161 research outputs found

    Expression of CAP2 during early Xenopus embryogenesis

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    We have cloned and characterized a second member of the Xenopus CAP (cyclase associated protein) gene family. xCAP2 demonstrates greater restriction of expression than its homolog, xCAP1, and is differentially expressed throughout early embryogenesis. Although present as a maternal transcript, CAP2 comes to be expressed in the anterior-most mesoderm/endoderm during late gastrulation, in paraxial mesoderm during late neurula stages, and later expresses in lens, cardiac primordia, somites, otic vesicles, retina,and in the optic and craniofacial musculature. The gene is also expressed in the leading edge of myotome

    Analyzing Digital Image by Deep Learning for Melanoma Diagnosis

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    Image classi cation is an important task in many medical applications, in order to achieve an adequate diagnostic of di erent le- sions. Melanoma is a frequent kind of skin cancer, which most of them can be detected by visual exploration. Heterogeneity and database size are the most important di culties to overcome in order to obtain a good classi cation performance. In this work, a deep learning based method for accurate classi cation of wound regions is proposed. Raw images are fed into a Convolutional Neural Network (CNN) producing a probability of being a melanoma or a non-melanoma. Alexnet and GoogLeNet were used due to their well-known e ectiveness. Moreover, data augmentation was used to increase the number of input images. Experiments show that the compared models can achieve high performance in terms of mean ac- curacy with very few data and without any preprocessing.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

    Training Residents to Employ Self-efficacy-enhancing Interviewing Techniques: Randomized Controlled Trial of a Standardized Patient Intervention

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    Current interventions to enhance patient self-efficacy, a key mediator of health behavior, have limited primary care application. To explore the effectiveness of an office-based intervention for training resident physicians to use self-efficacy-enhancing interviewing techniques (SEE IT). Randomized controlled trial. Family medicine and internal medicine resident physicians (N = 64) at an academic medical center. Resident use of SEE IT (a count of ten possible behaviors) was coded from audio recordings of the physician-patient portion of two standardized patient (SP) instructor training visits and two unannounced post-training SP visits, all involving common physical and mental health conditions and behavior change issues. One post-training SP visit involved health conditions similar to those experienced in training, while the other involved new conditions. Experimental group residents demonstrated significantly greater use of SEE IT than controls, starting after the first training visit and sustained through the final post-training visit. The mean effect of the intervention was significant [adjusted incidence rate ratio for increased use of SEE IT = 1.94 (95% confidence interval = 1.34, 2.79; p < 0.001)]. There were no significant effects of resident gender, race/ethnicity, specialty, training level, or SP health conditions. SP instructors can teach resident physicians to apply SEE IT during SP office visits, and the effects extend to health conditions beyond those used for training. Future studies should explore the effects of the intervention on practicing physicians, physician use of SEE IT during actual patient visits, and its influence on patient health behaviors and outcomes

    Diabetes Distress but Not Clinical Depression or Depressive Symptoms Is Associated With Glycemic Control in Both Cross-Sectional and Longitudinal Analyses

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    ObjectiveTo determine the concurrent, prospective, and time-concordant relationships among major depressive disorder (MDD), depressive symptoms, and diabetes distress with glycemic control.Research design and methodsIn a noninterventional study, we assessed 506 type 2 diabetic patients for MDD (Composite International Diagnostic Interview), for depressive symptoms (Center for Epidemiological Studies-Depression), and for diabetes distress (Diabetes Distress Scale), along with self-management, stress, demographics, and diabetes status, at baseline and 9 and 18 months later. Using multilevel modeling (MLM), we explored the cross-sectional relationships of the three affective variables with A1C, the prospective relationships of baseline variables with change in A1C over time, and the time-concordant relationships with A1C.ResultsAll three affective variables were moderately intercorrelated, although the relationship between depressive symptoms and diabetes distress was greater than the relationship of either with MDD. In the cross-sectional MLM, only diabetes distress but not MDD or depressive symptoms was significantly associated with A1C. None of the three affective variables were linked with A1C in prospective analyses. Only diabetes distress displayed significant time-concordant relationships with A1C.ConclusionsWe found no concurrent or longitudinal association between MDD or depressive symptoms with A1C, whereas both concurrent and time-concordant relationships were found between diabetes distress and A1C. What has been called "depression" among type 2 diabetic patients may really be two conditions, MDD and diabetes distress, with only the latter displaying significant associations with A1C. Ongoing evaluation of both diabetes distress and MDD may be helpful in clinical settings

    Associations of Patient Health-Related Problem Solving with Disease Control, Emergency Department Visits, and Hospitalizations in HIV and Diabetes Clinic Samples

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    BACKGROUND: Patient problem solving and decision making are recognized as essential to effective self-management across multiple chronic diseases. However, a health-related problem-solving instrument that demonstrates sensitivity to disease control parameters in multiple diseases has not been established. OBJECTIVES: To determine, in two disease samples, internal consistency and associations with disease control of the Health Problem-Solving Scale (HPSS), a 50-item measure with 7 subscales assessing effective and ineffective problem-solving approaches, learning from past experiences, and motivation/orientation. DESIGN: Cross-sectional study. PARTICIPANTS: Outpatients from university-affiliated medical center HIV (N = 111) and diabetes mellitus (DM, N = 78) clinics. MEASUREMENTS: HPSS, CD4, hemoglobin A1c (HbA1c), and number of hospitalizations in the previous year and Emergency Department (ED) visits in the previous 6 months. RESULTS: Administration time for the HPSS ranged from 5 to 10 minutes. Cronbach’s alpha for the total HPSS was 0.86 and 0.89 for HIV and DM, respectively. Higher total scores (better problem solving) were associated with higher CD4 and fewer hospitalizations in HIV and lower HbA1c and fewer ED visits in DM. Health Problem-Solving Scale subscales representing negative problem-solving approaches were consistently associated with more hospitalizations (HIV, DM) and ED visits (DM). CONCLUSIONS: The HPSS may identify problem-solving difficulties with disease self-management and assess effectiveness of interventions targeting patient decision making in self-care

    Predicting complete loss to follow-up after a health-education program: number of absences and face-to-face contact with a researcher

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    <p>Abstract</p> <p>Background</p> <p>Research on health-education programs requires longitudinal data. Loss to follow-up can lead to imprecision and bias, and <it>complete </it>loss to follow-up is particularly damaging. If that loss is predictable, then efforts to prevent it can be focused on those program participants who are at the highest risk. We identified predictors of complete loss to follow-up in a longitudinal cohort study.</p> <p>Methods</p> <p>Data were collected over 1 year in a study of adults with chronic illnesses who were in a program to learn self-management skills. Following baseline measurements, the program had one group-discussion session each week for six weeks. Follow-up questionnaires were sent 3, 6, and 12 months after the baseline measurement. A person was classified as completely lost to follow-up if none of those three follow-up questionnaires had been returned by two months after the last one was sent.</p> <p>We tested two hypotheses: that complete loss to follow-up was directly associated with the number of absences from the program sessions, and that it was less common among people who had had face-to-face contact with one of the researchers. We also tested predictors of data loss identified previously and examined associations with specific diagnoses.</p> <p>Using the unpaired t-test, the U test, Fisher's exact test, and logistic regression, we identified good predictors of complete loss to follow-up.</p> <p>Results</p> <p>The prevalence of complete loss to follow-up was 12.2% (50/409). Complete loss to follow-up was directly related to the number of absences (odds ratio; 95% confidence interval: 1.78; 1.49-2.12), and it was inversely related to age (0.97; 0.95-0.99). Complete loss to follow-up was less common among people who had met one of the researchers (0.51; 0.28-0.95) and among those with connective tissue disease (0.29; 0.09-0.98). For the multivariate logistic model the area under the ROC curve was 0.77.</p> <p>Conclusions</p> <p>Complete loss to follow-up after this health-education program can be predicted to some extent from data that are easy to collect (age, number of absences, and diagnosis). Also, face-to-face contact with a researcher deserves further study as a way of increasing participation in follow-up, and health-education programs should include it.</p

    Expectations and needs of patients with a chronic disease toward self-management and eHealth for self-management purposes

