Comparative efficacy of seven psychotherapeutic interventions for patients with depression: a network meta-analysis

BACKGROUND Previous meta-analyses comparing the efficacy of psychotherapeutic interventions for depression were clouded by a limited number of within-study treatment comparisons. This study used network meta-analysis, a novel methodological approach that integrates direct and indirect evidence from randomised controlled studies, to re-examine the comparative efficacy of seven psychotherapeutic interventions for adult depression. METHODS AND FINDINGS We conducted systematic literature searches in PubMed, PsycINFO, and Embase up to November 2012, and identified additional studies through earlier meta-analyses and the references of included studies. We identified 198 studies, including 15,118 adult patients with depression, and coded moderator variables. Each of the seven psychotherapeutic interventions was superior to a waitlist control condition with moderate to large effects (range d = -0.62 to d = -0.92). Relative effects of different psychotherapeutic interventions on depressive symptoms were absent to small (range d = 0.01 to d = -0.30). Interpersonal therapy was significantly more effective than supportive therapy (d = -0.30, 95% credibility interval [CrI] [-0.54 to -0.05]). Moderator analysis showed that patient characteristics had no influence on treatment effects, but identified aspects of study quality and sample size as effect modifiers. Smaller effects were found in studies of at least moderate (Δd = 0.29 [-0.01 to 0.58]; p = 0.063) and large size (Δd = 0.33 [0.08 to 0.61]; p = 0.012) and those that had adequate outcome assessment (Δd = 0.38 [-0.06 to 0.87]; p = 0.100). Stepwise restriction of analyses by sample size showed robust effects for cognitive-behavioural therapy, interpersonal therapy, and problem-solving therapy (all d>0.46) compared to waitlist. Empirical evidence from large studies was unavailable or limited for other psychotherapeutic interventions. CONCLUSIONS Overall our results are consistent with the notion that different psychotherapeutic interventions for depression have comparable benefits. However, the robustness of the evidence varies considerably between different psychotherapeutic treatments.

Accounting for baseline differences and measurement error in the analysis of change over time

If change over time is compared in several groups, it is important to take into account baseline values so that the comparison is carried out under the same preconditions. As the observed baseline measurements are distorted by measurement error, it may not be sufficient to include them as covariate. By fitting a longitudinal mixed-effects model to all data including the baseline observations and subsequently calculating the expected change conditional on the underlying baseline value, a solution to this problem has been provided recently so that groups with the same baseline characteristics can be compared. In this article, we present an extended approach where a broader set of models can be used. Specifically, it is possible to include any desired set of interactions between the time variable and the other covariates, and also, time-dependent covariates can be included. Additionally, we extend the method to adjust for baseline measurement error of other time-varying covariates. We apply the methodology to data from the Swiss HIV Cohort Study to address the question if a joint infection with HIV-1 and hepatitis C virus leads to a slower increase of CD4 lymphocyte counts over time after the start of antiretroviral therapy.

Improved dispersive analysis of the scalar form factor of the nucleon

We present a coupled system of integral equations for the pp → ¯NN and ¯K K → ¯N N S-waves derived from Roy–Steiner equations for pion–nucleon scattering. We discuss the solution of the corresponding two-channel Muskhelishvili–Omnès problem and apply the results to a dispersive analysis of the scalar form factor of the nucleon fully including ¯KK intermediate states. In particular, we determine the corrections Ds and DD, which are needed for the extraction of the pion– nucleon s term from pN scattering, and show that the difference DD −Ds = (−1.8±0.2)MeV is insensitive to the input pN parameters.

Cancer, meta-analysis and reporting biases: the case of erythropoiesis-stimulating agents.

Reporting and publication bias is a well-known problem in meta-analysis and healthcare research. In 2002 we conducted a meta-analysis on the effects of erythropoiesis-stimulating agents (ESAs) on overall survival in cancer patients, which suggested some evidence for improved survival in patients receiving ESAs compared with controls. However, a meta-analysis of individual patient data conducted several years later showed the opposite of our first meta-analysis, that is, evidence for increased on-study mortality and reduced overall survival in cancer patients receiving ESAs. We aimed to determine whether the results of our first meta-analysis could have been affected by publication and reporting biases and, if so, whether timely access to clinical study reports and individual patient data could have prevented this. We conducted a hypothetical meta-analysis for overall survival including all studies and study data that could have been available in 2002, at the time when we conducted our first meta-analysis. Compared with our original meta-analysis, which suggested an overall survival benefit for cancer patients receiving ESAs [hazard ratio (HR) 0.81, 95% confidence interval (CI) 0.67‒0.99], our hypothetical meta-analysis based on the results of all studies conducted at the time of the first analysis did not show evidence for a beneficial effect of ESAs on overall survival (HR 0.97, 95% CI 0.83‒1.12). Thus we have to conclude that our first meta-analysis showed misleading overall survival benefits due to publication and reporting biases, which could have been prevented by timely access to clinical study reports and individual patient data. Unrestricted access to clinical study protocols including amendments, clinical study reports and individual patient data is needed to ensure timely detection of both beneficial and harmful effects of healthcare interventions.

Is the relation between early post-session reports and treatment outcome an epiphenomenon of intake distress and early response? A multi-predictor analysis in outpatient psychotherapy

The early phase of psychotherapy has been regarded as a sensitive period in the unfolding of psychotherapy leading to positive outcomes. However, there is disagreement about the degree to which early (especially relationship-related) session experiences predict outcome over and above initial levels of distress and early response to treatment. The goal of the present study was to simultaneously examine outcome at post treatment as a function of (a) intake symptom and interpersonal distress as well as early change in well-being and symptoms, (b) the patient's early session-experiences, (c) the therapist's early session-experiences/interventions, and (d) their interactions. The data of 430 psychotherapy completers treated by 151 therapists were analyzed using hierarchical linear models. Results indicate that early positive intra- and interpersonal session experiences as reported by patients and therapists after the sessions explained 58% of variance of a composite outcome measure, taking intake distress and early response into account. All predictors (other than problem-activating therapists' interventions) contributed to later treatment outcomes if entered as single predictors. However, the multi-predictor analyses indicated that interpersonal distress at intake as well as the early interpersonal session experiences by patients and therapists remained robust predictors of outcome. The findings underscore that early in therapy therapists (and their supervisors) need to understand and monitor multiple interconnected components simultaneously

Proteomic analysis of the Theileria annulata schizont

The apicomplexan parasite, Theileria annulata, is the causative agent of tropical theileriosis, a devastating lymphoproliferative disease of cattle. The schizont stage transforms bovine leukocytes and provides an intriguing model to study host/pathogen interactions. The genome of T. annulata has been sequenced and transcriptomic data are rapidly accumulating. In contrast, little is known about the proteome of the schizont, the pathogenic, transforming life cycle stage of the parasite. Using one-dimensional (1-D) gel LC-MS/MS, a proteomic analysis of purified T. annulata schizonts was carried out. In whole parasite lysates, 645 proteins were identified. Proteins with transmembrane domains (TMDs) were under-represented and no proteins with more than four TMDs could be detected. To tackle this problem, Triton X-114 treatment was applied, which facilitates the extraction of membrane proteins, followed by 1-D gel LC-MS/MS. This resulted in the identification of an additional 153 proteins. Half of those had one or more TMD and 30 proteins with more than four TMDs were identified. This demonstrates that Triton X-114 treatment can provide a valuable additional tool for the identification of new membrane proteins in proteomic studies. With two exceptions, all proteins involved in glycolysis and the citric acid cycle were identified. For at least 29% of identified proteins, the corresponding transcripts were not present in the existing expressed sequence tag databases. The proteomics data were integrated into the publicly accessible database resource at EuPathDB (www.eupathdb.org) so that mass spectrometry-based protein expression evidence for T. annulata can be queried alongside transcriptional and other genomics data available for these parasites.

An Extended Hierarchical Task Analysis for Error Prediction in Medical Devices

This paper introduces an extended hierarchical task analysis (HTA) methodology devised to evaluate and compare user interfaces on volumetric infusion pumps. The pumps were studied along the dimensions of overall usability and propensity for generating human error. With HTA as our framework, we analyzed six pumps on a variety of common tasks using Norman’s Action theory. The introduced method of evaluation divides the problem space between the external world of the device interface and the user’s internal cognitive world, allowing for predictions of potential user errors at the human-device level. In this paper, one detailed analysis is provided as an example, comparing two different pumps on two separate tasks. The results demonstrate the inherent variation, often the cause of usage errors, found with infusion pumps being used in hospitals today. The reported methodology is a useful tool for evaluating human performance and predicting potential user errors with infusion pumps and other simple medical devices.

