Web-Based Cognitive Behavioral Therapy for Female Patients With Eating Disorders: Randomized Controlled Trial

Background: Many patients with eating disorders do not receive help for their symptoms, even though these disorders have severe morbidity. The Internet may offer alternative low-threshold treatment interventions.\ud \ud Objective: This study evaluated the effects of a Web-based cognitive behavioral therapy (CBT) intervention using intensive asynchronous therapeutic support to improve eating disorder psychopathology, and to reduce body dissatisfaction and related health problems among patients with eating disorders.\ud \ud Methods: A two-arm open randomized controlled trial comparing a Web-based CBT intervention to a waiting list control condition (WL) was carried out among female patients with bulimia nervosa (BN), binge eating disorder (BED), and eating disorders not otherwise specified (EDNOS). The eating disorder diagnosis was in accordance with the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, and was established based on participants’ self-report. Participants were recruited from an open-access website, and the intervention consisted of a structured two-part program within a secure Web-based application. The aim of the first part was to analyze participant’s eating attitudes and behaviors, while the second part focused on behavioral change. Participants had asynchronous contact with a personal therapist twice a week, solely via the Internet. Self-report measures of eating disorder psychopathology (primary outcome), body dissatisfaction, physical health, mental health, self-esteem, quality of life, and social functioning were completed at baseline and posttest.\ud \ud Results: A total of 214 participants were randomized to either the Web-based CBT group (n=108) or to the WL group (n=106) stratified by type of eating disorder (BN: n=44; BED: n=85; EDNOS: n=85). Study attrition was low with 94% of the participants completing the posttest assignment. Overall, Web-based CBT showed a significant improvement over time for eating disorder psychopathology (F97=63.07, P<.001, d=.82) and all secondary outcome measures (effect sizes between d=.34 to d=.49), except for Body Mass Index. WL participants also improved on most outcomes; however, effects were smaller in this group with significant between-group effects for eating disorder psychopathology (F201=9.42, P=.002, d=.44), body dissatisfaction (F201=13.16, P<.001, d=.42), physical health (F200=12.55, P<.001, d=.28), mental health (F203=4.88, P=.028, d=.24), self-esteem (F202=5.06, P=.026, d=.20), and social functioning (F205=7.93, P=.005, d=.29). Analyses for the individual subgroups BN, BED, and EDNOS showed that eating disorder psychopathology improved significantly over time among Web-based CBT participants in all three subgroups; however, the between-group effect was significant only for participants with BED (F78=4.25, P=.043, d=.61).\ud \ud Conclusions: Web-based CBT proved to be effective in improving eating disorder psychopathology and related health among female patients with eating disorder

Induction of c-Jun immunoreactivity in spinal cord and brainstem neurons in a transgenic mouse model for amyotrophic lateral sclerosis

Transgenic mice carrying amyotrophic lateral sclerosis (ALS)-linked superoxide dismutase 1 (SOD1) mutations develop a motoneuron disease resembling human ALS. c-Jun is a transcription factor frequently induced in injured neurons. In this study we have examined the distribution of c-Jun-immunoreactivity in the brainstem and spinal cord of transgenic SOD1 mice with a glycine 93 alanine (G93A) mutation. In non-transgenic littermates c-Jun immunostaining was predominantly situated in motoneurons. The number of c-Jun immunoreactive motoneuron was reduced in SOD1(G93A) mice due to pronounced loss of motoneurons. In SOD1(G93A) mice, however, c-Jun-immunoreactivity was strongly induced in neurons in the intermediate zone (Rexed's laminae V-VIII and X) of the spinal cord and throughout the brainstem reticular formation. These findings are of interest since increased levels of c-jun also have been found in the intermediate zone of the spinal cord of ALS patients. Thus c-Jun may be involved in the neurodegenerative processes both in ALS and in motoneuron disease in SOD1(G93A) mice

Growth hormone treatment in growth-retarded adolescents after renal transplant

Growth failure is a psychosocial problem for many patients who have undergone renal transplantation. 18 adolescents (mean age 15 6, range 11·3-19 5) with severe growth retardation after renal transplantation were treated with biosynthetic growth hormone (GH) for 2 years. All received prednisone, administered daily or on alternate days, with azathioprine and/or cyclosporin A. 16 were blindly assigned to one of two GH doses (4 vs 8 IU per m2 per day). Growth, bone maturation, renal graft function, plasma insulin-like growth factors, serum binding proteins, and other biochemical parameters were checked regularly. Glomerular filtration rate and effective renal plasma flow were tested with 125I-Thalamate and 131I-Hippuran. Data on growth and glomerular filtration rate during GH treatment were also compared with those of matched non-GH-treated controls. Mean (standard deviation) increment in height after 2 years of GH was 15·7 (5·1) cm, significantly greater (p25% reduction in glomerular filtration rate over 2 years was not significantly higher in GH-treated patients than in non-GH-treated controls (39% vs 32%, p=0·97). Although a few patients had deterioration of graft function, we could not find a relation with GH treatment. Our results show that sustained improvement of height can be achieved with GH in severely growth-retarded adolescents after renal transplantation