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    Background: Self-management is considered as an essential component of chronic care by primary care professionals. eHealth is expected to play an important role in supporting patients in their self-management. For effective implementation of eHealth it is important to investigate patients’ expectations and needs regarding self-management and eHealth. The objectives of this study are to investigate expectations and needs of people with a chronic condition regarding self-management and eHealth for self-management purposes, their willingness to use eHealth, and possible differences between patient groups regarding these topics. Methods: Five focus groups with people with diabetes (n = 14), COPD (n = 9), and a cardiovascular condition (n = 7) were conducted in this qualitative research. Separate focus groups were organized based on patients’ chronic condition. The following themes were discussed: 1) the impact of the chronic disease on patients’ daily life; 2) their opinions and needs regarding self-management; and 3) their expectations and needs regarding, and willingness to use, eHealth for self-management purposes. A conventional content analysis approach was used for coding. Results: Patient groups seem to differ in expectations and needs regarding self-management and eHealth for self-management purposes. People with diabetes reported most needs and benefits regarding self-management and were most willing to use eHealth, followed by the COPD group. People with a cardiovascular condition mentioned having fewer needs for self-management support, because their disease had little impact on their life. In all patient groups it was reported that the patient, not the care professional, should choose whether or not to use eHealth. Moreover, participants reported that eHealth should not replace, but complement personal care. Many participants reported expecting feelings of anxiety by doing measurement themselves and uncertainty about follow-up of deviant data of measurements. In addition, many participants worried about the implementation of eHealth being a consequence of budget cuts in care. Conclusion: This study suggests that aspects of eHealth, and the way in which it should be implemented, should be tailored to the patient. Patients’ expected benefits of using eHealth to support self-management and their perceived controllability over their disease seem to play an important role in patients’ willingness to use eHealth for self-management purposes

    Access to primary care for socio-economically disadvantaged older people in rural areas: exploring realist theory using structural equation modelling in a linked dataset

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    Background: Realist approaches seek to answer questions such as ‘how?’, ‘why?’, ‘for whom?’, ‘in what circumstances?’ and ‘to what extent?’ interventions ‘work’ using context-mechanism-outcome (CMO) configurations. Quantitative methods are not well-established in realist approaches, but structural equation modelling (SEM) may be useful to explore CMO configurations. Our aim was to assess the feasibility and appropriateness of SEM to explore CMO configurations and, if appropriate, make recommendations based on our access to primary care research. Our specific objectives were to map variables from two large population datasets to CMO configurations from our realist review looking at access to primary care, generate latent variables where needed, and use SEM to quantitatively test the CMO configurations. Methods: A linked dataset was created by merging individual patient data from the English Longitudinal Study of Ageing and practice data from the GP Patient Survey. Patients registered in rural practices and who were in the highest deprivation tertile were included. Three latent variables were defined using confirmatory factor analysis. SEM was used to explore the nine full CMOs. All models were estimated using robust maximum likelihoods and accounted for clustering at practice level. Ordinal variables were treated as continuous to ensure convergence. Results: We successfully explored our CMO configurations, but analysis was limited because of data availability. Two hundred seventy-six participants were included. We found a statistically significant direct (context to outcome) or indirect effect (context to outcome via mechanism) for two of nine CMOs. The strongest association was between ‘ease of getting through to the surgery’ and ‘being able to get an appointment’ with an indirect mediated effect through convenience (proportion of the indirect effect of the total was 21%). Healthcare experience was not directly associated with getting an appointment, but there was a statistically significant indirect effect through convenience (53% mediated effect). Model fit indices showed adequate fit. Conclusions: SEM allowed quantification of CMO configurations and could complement other qualitative and quantitative techniques in realist evaluations to support inferences about strengths of relationships. Future research exploring CMO configurations with SEM should aim to collect, preferably continuous, primary data

    Varicella susceptibility and transmission dynamics in Slovenia

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    <p>Abstract</p> <p>Background</p> <p>A cross-sectional, age-stratified study was conducted to determine varicella-zoster seroprevalence and force of infection in Slovenia.</p> <p>Methods</p> <p>3689 serum samples were tested for VZV IgG antibodies with an enzyme immunoassay. Semiparametric and parametric modelling were used to estimate the force of infection.</p> <p>Results</p> <p>Overall, 85.6% of serum samples were seropositive. Age-specific prevalence rose rapidly in preschool children and over 90% of 8 years old tested positive for VZV. However, 2.8% of serum samples among women of childbearing age were seronegative. Semiparametric modelling yielded force of infection estimates of 0.182 (95% CI 0.158-0.206), 0.367 (95% CI 0.285-0.448) and 0.008 (95% CI 0.0-0.032) for age groups 0.5- < 6, 6-11 and ≥12 years, respectively, and 0.175 (95% CI 0.147-0.202), 0.391 (95% CI 0.303-0.480) and 0.025 (95% CI 0.003-0.046) for age groups 0.5- < 5, 5-9 and ≥10 years, respectively.</p> <p>Conclusions</p> <p>Regardless of the age grouping used, the highest transmission occurred in children in their first years of school.</p
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