Identification of the Causative Bacteria in Musculoskeletal Infections Using 16s rDNA - Denaturing Gradient Gel Electrophoresis Analysis

Musculoskeletal infections are infections of the bone and surrounding tissues. They are currently diagnosed based on culture analysis, which is the gold standard for pathogen identification. However, these clinical laboratory methods are frequently inadequate for the identification of the causative agents, because a large percentage (25-50%) of confirmed musculoskeletal infections are false negatives in which no pathogen is identified in culture. My data supports these results. The goal of this project was to use PCR amplification of a portion of the 16S rRNA gene to test an alternative approach for the identification of these pathogens and to assess the diversity of the bacteria involved. The advantages of this alternative method are that it should increase sample sensitivity and the speed of detection. In addition, bacteria that are non-culturable or in low abundance can be detected using this molecular technique. However, a complication of this approach is that the majority of musculoskeletal infections are polymicrobial, which prohibits direct identification from the infected tissue by DNA sequencing of the initial 16S rDNA amplification products. One way to solve this problem is to use denaturing gradient gel electrophoresis (DGGE) to separate the PCR products before DNA sequencing. Denaturing gradient gel electrophoresis (DGGE) separates DNA molecules based on their melting point, which is determined by their DNA sequence. This analytical technique allows a mixture of PCR products of the same length that electrophoreses through agarose gels as one band, to be separated into different bands and then used for DNA sequence analysis. In this way, the DGGE allows for the identification of individual bacterial species in polymicrobial-infected tissue, which is critical for improving clinical outcomes. By combining the 16S rDNA amplification and the DGGE techniques together, an alternative approach for identification has been used. The 16S rRNA gene PCR-DGGE method includes several critical steps: DNA extraction from tissue biopsies, amplification of the bacterial DNA, PCR product separation by DGGE, amplification of the gel-extracted DNA, and DNA sequencing and analysis. Each step of the method was optimized to increase its sensitivity and for rapid detection of the bacteria present in human tissue samples. The limit of detection for the DNA extraction from tissue was at least 20 Staphylococcus aureus cells and the limit of detection for PCR was at least 0.05 pg of template DNA. The conditions for DGGE electrophoreses were optimized by using a double gradient of acrylamide (6 – 10%) and denaturant (30-70%), which increased the separation between distinct PCR products. The use of GelRed (Biotium) improved the DNA visualization in the DGGE gel. To recover the DNA from the DGGE gels the gel slices were excised, shredded in a bead beater, and the DNA was allowed to diffuse into sterile water overnight. The use of primers containing specific linkers allowed the entire amplified PCR product to be sequenced and then analyzed. The optimized 16S rRNA gene PCR-DGGE method was used to analyze 50 tissue biopsy samples chosen randomly from our collection. The results were compared to those of the Memorial Hermann Hospital Clinical Microbiology Laboratory for the same samples. The molecular method was congruent for 10 of the 17 (59%) culture negative tissue samples. In 7 of the 17 (41%) culture negative the molecular method identified a bacterium. The molecular method was congruent with the culture identification for 7 of the 33 (21%) positive cultured tissue samples. However, in 8 of the 33 (24%) the molecular method identified more organisms. In 13 of the 15 (87%) polymicrobial cultured tissue samples the molecular method identified at least one organism that was also identified by culture techniques. Overall, the DGGE analysis of 16S rDNA is an effective method to identify bacteria not identified by culture analysis.

Streaming Support for Data Intensive Cloud-Based Sequence Analysis

Cloud computing provides a promising solution to the genomics data deluge problem resulting from the advent of next-generation sequencing (NGS) technology. Based on the concepts of “resources-on-demand” and “pay-as-you-go”, scientists with no or limited infrastructure can have access to scalable and cost-effective computational resources. However, the large size of NGS data causes a significant data transfer latency from the client’s site to the cloud, which presents a bottleneck for using cloud computing services. In this paper, we provide a streaming-based scheme to overcome this problem, where the NGS data is processed while being transferred to the cloud. Our scheme targets the wide class of NGS data analysis tasks, where the NGS sequences can be processed independently from one another. We also provide the elastream package that supports the use of this scheme with individual analysis programs or with workflow systems. Experiments presented in this paper show that our solution mitigates the effect of data transfer latency and saves both time and cost of computation.

Combination of Psychological Intervention and Phosphodiesterase-5 Inhibitors for Erectile Dysfunction: A Narrative Review and Meta-Analysis

INTRODUCTION Erectile dysfunction (ED) is an increasing health problem that demands effective treatment. There is evidence that phosphodiesterase-5 inhibitors (PDE5-Is) and psychological intervention (PI) are effective treatment options; however, little is known about their comparative efficacy and the efficacy of combined treatments. AIM The aim of this systematic review and meta-analysis is to evaluate the comparative efficacy of PI, PDE5-Is, and their combination in the treatment of ED. MAIN OUTCOME MEASURES Primary outcome was ED symptoms, and secondary outcome was sexual satisfaction of the patient. METHODS A systematic literature search was conducted in order to identify relevant articles published between 1998 and 2012. We included randomized controlled trials and controlled trials comparing PI with PDE5-I treatment or one of them against a combination of both. RESULTS Eight studies with a total number of 562 patients were included in the meta-analysis. The results of the included studies are inconclusive, though they show a trend towards a larger effect of combined treatment compared with PI or PDE5-I treatment alone. The meta-analysis found that, overall, combined treatment was more efficacious for ED symptoms than PDE5-I treatment or PI alone. Combined treatment was more efficacious than PDE5-I use alone on sexual satisfaction. No differences were found between PDE5-Is and PI as stand-alone treatments. None of the moderators (treatment duration, methodological quality, or researcher allegiance) altered the effects. CONCLUSIONS The combination of PI and PDE5-Is is a promising strategy for a favorable outcome in ED and can be considered as a first-choice option for ED patients. Stronger RCTs are required to confirm this initial finding. Schmidt HM, Munder T, Gerger H, Frühauf S, and Barth J. Combination of psychological intervention and phosphodiesterase-5 inhibitors for erectile dysfunction: A narrative review and meta-analysis. J Sex Med **;**:**-**.

Isolation, characterization and functional analysis of the {\it xnf7\/} gene from {\it Xenopus laevis\/}

A fundamental problem in developmental biology concerns the mechanisms involved in the establishment of the embryonic axis. We are studying Xenopus nuclear factor 7 (xnf7) which we believe to be involved in dorsal-ventral patterning in Xenopus laevis. Xnf7 is a maternal gene product that is retained in the cytoplasm during early embryogenesis until the mid-blastula transition (MBT) when it reenters the nuclei. It is a member of a novel zinc finger proteins, the B-box family, consisting mainly of transcription factors and protooncogenes.^ The xnf7 gene is reexpressed during embryogenesis at the gastrula-neurula stage of development, with its zygotic expression limited to the central nervous system (CNS). In this study we showed that there are two different cDNAs coding for xnf7, xnf7-O and xnf7-B. They differ by 39 amino acid changes scattered throughout the cDNA. The expression of both forms of xnf7 is limited primarily to the central nervous system (CNS) and dorsal axial structures during later stages of embryogenesis.^ In order to study the spatial and temporal regulation of the gene, we screened a Xenopus genomic library using part of xnf7 cDNA as a probe. A genomic clone corresponding to the xnf7-O type was isolated, its 5$\sp\prime$ putative regulatory region sequenced, and its transcriptional initiation site mapped. The putative promoter region contained binding sites for Sp1, E2F, USF, a Pu box and AP1. CAT/xnf7 fusion genes were constructed containing various 5$\sp\prime$ deleted regions of the xnf7 promoter linked to a CAT (Chloramphenicol Acetyl Transferase) reporter vector. These constructs were injected into Xenopus oocytes and embryos to study the regions of the xnf7 promoter responsible for basal, temporal and spatial regulation of the gene. The activity of the fusion genes was measured by the conversion of chloramphenicol to its acetylated forms, and the spatial distribution of the transcripts by whole mount in situ hybridization. We showed that the elements involved in basal regulation of xnf7 lie within 121 basepairs upstream of the transcriptional inititiation site. A DNase I footprint analysis performed using oocyte extract showed that a E2F and 2 Sp1 sites were protected. During development, the fusion genes were expressed following the MBT, in accordance with the timing of the endogenous xnf7 gene. Spatially, the expression of the fusion gene containing 421 basepairs of the promoter was localized to the dorsal region of the embryo in a pattern that was almost identical to that detected with the endogenous transcripts. Therefore, the elements involved in spatial and temporal regulation of the xnf7 gene during development were contained within 421 basepairs upstream of the transcriptional initiation site. Future work will further define the elements involved in the spatial and temporal regulation and the trans-factors that interact with them. ^

Experimental Validation of Finite Element Analysis of Human Vertebral Collapse Under Large Compressive Strains