Using Co-solvability to Model and Exploit Synergetic Effects in Evolution

We introduce, analyze, and experimentally verify the concept of co-solvability, meant as the ability of a solution maintained by an evolutionary run to solve (correctly process) a pair of fitness cases (tests). The method based on this concept can be considered as a second-order implicit fitness sharing, where solutions compete for the rewards granted for solving pairs of tests, rather than single tests. We prove that co-solvability fitness function is by definition synergistic and imposes selection pressure which is qualitatively different from that induced by standard fitness function or implicit fitness sharing. The results of experimental verification on eight genetic programming tasks demonstrate that evolutionary runs driven by the proposed fitness function usually converge faster to global optima than other methods

Relativistic Mean Field Model with Generalized Derivative Nucleon-Meson Couplings

The quantum hadrodynamics (QHD) model with minimal nucleon-meson couplings is generalized by introducing couplings of mesons to derivatives of the nucleon field in the Lagrangian density. This approach allows an effective description of a state-dependent in-medium interaction in the mean-field approximation. Various parametrizations for the generalized couplings are developed and applied to infinite nuclear matter. In this approach, scalar and vector self-energies depend on both density and momentum similarly as in the Dirac-Brueckner theory. The Schr\"{o}diger-equivalent optical potential is much less repulsive at high nucleon energies as compared to standard relativistic mean field models and thus agrees better with experimental findings. The derivative couplings in the extended model have significant effects on properties of symmetric nuclear matter and neutron matter.Comment: 35 pages, 1 table, 10 figure

Baseline radiomics features and MYC rearrangement status predict progression in aggressive B-cell lymphoma

We investigated whether the outcome prediction of patients with aggressive B-cell lymphoma can be improved by combining clinical, molecular genotype, and radiomics features. MYC, BCL2, and BCL6 rearrangements were assessed using fluorescence in situ hybridization. Seventeen radiomics features were extracted from the baseline positron emission tomography–computed tomography of 323 patients, which included maximum standardized uptake value (SUV(max)), SUV(peak), SUV(mean), metabolic tumor volume (MTV), total lesion glycolysis, and 12 dissemination features pertaining to distance, differences in uptake and volume between lesions, respectively. Logistic regression with backward feature selection was used to predict progression after 2 years. The predictive value of (1) International Prognostic Index (IPI); (2) IPI plus MYC; (3) IPI, MYC, and MTV; (4) radiomics; and (5) MYC plus radiomics models were tested using the cross-validated area under the curve (CV-AUC) and positive predictive values (PPVs). IPI yielded a CV-AUC of 0.65 ± 0.07 with a PPV of 29.6%. The IPI plus MYC model yielded a CV-AUC of 0.68 ± 0.08. IPI, MYC, and MTV yielded a CV-AUC of 0.74 ± 0.08. The highest model performance of the radiomics model was observed for MTV combined with the maximum distance between the largest lesion and another lesion, the maximum difference in SUV(peak) between 2 lesions, and the sum of distances between all lesions, yielding an improved CV-AUC of 0.77 ± 0.07. The same radiomics features were retained when adding MYC (CV-AUC, 0.77 ± 0.07). PPV was highest for the MYC plus radiomics model (50.0%) and increased by 20% compared with the IPI (29.6%). Adding radiomics features improved model performance and PPV and can, therefore, aid in identifying poor prognosis patients

A Multimodal Problem for Competitive Coevolution

Coevolutionary algorithms are a special kind of evolutionary algorithm with advantages in solving certain specific kinds of problems. In particular, competitive coevolutionary algorithms can be used to study problems in which two sides compete against each other and must choose a suitable strategy. Often these problems are multimodal - there is more than one strong strategy for each side. In this paper, we introduce a scalable multimodal test problem for competitive coevolution, and use it to investigate the effectiveness of some common coevolutionary algorithm enhancement techniques

The Fluorescence Detector of the Pierre Auger Observatory

The Pierre Auger Observatory is a hybrid detector for ultra-high energy cosmic rays. It combines a surface array to measure secondary particles at ground level together with a fluorescence detector to measure the development of air showers in the atmosphere above the array. The fluorescence detector comprises 24 large telescopes specialized for measuring the nitrogen fluorescence caused by charged particles of cosmic ray air showers. In this paper we describe the components of the fluorescence detector including its optical system, the design of the camera, the electronics, and the systems for relative and absolute calibration. We also discuss the operation and the monitoring of the detector. Finally, we evaluate the detector performance and precision of shower reconstructions.Comment: 53 pages. Submitted to Nuclear Instruments and Methods in Physics Research Section

Atmospheric effects on extensive air showers observed with the Surface Detector of the Pierre Auger Observatory

Atmospheric parameters, such as pressure (P), temperature (T) and density, affect the development of extensive air showers initiated by energetic cosmic rays. We have studied the impact of atmospheric variations on extensive air showers by means of the surface detector of the Pierre Auger Observatory. The rate of events shows a ~10% seasonal modulation and ~2% diurnal one. We find that the observed behaviour is explained by a model including the effects associated with the variations of pressure and density. The former affects the longitudinal development of air showers while the latter influences the Moliere radius and hence the lateral distribution of the shower particles. The model is validated with full simulations of extensive air showers using atmospheric profiles measured at the site of the Pierre Auger Observatory.Comment: 24 pages, 9 figures, accepted for publication in Astroparticle Physic