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Female Genital Schistosomiasis (FGS), commonly referred to as Female Bilharzia (FB), is a prevalent yet socially obscure disease. Caused by a waterborne parasite, it affects millions of people all over the world. Although it is a global health concern, FB is more pervasive in Sub-Saharan Africa. Motivated by the rapid response to treatment as demonstrated by rural Zimbabwean women, an organisation known as the FB Project conducted research exclusively with this group. Based in KwaZulu-Natal's Ugu District (Port Shepstone), the FB Project sought to raise an awareness of, to treat and ultimately eradicate the FB threat. This study investigated the most appropriate communication tools for achieving these goals. In 2012, in-depth semi-structured interviews were conducted with a sample of 20 female teenagers from both rural and urban areas across the Ugu District. Their perceptions of this issue highlighted various sociocultural, economic and logistical constraints to effective FB communication. This paper explores these barriers and the implications they have for realising the project's goals. The opinions that are voiced by the participants underscore the value of adopting a participatory communication approach to addressing a health problem. The researcher's observations are also integrated into the discussion. The responses gathered from the participants were considered as recommendations that could support the design of a contextually-sensitive FB awareness campaign. [ABSTRACT FROM AUTHOR]

Lars Henrik Myklebust,1 Knut Sørgaard,1,2 Rolf Wynn21Psychiatric Research Centre of North Norway, Nordland Hospital Trust, Bodø, 2Department of Clinical Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, NorwayObjectives: In the last few decades, there has been a restructuring of the psychiatric services in many countries. The complexity of these systems may represent a challenge to patients that suffer from serious psychiatric disorders. We examined whether local integration of inpatient and outpatient services in contrast to centralized institutions strengthened continuity of care.Methods: Two different service-systems were compared. Service-utilization over a 4-year period for 690 inpatients was extracted from the patient registries. The results were controlled for demographic variables, model of service-system, central inpatient admission or local inpatient admission, diagnoses, and duration of inpatient stays.Results: The majority of inpatients in the area with local integration of inpatient and outpatient services used both types of care. In the area that did not have beds locally, many patients that had been hospitalized did not receive outpatient follow-up. Predictors of inpatients' use of outpatient psychiatric care were: Model of service-system (centralized vs decentralized), a diagnosis of affective disorder, central inpatient admission only, and duration of inpatient stays.Conclusion: Psychiatric centers with local inpatient units may positively affect continuity of care for patients with severe psychiatric disorders, probably because of a high functional integration of inpatient and outpatient care.Keywords: psychiatry, hospitalization, decentralization, outpatients, continuity of care, health service research, affective

Abstract Background There are few reports on the effects of extensive decentralization of mental health services. We investigated the total patterns of utilization in a local-bed model and a central-bed model. Methods In a time-trend case-registry design, 7635 single treatment episodes, from the specialist and municipality services in 2003-2006, were linked to 2975 individual patients over all administrative levels. Patterns of utilization were analyzed by univariate comparisons and multivariate regressions. Results Total treated prevalence was consistently higher for the central-bed system. Outpatient utilization increased markedly, in the central-bed system. Utilization of psychiatric beds decreased, only in the central-bed system. Utilization of highly supported municipality units increased in both systems. Total utilization of all types of services, showed an additive pattern in the local-bed system and a substitutional pattern in the central-bed system. Only severe diagnoses predicted inpatient admission in the central-bed system, whereas also anxiety-disorders and outpatient consultations predicted inpatient admission in the local-bed system. Characteristics of the inpatient populations changed markedly over time, in the local-bed system. Conclusions Geographical availability is not important as a filter in patients' pathway to inpatient care, and the association between distance to hospital and utilization of psychiatric beds may be an historical artefact. Under a public health-insurance system, local psychiatric personnel as gatekeepers for inpatient care may be of greater importance than the availability of local psychiatric beds. Specialist psychiatric beds and highly supported municipality units for people with mental health problems do not work together in terms of utilization. Outpatient and day-hospital services may be filters in the pathway to inpatient care, however this depends on the structure of the whole service-system. Local integration of psychiatric services may bring about additive, rather than substitutional patterns of total utilization. A large proportion of decentralized psychiatric beds may hinder the development of various local psychiatric services, with negative consequences for overall treated prevalence.

