Meta-analytic review of neurocognition in bipolar II disorder

Objective: The clinical distinction between bipolar II disorder (BD II) and bipolar I disorder (BD I) is not clear-cut. Cognitive functioning offers the potential to explore objective markers to help delineate this boundary. To examine this issue, we conducted a quantitative review of the cognitive profile of clinically stable patients with BD II in comparison with both patients with BD I and healthy controls.
Method: Meta-analytical methods were used to compare cognitive functioning of BD II disorder with both BD I disorder and healthy controls.
Results: Individuals with BD II were less impaired than those with BD I on verbal memory. There were also small but significant difference in
visual memory and semantic fluency. There were no significant differences in global cognition or in other cognitive domains. Patients with BD II performed poorer than controls in all cognitive domains.
Conclusion: Our findings suggest that with the exception of memory and semantic fluency, cognitive impairment in BD II is as severe as in BD I. Further studies are needed to investigate whether more severe deficits in BD I are related to neurotoxic effects of severe manic episodes on medial temporal structures or neurobiological differences from the onset of the illness.

Cause and effect in studies on unemployment, mental health and suicide: a meta-analytic and conceptual review

Background There are ongoing questions about whether unemployment has causal effects on suicide as this relationship may be confounded by past experiences of mental illness. The present review quantified the effects of adjustment for mental health on the relationship between unemployment and suicide. Findings were used to develop and interpret likely causal models of unemployment, mental health and suicide. Method A random-effects meta-analysis was conducted on five population-based cohort studies where temporal relationships could be clearly ascertained. Results Results of the meta-analysis showed that unemployment was associated with a significantly higher relative risk (RR) of suicide before adjustment for prior mental health [RR 1.58, 95% confidence interval (CI) 1.33–1.83]. After controlling for mental health, the RR of suicide following unemployment was reduced by approximately 37% (RR 1.15, 95% CI 1.00–1.30). Greater exposure to unemployment was associated with higher RR of suicide, and the pooled RR was higher for males than for females. Conclusions Plausible interpretations of likely pathways between unemployment and suicide are complex and difficult to validate given the poor delineation of associations over time and analytic rationale for confounder adjustment evident in the revised literature. Future research would be strengthened by explicit articulation of temporal relationships and causal assumptions. This would be complemented by longitudinal study designs suitable to assess potential confounders, mediators and effect modifiers influencing the relationship between unemployment and suicide.

A novel aggregate gene selection method for microarray data classification

This paper introduces a novel method for gene selection based on a modification of analytic hierarchy process (AHP). The modified AHP (MAHP) is able to deal with quantitative factors that are statistics of five individual gene ranking methods: two-sample t-test, entropy test, receiver operating characteristic curve, Wilcoxon test, and signal to noise ratio. The most prominent discriminant genes serve as inputs to a range of classifiers including linear discriminant analysis, k-nearest neighbors, probabilistic neural network, support vector machine, and multilayer perceptron. Gene subsets selected by MAHP are compared with those of four competing approaches: information gain, symmetrical uncertainty, Bhattacharyya distance and ReliefF. Four benchmark microarray datasets: diffuse large B-cell lymphoma, leukemia cancer, prostate and colon are utilized for experiments. As the number of samples in microarray data datasets are limited, the leave one out cross validation strategy is applied rather than the traditional cross validation. Experimental results demonstrate the significant dominance of the proposed MAHP against the competing methods in terms of both accuracy and stability. With a benefit of inexpensive computational cost, MAHP is useful for cancer diagnosis using DNA gene expression profiles in the real clinical practice.

A factor analytical method to interactive effects dynamic panel models with or without unit root

In a recent study, Bai (Fixed-Effects Dynamic Panel Models, A Factor Analytical Method. Econometrica 81, 285-314, 2013a) proposes a new factor analytic (FA) method to the estimation of dynamic panel data models, which has the unique and very useful property that it is completely bias-free. However, while certainly appealing, it is restricted to fixed effects models without a unit root. In many situations of practical relevance this is a rather restrictive consideration. The purpose of the current study is therefore to extend the FA approach to cover models with multiple interactive effects and a possible unit root.