Osteoporosis-related vertebral fractures represent a major health problem in elderly populations. Such fractures can often only be diagnosed after a substantial deformation history of the vertebral body. Therefore, it remains a challenge for clinicians to distinguish between stable and progressive potentially harmful fractures. Accordingly, novel criteria for selection of the appropriate conservative or surgical treatment are urgently needed. Computer tomography-based finite element analysis is an increasingly accepted method to predict the quasi-static vertebral strength and to follow up this small strain property longitudinally in time. A recent development in constitutive modeling allows us to simulate strain localization and densification in trabecular bone under large compressive strains without mesh dependence. The aim of this work was to validate this recently developed constitutive model of trabecular bone for the prediction of strain localization and densification in the human vertebral body subjected to large compressive deformation. A custom-made stepwise loading device mounted in a high resolution peripheral computer tomography system was used to describe the progressive collapse of 13 human vertebrae under axial compression. Continuum finite element analyses of the 13 compression tests were realized and the zones of high volumetric strain were compared with the experiments. A fair qualitative correspondence of the strain localization zone between the experiment and finite element analysis was achieved in 9 out of 13 tests and significant correlations of the volumetric strains were obtained throughout the range of applied axial compression. Interestingly, the stepwise propagating localization zones in trabecular bone converged to the buckling locations in the cortical shell. While the adopted continuum finite element approach still suffers from several limitations, these encouraging preliminary results towardsthe prediction of extended vertebral collapse may help in assessing fracture stability in future work.

Growth Codes: Intermediate Performance Analysis and Application to Video

Growth codes are a subclass of Rateless codes that have found interesting applications in data dissemination problems. Compared to other Rateless and conventional channel codes, Growth codes show improved intermediate performance which is particularly useful in applications where partial data presents some utility. In this paper, we investigate the asymptotic performance of Growth codes using the Wormald method, which was proposed for studying the Peeling Decoder of LDPC and LDGM codes. Compared to previous works, the Wormald differential equations are set on nodes' perspective which enables a numerical solution to the computation of the expected asymptotic decoding performance of Growth codes. Our framework is appropriate for any class of Rateless codes that does not include a precoding step. We further study the performance of Growth codes with moderate and large size codeblocks through simulations and we use the generalized logistic function to model the decoding probability. We then exploit the decoding probability model in an illustrative application of Growth codes to error resilient video transmission. The video transmission problem is cast as a joint source and channel rate allocation problem that is shown to be convex with respect to the channel rate. This illustrative application permits to highlight the main advantage of Growth codes, namely improved performance in the intermediate loss region.

Sustainable Wastewater Management: Is it Possible to Regulate Micropollution in the Future by Learning from the Past? A Policy Analysis

This paper applies a policy analysis approach to the question of how to effectively regulate micropollution in a sustainable manner. Micropollution is a complex policy problem characterized by a huge number and diversity of chemical substances, as well as various entry paths into the aquatic environment. It challenges traditional water quality management by calling for new technologies in wastewater treatment and behavioral changes in industry, agriculture and civil society. In light of such challenges, the question arises as to how to regulate such a complex phenomenon to ensure water quality is maintained in the future? What can we learn from past experiences in water quality regulation? To answer these questions, policy analysis strongly focuses on the design and choice of policy instruments and the mix of such measures. In this paper, we review instruments commonly used in past water quality regulation. We evaluate their ability to respond to the characteristics of a more recent water quality problem, i.e., micropollution, in a sustainable way. This way, we develop a new framework that integrates both the problem dimension (i.e., causes and effects of a problem) as well as the sustainability dimension (e.g., long-term, cross-sectoral and multi-level) to assess which policy instruments are best suited to regulate micropollution. We thus conclude that sustainability criteria help to identify an appropriate instrument mix of end-of-pipe and source-directed measures to reduce aquatic micropollution.

Resistance prediction in AML: analysis of 4601 patients from MRC/NCRI, HOVON/SAKK, SWOG and MD Anderson Cancer Center

Therapeutic resistance remains the principal problem in acute myeloid leukemia (AML). We used area under receiver-operating characteristic curves (AUCs) to quantify our ability to predict therapeutic resistance in individual patients, where AUC=1.0 denotes perfect prediction and AUC=0.5 denotes a coin flip, using data from 4601 patients with newly diagnosed AML given induction therapy with 3+7 or more intense standard regimens in UK Medical Research Council/National Cancer Research Institute, Dutch–Belgian Cooperative Trial Group for Hematology/Oncology/Swiss Group for Clinical Cancer Research, US cooperative group SWOG and MD Anderson Cancer Center studies. Age, performance status, white blood cell count, secondary disease, cytogenetic risk and FLT3-ITD/NPM1 mutation status were each independently associated with failure to achieve complete remission despite no early death (‘primary refractoriness’). However, the AUC of a bootstrap-corrected multivariable model predicting this outcome was only 0.78, indicating only fair predictive ability. Removal of FLT3-ITD and NPM1 information only slightly decreased the AUC (0.76). Prediction of resistance, defined as primary refractoriness or short relapse-free survival, was even more difficult. Our limited ability to forecast resistance based on routinely available pretreatment covariates provides a rationale for continued randomization between standard and new therapies and supports further examination of genetic and posttreatment data to optimize resistance prediction in AML.