Abstract Background The VELO study is a comparative study of two Community Mental Health Centres (CMHC) in Northern Norway. The CMHCs are organized differently: one has no local inpatient unit, the other has three. Both CMHCs use the Central Mental Hospital situated rather far away for compulsory and other admissions, but one uses mainly local beds while the other uses only central hospital beds. In this part of the study the ward staffs level of competence and treatment philosophy in the CMHCs bed units are compared to Central Mental Hospital units. Differences may influence health service given, resulting in different treatment for similar patients from the two CMHCs. Methods 167 ward staff at Vesterålen CMHCs bed units and the Nordland Central Mental Hospital bed units answered two questionnaires on clinical practice: one with questions about education, work experience and clinical orientation; the other with questions about the philosophy and practice at the unit. An extended version of Community Program Philosophy Scale (CPPS) was used. Data were analyzed with descriptive statistics, non-parametric test and logistic regression. Results We found significant differences in several aspects of competence and treatment philosophy between local bed units and central bed units. CMHC staff are younger, have shorter work experience and a more generalised postgraduate education. CMHC emphasises family therapy and cooperation with GP, while Hospital staff emphasise diagnostic assessment, medication, long term treatment and handling aggression. Conclusion The implications of the differences found, and the possibility that these differences influence the treatment mode for patients with similar psychiatric problems from the two catchment areas, are discussed.

Abstract Background Relapse due to chemoresistant residual disease is a major cause of death in acute myelogenous leukemia (AML). The present study was undertaken to elucidate the molecular mechanisms of chemoresistance by comparing differential gene expression in blasts from patients with resistant relapsing AML and chemosensitive AML. Results About 20 genes were identified as preferentially expressed in blasts pooled from patients with resistant disease, as compared to chemosensitive AML blasts, based on differential gene expression screening. Half of these genes encoded proteins related to protein translation, of these a novel protein related to the ribosomal stalk protein P0. Other upregulated mRNAs coded for cytochrome C oxidase III, the transcription factors ERF-2/TIS11d, and the p75 and p52 splice variants of Lens Epithelial Derived Growth Factor (LEDGF). Analysis of blasts from single patients disclosed that LEDGF/p75 was the most consistently upregulated mRNA in resistant AML. Transfection experiments demonstrated that LEDGF/p75 and p52b antagonized daunorubicin-induced and cAMP-induced apoptosis in an AML cell line. Also HEK-293 cells were protected against daunorubicin by LEDGF/p75 and p52b, whereas LEDGF/p52 splice variants lacking exon 6 had proapoptotic effects. Interestingly, full length LEDGF/p75 protected against truncated pro-apoptotic LEDGF/p75. Conclusion Our results provide evidence for an association between the overexpression of genes encoding survival proteins like LEDGF/p75 and chemo-resistance in acute myelogenous leukemia. LEDGF/p75 has previously not been shown to protect against chemotherapy, and is a potential drug target in AML.

Background: The electrophysiological mechanism connecting mitral valve prolapse (MVP), premature ventricular complexes and life-threatening ventricular arrhythmia is unknown. A common hypothesis is that stretch activated channels (SACs) play a significant role. SACs can trigger depolarizations or shorten repolarization times in response to myocardial stretch. Through these mechanisms, pathological traction of the papillary muscle (PM), as has been observed in patients with MVP, may induce irregular electrical activity and result in reentrant arrhythmia., Methods: Based on a patient with MVP and mitral annulus disjunction, we modeled the effect of excessive PM traction in a detailed medical image-derived ventricular model by activating SACs in the PM insertion region. By systematically varying the onset of SAC activation following sinus pacing, we identified vulnerability windows for reentry with 1 ms resolution. We explored how reentry was affected by the SAC reversal potential ( E SAC ) and the size of the region with simulated stretch (SAC region). Finally, the effect of global or focal fibrosis, modeled as reduction in tissue conductivity or mesh splitting (fibrotic microstructure), was investigated., Results: In models with healthy tissue or fibrosis modeled solely as CV slowing, we observed two vulnerable periods of reentry: For E SAC of -10 and -30 mV, SAC activated during the T-wave could cause depolarization of the SAC region which lead to reentry. For E SAC of -40 and -70 mV, SAC activated during the QRS complex could result in early repolarization of the SAC region and subsequent reentry. In models with fibrotic microstructure in the SAC region, we observed micro-reentries and a larger variability in which times of SAC activation triggered reentry. In these models, 86% of reentries were triggered during the QRS complex or T-wave. We only observed reentry for sufficiently large SAC regions ( > = 8 mm radius in models with healthy tissue)., Conclusion: Stretch of the PM insertion region following sinus activation may initiate ventricular reentry in patients with MVP, with or without fibrosis. Depending on the SAC reversal potential and timing of stretch, reentry may be triggered by ectopy due to SAC-induced depolarizations or by early repolarization within the SAC region., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Myklebust, Monopoli, Balaban, Aabel, Ribe, Castrini, Hasselberg, Bugge, Five, Haugaa, Maleckar and Arevalo.)