Letters, green cards, telephone calls and postcards: systematic and meta-analytic review of brief contact interventions for reducing self-harm, suicide attempts and suicide

BACKGROUND: There is growing interest in brief contact interventions for self-harm and suicide attempt. AIMS: To synthesise the evidence regarding the effectiveness of brief contact interventions for reducing self-harm, suicide attempt and suicide. METHOD: A systematic review and random-effects meta-analyses were conducted of randomised controlled trials using brief contact interventions (telephone contacts; emergency or crisis cards; and postcard or letter contacts). Several sensitivity analyses were conducted to examine study quality and subgroup effects. RESULTS: We found 14 eligible studies overall, of which 12 were amenable to meta-analyses. For any subsequent episode of self-harm or suicide attempt, there was a non-significant reduction in the overall pooled odds ratio (OR) of 0.87 (95% CI 0.74-1.04, P = 0119) for intervention compared with control. The number of repetitions per person was significantly reduced in intervention v. control (incidence rate ratio IRR = 066, 95% CI 0.54-0.80, P<0001). There was no significant reduction in the odds of suicide in intervention compared with control (OR = 0.58, 95% CI 0.24-1.38). CONCLUSIONS: A non-significant positive effect on repeated self-harm, suicide attempt and suicide and a significant effect on the number of episodes of repeated self-harm or suicide attempts per person (based on only three studies) means that brief contact interventions cannot yet be recommended for widespread clinical implementation. We recommend further assessment of possible benefits in well-designed trials in clinical populations.

Consensus building in a local context for the AHP-GDM with the individual numerical scale and prioritization method

The methodology for selecting the individual numerical scale and prioritization method has recently been presented and justified in the analytic hierarchy process (AHP). In this study, we further propose a novel AHP-group decision making (GDM) model in a local context (a unique criterion), based on the individual selection of the numerical scale and prioritization method. The resolution framework of the AHP-GDM with the individual numerical scale and prioritization method is first proposed. Then, based on linguistic Euclidean distance (LED) and linguistic minimum violations (LMV), the novel consensus measure is defined so that the consensus degree among decision makers who use different numerical scales and prioritization methods can be analyzed. Next, a consensus reaching model is proposed to help decision makers improve the consensus degree. In this consensus reaching model, the LED-based and LMV-based consensus rules are proposed and used. Finally, a new individual consistency index and its properties are proposed for the use of the individual numerical scale and prioritization method in the AHP-GDM. Simulation experiments and numerical examples are presented to demonstrate the validity of the proposed model.

Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

ANALYTIC STUDY ON HIGH-VOLTAGE CROWBAR SYSTEM

Crowbar switches are largely used in plasma devices, such as field-reversed configuration (FRC) machines and tokamaks, to avoid energy return from the discharge coil to the capacitor bank. A method of identification of all resistances, inductances and currents involved in capacitor bank discharges using a crowbar is proposed based on the derivation of the general analytical form of the coil current. This analysis can also be used for optimization of the discharge, reducing the ripple amplitude inherent in the crowbar-switched current. Fitting results of the TC-1 UNICAMP FRC device are also presented in this work.

Analytic hierarchy prioritisation of new product development activities for electronics manufacturing

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Analytic element modelling for strip aquifers

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Using the Analytic Network Process to evaluate the relation between Reverse Logistics and corporate performance in Brazilian companies

Reverse Logistics activities are practiced by most Brazilian companies. However, a relevant problem is to identify how different Reverse Logistics programs can affect corporate performance indicators. Analytic Network Process is one of the analytical tools, which can be used to handle a multi-criteria decision-making problem and it is the only one that can capture the interdependencies between the criteria under consideration. This method was adopted here to study the influence of Reverse Logistics practices in corporate performance. Preliminary results indicated that the method can be used, reaching a result compatible to the reality of the Brazilian companies.

Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

DETERMINATION OF CHLORFENVINPHOS, FIPRONIL, AND CYPERMETHRIN RESIDUES IN MEAT AND BOVINE FAT USING QUECHERS METHOD AND GAS CHROMATOGRAPHY-MASS SPECTROMETRY

Analytic methods were applied and validated to measure residues of chlorfenvinphos, fipronil, and cypermethrin in meat and bovine fat, using the QuEChERS method and gas chromatography-mass spectrometry. For the meat, 2 g of sample, 4mL of acetonitrile, 1.6 g of MgSO4, and 0.4 g of NaCl were used in the liquid-liquid partition, while 80 mg of C18, 80 mg of primary and secondary amine and 150 mg of MgSO4 were employed in the dispersive solid-phase extraction. For the fat, 1 g of sample, 5 mL of hexane, 10 mL of water, 10 mL of acetonitrile, 4 g of MgSO4, and 0.5 g of NaCl were used in the liquid-liquid partition and 50 mg of primary and secondary amine and 150 mg of MgSO4 were used in the dispersive solid-phase extraction. The recovery percentages obtained for the pesticides in meat at different concentrations ranged from 81 to 129% with relative standard deviation below 27%. The corresponding results from the fat ranged from 70 to 123% with relative standard deviation below 25%. The methods showed sensitivity, precision, and accuracy according to EPA standards and quantification limits below the maximum residue limit established by European Union, except for chlorfenvinphos in the fat.

Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle

A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits.