrados nos cinco inqueritos indices de prevalencia de 8,6 por cento, 6,8 por cento, 9,9 por cento, 5,8 por cento e 17,2 por cento pelo metodo parasitologico...