Introduction: Patients with non-ischemic cardiomyopathy (NICM) are at risk for ventricular arrhythmias, but diagnosis and treatment planning remain a serious clinical challenge. Although computational modeling has provided valuable insight into arrhythmic mechanisms, the optimal method for simulating reentry in NICM patients with structural disease is unknown. Methods: Here, we compare the effects of fibrotic representation on both reentry initiation and reentry morphology in patient-specific cardiac models. We investigate models with heterogeneous networks of non-conducting structures (cleft models) and models where fibrosis is represented as a dense core with a surrounding border zone (non-cleft models). Using segmented cardiac magnetic resonance with late gadolinium enhancement (LGE) of five NICM patients, we created 185 3D ventricular electrophysiological models with different fibrotic representations (clefts, reduced conductivity and ionic remodeling). Results: Reentry was induced by electrical pacing in 647 out of 3,145 simulations. Both cleft and non-cleft models can give rise to double-loop reentries meandering through fibrotic regions (Type 1-reentry). When accounting for fibrotic volume, the initiation sites of these reentries are associated with high local fibrotic density (mean LGE in cleft models: p < 0.001, core volume in non-cleft models: p = 0.018, negative binomial regression). In non-cleft models, Type 1-reentries required slow conduction in core tissue (non-clefts c models) as opposed to total conduction block. Incorporating ionic remodeling in fibrotic regions can give rise to single- or double-loop rotors close to healthy-fibrotic interfaces (Type 2-reentry). Increasing the cleft density or core-to-border zone ratio in cleft and non-cleft c models, respectively, leads to increased inducibility and a change in reentry morphology from Type 2 to Type 1. Conclusions: By demonstrating how fibrotic representation affects reentry morphology and location, our findings can aid model selection for simulating arrhythmogenesis in NICM., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Myklebust, Maleckar and Arevalo.)

Background: Remodeling due to myocardial infarction (MI) significantly increases patient arrhythmic risk. Simulations using patient-specific models have shown promise in predicting personalized risk for arrhythmia. However, these are computationally- and time- intensive, hindering translation to clinical practice. Classical machine learning (ML) algorithms (such as K-nearest neighbors, Gaussian support vector machines, and decision trees) as well as neural network techniques, shown to increase prediction accuracy, can be used to predict occurrence of arrhythmia as predicted by simulations based solely on infarct and ventricular geometry. We present an initial combined image-based patient-specific in silico and machine learning methodology to assess risk for dangerous arrhythmia in post-infarct patients. Furthermore, we aim to demonstrate that simulation-supported data augmentation improves prediction models, combining patient data, computational simulation, and advanced statistical modeling, improving overall accuracy for arrhythmia risk assessment. Methods: MRI-based computational models were constructed from 30 patients 5 days post-MI (the "baseline" population). In order to assess the utility biophysical model-supported data augmentation for improving arrhythmia prediction, we augmented the virtual baseline patient population. Each patient ventricular and ischemic geometry in the baseline population was used to create a subfamily of geometric models, resulting in an expanded set of patient models (the "augmented" population). Arrhythmia induction was attempted via programmed stimulation at 17 sites for each virtual patient corresponding to AHA LV segments and simulation outcome, "arrhythmia," or "no-arrhythmia," were used as ground truth for subsequent statistical prediction (machine learning, ML) models. For each patient geometric model, we measured and used choice data features: the myocardial volume and ischemic volume, as well as the segment-specific myocardial volume and ischemia percentage, as input to ML algorithms. For classical ML techniques (ML), we trained k-nearest neighbors, support vector machine, logistic regression, xgboost, and decision tree models to predict the simulation outcome from these geometric features alone. To explore neural network ML techniques, we trained both a three - and a four-hidden layer multilayer perceptron feed forward neural networks (NN), again predicting simulation outcomes from these geometric features alone. ML and NN models were trained on 70% of randomly selected segments and the remaining 30% was used for validation for both baseline and augmented populations. Results: Stimulation in the baseline population (30 patient models) resulted in reentry in 21.8% of sites tested; in the augmented population (129 total patient models) reentry occurred in 13.0% of sites tested. ML and NN models ranged in mean accuracy from 0.83 to 0.86 for the baseline population, improving to 0.88 to 0.89 in all cases. Conclusion: Machine learning techniques, combined with patient-specific, image-based computational simulations, can provide key clinical insights with high accuracy rapidly and efficiently. In the case of sparse or missing patient data, simulation-supported data augmentation can be employed to further improve predictive results for patient benefit. This work paves the way for using data-driven simulations for prediction of dangerous arrhythmia in MI patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Maleckar, Myklebust, Uv, Florvaag, Strøm, Glinge, Jabbari, Vejlstrup, Engstrøm, Ahtarovski, Jespersen, Tfelt-Hansen, Naumova and Arevalo.)