Multimodal MR Prediction Models for Late-Life Depression and Treatment Response

Currently, depression diagnosis relies primarily on behavioral symptoms and signs, instead of underlying brain characteristics, and treatment is guided by trial and error instead of individual suitability associated with underlying brain characteristics. Also, previous brain-imaging studies attempting to resolve this issue have traditionally focused on mid-life depression using a single imaging modality and region-based approach, which may not fully explain the complexity of the underlying brain characteristics; especially for late-life depression. We aimed to evaluate and compare underlying brain characteristics of late-life depression diagnosis and treatment response by estimating accurate prediction models using multi-modal magnetic resonance imaging and non-imaging measures. Based on our finding, late-life depression diagnosis and treatment response predictors involve measures from different imaging modalities, which are indicative of differences in underlying brain characteristics

STATISTICAL OPTIMIZATION AND EVALUATION OF ETHOSOMAL MICONAZOLE NITRATE SUSPENSION

Objective: The objectives of the present study were to optimize and evaluate the ethosomal suspension of miconazole nitrate for the treatment of local and systemic fungal infections. Methods: Miconazole topical formulation is prepared for better patient compliance and to reduce the dose of a drug. Miconazole nitrate ethosomes were prepared by the cold method using factorial designing with Ethanol(X1), IPA(Isopropyl alcohol)(X2), and Lecithin(X3) as Independent variables and % EE(Entrapment efficiency)(Y1) and % DR(drug release at 8th h)(Y2) was selected as responses. Results: The results obtained in the design showed that there was no significant interaction among factors. The lecithin concentration had a positive response on % EE, while ethanol concentration and IPA had a positive effect. For % DR, Ethanol, and IPA showed a positive effect and Lecithin had a negative response. The formulation EM22 (3 ml X1,3 ml X2 and 300 mg of X3) characterized by high % EE(77.3 %) and optimum % DR(94.2%) and formulation EM6 (2 ml X1,2 ml X2 and 100 mg of X3) characterized by high % DR(97.32 %) and optimum % EE (74.8 %). EM22 was incorporated in the gel as it is showing more entrapment efficiency and compared with the marketed product for drug release. Conclusion: From the result, it was concluded that formulated ethosomal suspension and optimized gel have more drug release than marketed formulation so that formulated suspension can be used for the preparation of antifungal gels, creams, ointments for sustained release

Persistent physical symptoms reduction intervention: a system change and evaluation (PRINCE) - integrated GP care for persistent physical symptoms: protocol for a feasibility and cluster randomised waiting list, controlled trial

Introduction Persistent physical symptoms (PPS), also known as medically unexplained symptoms are associated with profound physical disability, psychological distress and high healthcare costs. England's annual National Health Service costs of attempting to diagnose and treat PPS amounts to approximately £3 billion. Current treatment relies on a positive diagnosis, life-style advice and drug therapy. However, many patients continue to suffer from ongoing symptoms and general practitioners (GPs) are challenged to find effective treatments. Training GPs in basic cognitive behavioural skills and providing self-help materials to patients could be useful, but availability in primary care settings is limited. Methods and analysis A cluster randomised waiting list, controlled trial will be conducted to assess the feasibility of an integrated approach to care in general practice. Approximately 240 patients with PPS will be recruited from 8 to 12 GP practices in London. GP practices will be randomised to 'integrated GP care plus treatment as usual' or waiting list control. Integrated GP care plus treatment as usual will include GP training in cognitive behavioural skills, GP supervision and written and audio visual materials for both GPs and participants. The primary objectives will be assessment of trial and intervention feasibility. Secondary objectives will include estimating the intracluster correlation coefficient for potential outcome measures for cluster effects in a sample size calculation. Feasibility parameters and identification of suitable primary and secondary outcomes for future trial evaluations will be assessed prerandomisation and at 12 and 24 weeks' postrandomisation, using a mixed-methods approach. Ethics and dissemination Ethical approval was granted by the Camberwell St Giles Ethics Committee. Results will be disseminated via peer-reviewed publications and conference presentations. This trial will inform researchers, clinicians, patients and healthcare providers about the feasibility and potential cost-effectiveness of an integrated approach to managing PPS in primary care. Trial registration number NCT02444520; Pre-results

Studying depression using imaging and machine learning methods

Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1) presents a background on depression, imaging, and machine learning methodologies; (2) reviews methodologies of past studies that have used imaging and machine learning to study depression; and (3) suggests directions for future depression-related studies

Recommendations for a Clinical Decision Support for the Management of Individuals with Chronic Kidney Disease

Background and objectives: Care for advanced CKD patients is suboptimal. CKD practice guidelines aim to close gaps in care, but making providers aware of guidelines is an ineffective implementation strategy. The Institute of Medicine has endorsed the use of clinical decision support (CDS) for implementing guidelines. The authors’ objective was to identify the requirements of an optimal CDS system for CKD management