ABSTRACT
OBJECTIVE: The study aims to assess the acceptance, chances and barriers of an online self-management program (moodgym) for depression from the perspective of experts and patients in inpatient psychiatric settings. METHODS: Paper-pencil interviews were conducted with nâ=â181 depressed inpatients (nâ=â181, pre-post-assessment after 8 weeks) and nâ=â31 medical experts. Two regression models were carried out to investigate factors associated with the uptake and the user acceptance of moodgym. Chances and barriers were analysed qualitatively. RESULTS: Experts and patients reported moderate to high user acceptance. 59â% (nâ=â107) of the patients logged in to moodgym. Factors associated with the uptake were the educational level and treatment preferences. The user acceptance was influenced by the patients' self-rated health and the frequency of using moodgym. Relevant barriers anticipated by experts were limited computer skills, difficulties in concentration and a severe course of depression. Patients highlighted the ease of use, the moodgym characters and the flexible availability. CONCLUSIONS: moodgym may represent a complementary treatment option for depressive disorders in an inpatient setting.
Subject(s)
Depressive Disorder , Internet , Self-Management , Adult , Cognitive Behavioral Therapy , Depressive Disorder/therapy , Female , Germany , Humans , Inpatients , Male , Middle Aged , Young AdultABSTRACT
BACKGROUND: Cobalt-ferrite nanoparticles (Co-Fe NPs) are attractive for nanotechnology-based therapies. Thus, exploring their effect on viability of seven different cell lines representing different organs of the human body is highly important. METHODS: The toxicological effects of Co-Fe NPs were studied by in-vitro exposure of A549 and NCIH441 cell-lines (lung), precision-cut lung slices from rat, HepG2 cell-line (liver), MDCK cell-line (kidney), Caco-2 TC7 cell-line (intestine), TK6 (lymphoblasts) and primary mouse dendritic-cells. Toxicity was examined following exposure to Co-Fe NPs in the concentration range of 0.05 -1.2 mM for 24 and 72 h, using Alamar blue, MTT and neutral red assays. Changes in oxidative stress were determined by a dichlorodihydrofluorescein diacetate based assay. Data analysis and predictive modeling of the obtained data sets were executed by employing methods of Knowledge Discovery from Data with emphasis on a decision tree model (J48). RESULTS: Different dose-response curves of cell viability were obtained for each of the seven cell lines upon exposure to Co-Fe NPs. Increase of oxidative stress was induced by Co-Fe NPs and found to be dependent on the cell type. A high linear correlation (R2=0.97) was found between the toxicity of Co-Fe NPs and the extent of ROS generation following their exposure to Co-Fe NPs. The algorithm we applied to model the observed toxicity belongs to a type of supervised classifier. The decision tree model yielded the following order with decrease of the ranking parameter: NP concentrations (as the most influencing parameter), cell type (possessing the following hierarchy of cell sensitivity towards viability decrease: TK6 > Lung slices > NCIH441 > Caco-2 = MDCK > A549 > HepG2 = Dendritic) and time of exposure, where the highest-ranking parameter (NP concentration) provides the highest information gain with respect to toxicity. The validity of the chosen decision tree model J48 was established by yielding a higher accuracy than that of the well-known "naive bayes" classifier. CONCLUSIONS: The observed correlation between the oxidative stress, caused by the presence of the Co-Fe NPs, with the hierarchy of sensitivity of the different cell types towards toxicity, suggests that oxidative stress is one possible mechanism for the toxicity of Co-Fe NPs.
Subject(s)
Artificial Intelligence , Cobalt/toxicity , Ferric Compounds/toxicity , Metal Nanoparticles , Toxicology/methods , Algorithms , Animals , Caco-2 Cells , Cell Survival/drug effects , Data Mining , Decision Support Techniques , Decision Trees , Dogs , Dose-Response Relationship, Drug , Hep G2 Cells , Humans , Linear Models , Madin Darby Canine Kidney Cells , Mice , Oxidative Stress/drug effects , Primary Cell Culture , Rats , Reactive Oxygen Species/metabolism , Time Factors , Tissue Culture TechniquesABSTRACT
The toxicological effects of cobalt nanoparticles (Co-NPs) aggregates were examined and compared with those of cobalt ions (Co-ions) using six different cell lines representing lung, liver, kidney, intestine, and the immune system. Dose-response curves were studied in the concentration range of 0.05-1.0 mM, employing 3-(4,5-dimethylthiazol-2-Yl)-2,5-diphenyltetrazolium bromide test, neutral red, and Alamar blue as end point assays following exposures for 48 and 72 h. Data analysis and predictive modeling of the obtained data sets were executed by employing a decision tree model (J48), where training and validation were carried out by an iterative process. It was established, as expected, that concentration is the highest rank parameter. This is because concentration parameter provides the highest information gain with respect to toxicity. The second-rank parameter emerged to be either the compound type (Co-ions or Co-NPs) or the cell model, depending on the concentration range. The third and the lowest rank in the model was exposure duration. The hierarchy of cell sensitivity toward cobalt ions was found to obey the following sequence of cell lines: A549 > MDCK > NCIH441 > Caco-2 > HepG2 > dendritic cells (DCs), with A549 being the most sensitive cell line and primary DCs were the least sensitive ones. However, a different hierarchy pattern emerged for Co-NPs: A549 = MDCK = NCIH441 = Caco-2 > DCs > HepG2. The overall findings are in line with the hypothesis that the toxic effects of aggregated cobalt NPs are mainly due to cobalt ion dissolution from the aggregated NPs.
Subject(s)
Cobalt/toxicity , Ions/toxicity , Metal Nanoparticles/toxicity , Algorithms , Animals , Caco-2 Cells , Female , Hep G2 Cells , Humans , Mice , Mice, Inbred C57BL , Models, Biological , Reproducibility of ResultsABSTRACT
Generally animal and human cells use oxygen during their whole life. Consequently the oxygen use is a simple indicator to test the vitality of cells. When the vitality decreases by the delivery of toxic substances the decrease can be observed directly by the oxygen-use of the cells. To get fast information of the vitality of cells we have measured the O2-tension by testing a new model of a bioreactor, the Cell Vitality Checker 96 (CVC96), in practical application. With this CVC96, soon a simple test will exist for the measurement of the oxygen use. In this respect the question had to be answered whether the use in the laboratory is easy and whether oxygen as a parameter in the vitality test can also be applied in future for problems in the field of material testing.
