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Macrophages with lysosomes pinpointed by quinacrine-induced fluorescence were infected with the endozoits of Toxoplasma gondii RH strain (peritoneal exudate of infected mouse), or treated with liquid (acellular) fraction of the same exudate. Dead toxoplasmas ingested by macrophages come into contact with the stained lysosomes of the cell and acquire a diffuse fluorescence. Viable toxoplasmas do not give fluorescence, which means that they do not come into contact with lysosomes, either primary or secondary. This supports the hypothesis that toxoplasmas can prevent lysosomes from fusing with the phagosomes of the host cell. Moderate doses of soluble products of toxoplasmas contained in peritoneal exudate cause an excessive output of macrophage lysosomes which points to the activation of macrophages; high doses of challenge inhibit the phagocytosis of toxoplasmas and damage macrophages. The pathogenicity of toxoplasmas due to their ability to inhibit the fusion of lysosomes and phagosomes and the cellular action of their soluble products is discussed.
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The social exchanges of young children with developmental disabilities over time with two different social partners and the nature of these exchanges were compared. Thirty-three toddlers with developmental disabilities were video-taped for 15 minutes with each partner at two different data points. Data were transcribed and coded using a modification of Vandell and Wilson's (1979) coding system. Results showed that more of the observation time was spent socially with mothers than with peers, and the number of turns per exchange was longer with mothers. In contrast, toddlers initiated more social exchanges with peers than with mothers. There were similarities in the content of the social exchanges with both partners. There were few changes over time, although exchanges consisted of more purely social behaviors at Time 2. Results were interpreted with respect to implications for early intervention.
Incubation of neutrophils with cytokines such as granulocyte macrophage colony-stimulating factor (GM-CSF) delays their loss of function and changes in cellular morphology that are characteristic of apoptosis. Adenosine triphosphate (ATP) and the diadenosine polyphosphates Ap4A and AP3A were almost as effective as GM-CSF in delaying neutrophil apoptosis. The nucleotides could thus preserve cellular morphology, protect against chromatin fragmentation, and preserve functions such as NADPH oxidase activity and expression of CD16. Moreover, addition of ATP, AP3A and AP4A together with GM-CSF resulted in more pronounced protection from apoptosis than was observed during incubation with either the cytokine or the nucleotides alone. Because ATP, Ap3A, and AP4A may be secreted from activated platelets, these observations suggest that platelet-derived products, perhaps acting in combination with endothelial-derived or immune cell-derived cytokines, can regulate neutrophil function during certain types of inflammation.
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INTRODUCTION: Recent studies show that the existing interaction patterns of children with multiple disabilities should be taken into consideration when planning communication interventions. For children with disabilities, it is especially important that the partner in interaction is sensitive and well aware of the importance of a qualitatively successful interaction. Wilder (unpublished report) found that the behaviour style of 30 children with multiple disabilities was more related to the caregiver-perceived interaction than the communicative skills and functional abilities of the children. This study inductively explored the caregivers' perceptions of interaction within seven caregiver-child dyads. The research questions were: How do the caregivers perceive the interaction? How do the caregivers perceive the children's behaviour style to be related to the interaction with the caregivers? METHOD: The children were selected individually from the participants in Wilder (unpublished report) depending upon the responses the caregivers had given about the children's self-regulation and reactivity in the Carolina Record of Individual Behaviour questionnaire. The study was undertaken by means of home visits where the caregivers participated in an interview asking about their strategies for interaction, how they perceived the roles of the children and their own roles in interaction, the caregivers' opinion of what an interaction constituted of and the caregivers' aims and aspiration for interaction. The data analysis was performed by meaning concentration and categorization through a pendulum between the parts and the entirety of the interviews. In this way, hermeneutics and thematic analysis were both being practised. RESULTS: The results of the interviews are presented as a model with categorizations as a network. The categorizations reflect the system of themes that permeate how the caregivers perceived interaction in the dyad. The themes are: sharing of experience, successful interaction, role of the child, role of the caregiver, interaction methods, obstacles and facilitators and aims and aspirations. DISCUSSION: The caregivers perceived their own role in interaction to be of a sensitive leading kind. The caregivers lead the interaction by using their knowledge about the children's usual way of interacting, the children's behaviour styles, functional abilities, the children's current mood and situation as well as the whole context. They monitored the interaction such that, throughout an interaction sequence, the caregivers always tried to optimize the interaction between the parties in the dyad. The behaviour style was a background factor that the caregivers had knowledge of and scanned in their everyday turn taking. Although there were differences in the children's behaviour styles, the caregivers discussed the same themes in the interviews. The behaviour style became a facilitator for the whole interaction, forced the interaction in certain directions and made the interaction more complete with turn taking of different kinds from both parties. The findings show that it is imperative to see caregivers as experts on their children and to make them assertive in this in relation to professionals. Furthermore, as a successful interaction can boost the development of children, it is essential to direct interventions to the everyday interaction in caregiver-child dyads.
BACKGROUND: The development of high-throughput technologies has produced several large scale protein interaction data sets for multiple species, and significant efforts have been made to analyze the data sets in order to understand protein activities. Considering that the basic units of protein interactions are domain interactions, it is crucial to understand protein interactions at the level of the domains. The availability of many diverse biological data sets provides an opportunity to discover the underlying domain interactions within protein interactions through an integration of these biological data sets. RESULTS: We combine protein interaction data sets from multiple species, molecular sequences, and gene ontology to construct a set of high-confidence domain-domain interactions. First, we propose a new measure, the expected number of interactions for each pair of domains, to score domain interactions based on protein interaction data in one species and show that it has similar performance as the E-value defined by Riley et al. Our new measure is applied to the protein interaction data sets from yeast, worm, fruitfly and humans. Second, information on pairs of domains that coexist in known proteins and on pairs of domains with the same gene ontology function annotations are incorporated to construct a high-confidence set of domain-domain interactions using a Bayesian approach. Finally, we evaluate the set of domain-domain interactions by comparing predicted domain interactions with those defined in iPfam database that were derived based on protein structures. The accuracy of predicted domain interactions are also confirmed by comparing with experimentally obtained domain interactions from H. pylori. As a result, a total of 2,391 high-confidence domain interactions are obtained and these domain interactions are used to unravel detailed protein and domain interactions in several protein complexes. CONCLUSION: Our study shows that integration of multiple biological data sets based on the Bayesian approach provides a reliable framework to predict domain interactions. By integrating multiple data sources, the coverage and accuracy of predicted domain interactions can be significantly increased.
INTRODUCTION: Computerised drug interaction surveillance systems (CIS) may be helpful in detecting clinically significant drug interactions. Experience with CIS reveals that they often yield alerts with questionable clinical significance, fail to provide relevant information on risk factors for the adverse reaction of the interaction and fail to detect all significant drug interactions. These problems highlight the importance of transparency and selectivity in choosing the drug interactions to be included in CIS. In The Netherlands, the Working Group on Pharmacotherapy and Drug Information is responsible for maintenance of the CIS of the Royal Dutch Association for the Advancement of Pharmacy (KNMP). METHODS: The Working Group developed an evidence-based procedure for structured assessment of drug-drug interactions and revised all drug interactions in the CIS accordingly. RESULTS: For every drug interaction four core parameters were assessed: (i) evidence on the interaction; (ii) clinical relevance of the potential adverse reaction resulting from the interaction; (iii) risk factors identifying patient, medication or disease characteristics for which the interaction is of special importance; and (iv) the incidence of the adverse reaction. On the basis of this assessment the drug-drug interactions for inclusion in the CIS were selected. After revision of the drug combinations in the KNMP-CIS, the Working Group judged 22% of the combinations to be not interacting and another 12% to be interacting but not requiring action. On the basis of this assessment the subset of drug combinations for which interaction alerts are generated and the information on management of a drug interaction alert for users of the CIS were adapted. When an alert is generated by the CIS, the user of the system is supplied with comprehensive information on the four core parameters, the mechanism of the interaction and critical information for management of the interaction for the individual patient. DISCUSSION: This structured procedure offers the possibility for transparent and reproducible assessment of the clinical relevance of drug interactions. CONCLUSION: A CIS selectively generating interaction alerts based on this assessment may help in realising the goal of good clinical practice and may offer a methodology to further increase drug safety.
BACKGROUND: Extensive protein interaction maps are being constructed for yeast, worm, and fly to ask how the proteins organize into pathways and systems, but no such genome-wide interaction map yet exists for the set of human proteins. To prepare for studies in humans, we wished to establish tests for the accuracy of future interaction assays and to consolidate the known interactions among human proteins. RESULTS: We established two tests of the accuracy of human protein interaction datasets and measured the relative accuracy of the available data. We then developed and applied natural language processing and literature-mining algorithms to recover from Medline abstracts 6,580 interactions among 3,737 human proteins. A three-part algorithm was used: first, human protein names were identified in Medline abstracts using a discriminator based on conditional random fields, then interactions were identified by the co-occurrence of protein names across the set of Medline abstracts, filtering the interactions with a Bayesian classifier to enrich for legitimate physical interactions. These mined interactions were combined with existing interaction data to obtain a network of 31,609 interactions among 7,748 human proteins, accurate to the same degree as the existing datasets. CONCLUSION: These interactions and the accuracy benchmarks will aid interpretation of current functional genomics data and provide a basis for determining the quality of future large-scale human protein interaction assays. Projecting from the approximately 15 interactions per protein in the best-sampled interaction set to the estimated 25,000 human genes implies more than 375,000 interactions in the complete human protein interaction network. This set therefore represents no more than 10% of the complete network.
OBJECTIVES: To determine the value of a new bedside monitor in assessing the interactions between spontaneous respiratory activity and ventilator inflations in preterm infants; and to monitor continuously the degree of patient-ventilator synchrony and the stability of spontaneous respiratory effort during different modes of ventilation and in response to care procedures. DESIGN: A prospective, observational study of physiologic variables recorded by a computerized monitoring system. SETTING: A neonatal intensive care unit in a teaching hospital. PATIENTS: Thirty-one neonates (median gestational age of 28 wks [range 24 to 36]; median birth weight of 942 g [range 624 to 2940]) were monitored during conventional mandatory ventilation at rates ranging from 47 to 108 inflations/min, and 22 infants (median gestational age of 27.5 wks [range 25 to 40]; median birth weight of 1345 g [range 510 to 3490]) were monitored during patient-triggered ventilation. All infants were sedated as part of the routine care policy. INTERVENTIONS: Spontaneous respiration (abdominal pressure capsule) and ventilator inflations (airway pressure) were recorded continuously for periods of up to 3 days in mechanically ventilated preterm infants. MEASUREMENTS AND MAIN RESULTS: The monitoring system uses the Frequency Tracking Locus method to derive the interaction Score, which quantifies the degree of entrainment of the spontaneous respiratory pattern by the ventilator. This analysis was applied to airway pressure and abdominal capsule signals. A perfect 1:1 interaction between spontaneous inspirations and mechanical inflations returns an interaction Score of 1.00, and irregular interactions return a score of > 1.5. During conventional mandatory ventilation, a total of 53,074 16-sec epochs (representing 782,811 spontaneous breaths) were studied in 31 preterm infants: 27.4% of epochs showed a 1:1 interaction, 60.5% a non 1:1 interaction, and 12.1% indicated a passive (i.e., infant apneic) response by the infant, despite excluding periods when paralyzing agents were used. The median interaction Score value during 1:1 interactions was 1.2, whereas for non 1:1 interactions the interaction Score was 2.2. One to one entrainment occurred at conventional mandatory ventilation rates between 50 and 85 inflations/min: for many infants, such entrainment was achievable over a range of conventional mandatory ventilation rates, while in some infants respiration was unstable at all rates of conventional mandatory ventilation. During passive ventilation, the median Interaction Score was 1.0. During patient-triggered mechanical ventilation, approximately 67,150 spontaneous respiratory cycles, represented by 3,592 16-sec epochs, were studied in 22 infants. Overall, 19.5% (702) of epochs showed the criteria for ideal triggering by spontaneous inspiration and 19.6% (703) showed autotriggering. In 60.9% (2187) of epochs, a non 1:1 interaction was noted. During ideal patient-triggered mechanical ventilation, the median interaction Score was 1.14; during passive (autotriggered) ventilation, the median Interaction Score was 1.05; and during non 1:1 ventilation, the median score was 1.74. "Autotriggering" was found frequently in infants of < or = 28 wks gestation. The monitor was able to distinguish between stable and unstable interactions and apnea during conventional mandatory ventilation and patient-triggered mechanical ventilation by reference to the Interaction Score value. CONCLUSIONS: We describe a new kind of bedside monitor for the Interpretation of respiratory data. Unlike other methods, it is able to give the clinician a continuous measure of patient-ventilator interaction which is easy to interpret. It appears to have wide-spread application in neonatal intensive care nurseries where the babies' own breathing efforts can affect the efficiency of respiration and cause unwanted physiologic instability. The monitor can be used to determine the optimal ventilatory settings to
AIM: This paper reports a study to evaluate patterns of nurse-child-parent interaction and identify the characteristics nurse-child and nurse-parent interactions in an inpatient paediatric unit. BACKGROUND: Positive nurse-patient interaction is a critical component of effective nursing care. The ability to interact positively with patients and their families who are facing crisis during illness and hospitalization is essential for professional nursing care. However, little is known about the patterns of interaction between nurses, hospitalized children and their parents. METHODS: Eight triads of nurses, patients and their mothers were videotaped. The triads were videotaped for 4 hours each day over a 2-day period as they interacted with each other on the inpatient unit. Both verbalizations and descriptions of nonverbal behaviour were recorded from the videotapes. The data were coded and analysed using Bales' Interaction Process Analysis. The interactions were evaluated for frequency, time, purpose of interaction and interaction dynamics. The data were collected between December 2001 and February 2002. RESULTS: The total amount of interaction over the 2-day period (8 hours) was 39.75 minutes and the average per interaction was 4.24 minutes. Interaction episodes consisted of nursing activities, which included nurses making patient rounds to monitoring their patient as well as providing patient care. Nurses initiated the majority of interactions between child and nurse. Affective (both positive and negative) behaviours were more frequent between nurses and children, whereas neutral behaviours were more common between nurses and mothers. CONCLUSION: Children remained passive participants in the interactions. Interaction strategies are needed to help children to learn how they can actively interact with their nurses. These strategies may contribute to the children feeling more in control in these interactions and in their care.