Response selection deficits in melancholic but not nonmelancholic unipolar major depression

One consistent functional imaging finding from patients with major depression has been abnormality of the anterior cingulate cortex (ACC). Hypoperfusion has been most commonly reported, but some studies suggest relative hyperperfusion is associated with response to somatic treatments. Despite these indications of the possible importance of the ACC in depression there have been relatively few cognitive studies ACC function in patients with major depression. The present study employed a series of reaction time (RT) tasks involving selection with melancholic and nonmelancholic depressed patients, as well as age-matched controls. Fifteen patients with unipolar major depression (7 melancholic, 8 nonmelancholic) and 8 healthy age-matched controls performed a series of response selection tasks (choice RT, spatial Stroop, spatial stimulus-response compatibility (SRC), and a combined Stroop + SRC condition). Reaction time and error data were collected. Melancholic patients were significantly slower than controls on all tasks but were slower than nonmelancholic patients only on the Stroop and Stroop + SRC conditions. Nonmelancholic patients did not differ from the control group on any task. The Stroop task seems crucial in differentiating the two depressive groups, they did not differ on the choice RT or SRC tasks. This may reflect differential task demands, the SRC involved symbolic manipulation that might engage the dorsal ACC and dorsolateral prefrontal cortex (DLPFC) to a greater extent than the, primarily inhibitory, Stroop task which may engage the ventral ACC and orbitofrontal cortex (OFC). This might suggest the melancholic group showed a greater ventral ACC-OFC deficit than the nonmelancholic group, while both groups showed similar dorsal ACC-DLPFC deficit.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

Operational regimes for a simplified one-step artificial chaperone refolding method

The artificial chaperone method for protein refolding developed by Rozema et al. (Rozema, D.; Gellman, S. H. J. Am. Chem. Soc. 1995, 117 (8), 2373-2374) involves the sequential dilution of denatured protein into a buffer containing detergent (cetyltrimethylammonium bromide, CTAB) and then into a refolding buffer containing cyclodextrin WD). In this paper a simplified one-step artificial chaperone method is reported, whereby CTAB is added directly to the denatured solution, which is then diluted directly into a refolding buffer containing P-cyclodextrin (P-CD). This new method can be applied at high protein concentrations, resulting in smaller processing volumes and a more concentrated protein solution following refolding. The increase in achievable protein concentration results from the enhanced solubility of CTAB at elevated temperatures in concentrated denaturant. The refolding yields obtained for the new method were significantly higher than for control experiments lacking additives and were comparable to the yields obtained with the classical two-step approach. A study of the effect of beta-CD and CTAB concentrations on refolding yield suggested two operational regimes: slow stripping ( beta-CDXTABsimilar to1), most suited for higher protein concentrations, and fast stripping (beta-CD/CTABsimilar to2.7), best suited for lower protein concentrations. An increased chaotrope concentration resulted in higher refolding yields and an enlarged operational regime.

The selection of intended actions and the observation of others' actions: A time-resolved fMRI study

Whenever we plan, imagine, or observe an action, the motor systems that would be involved in preparing and executing that action are similarly engaged. The way in which such common motor activation is formed, however, is likely to differ depending on whether it arises from our own intentional selection of action or from the observation of another's action. In this study, we use time-resolved event-related functional MRI to tease apart neural processes specifically related to the processing of observed actions, the selection of our own intended actions, the preparation for movement, and motor response execution. Participants observed a finger gesture movement or a cue indicating they should select their own finger gesture to perform, followed by a 5-s delay period; participants then performed the observed or self-selected action. During the preparation and readiness for action, prior to initiation, we found activation in a common network of higher motor areas, including dorsal and ventral premotor areas and the pre-supplementary motor area (pre-SMA); the more caudal SMA showed greater activation during movement execution. Importantly, the route to this common motor activation differed depending on whether participants freely selected the actions to perform or whether they observed the actions performed by another person. Observation of action specifically involved activation of inferior and superior parietal regions, reflecting involvement of the dorsal visual pathway in visuomotor processing required for planning the action. In contrast, the selection of action specifically involved the dorsal lateral prefrontal and anterior cingulate cortex, reflecting the role of these prefrontal areas in attentional selection and guiding the selection of responses. (c) 2005 Elsevier Inc. All rights reserved.

Social rules and attributions in the personnel selection interview

The study investigated the social rules applicable to selection interviews, and the attributions ions made by interviewers in response to rule-breaking behaviours by candidates. Sixty personnel specialists (31 males and 29 females) participated in the main study which examined their perceptions of social rules and attributions about rule breaking in their work experience. They listened to audiotapes of actual selection interviews, and made judgments about hireability communication competence, and specific social rules. Results indicated that interview rules could be categorized into two groups: specific interview presentation skills and general interpersonal competence. While situational attributions were more salient in explaining the breaking of general interpersonal competence rules, internal attributions (ability, effort) were more salient explanations for the breaking of more specific interview rules (with the exception of the preparation rule where lack of effort was the most likely explanation for rule breaking). Candidates previously judged as competent communicators were rated more favourably on both global and specific measures of rule-following competence, as well as on hireability. The theoretical and practical implications of combining social rules and attribution theory in the study of selection interviews are discussed.

Effect of body composition at selection on reproductive development in large white gilts

Fifty-four Large White gilts were used to determine the effect of body composition at selection (145 d of age) on the onset of puberty and subsequent reproductive development until 202 d of age. Gilts were assigned to one of three groups based on their backfat depth at selection: 10 to 12 mm (L), 13 to 15 mm (M), and 16 to 18 mm (F). All of the F gilts, 92% of the M gilts, and 67% of the L gilts reached puberty by slaughter at 202 d of age. Data from a subgroup (first 67% to reach puberty in each group; L = Lp, M = Mp, and F = Fp) was also used. The M (Mp) and F (Fp) gilts reached puberty at 172 d (166 d) and 170 d (166 d) of age, respectively, but the L (Lp) gilts at 184.5 d were 12 d (18 d) older than M(P < .05), Mp(P < .001), and F(P < .01), Fp (P < .001) gilts. The Lp (97.68 kg) and Mp (98.33 kg) gilts were lighter (P < .01) than Fp (108.72 kg) gilts at puberty. There were no differences (P < .05) among the L, M, and F gilts in terms of backfat depth or weight at puberty. The L (Lp) gilts had a mean of 1.16 (1.75) estrous cycles, which was lower (P < .01) than for M (Mp) and (P < .01) F (Fp) gilts, with 1.96 (2.29) and 2.25 (2.33) cycles, respectively. L (Lp) gilts had fewer (P < .05) follicles, 13.14 (12.63), than either M (Mp), 19.08 (18.71), or F (Fp), 18.25 (17.42) gilts. The number of corpora lutea was not influenced (P > .05) by grouping at selection, but Fp gilts had fewer (P < .05) corpora lutea than Mp or Fp gilts. Live weight at slaughter was not influenced (P > .10) by grouping at selection or subgrouping at puberty. The L gilts with a mean of 18.05 mm of backfat at slaughter were leaner (P < .05) than the F (21.66 mm) but not (P > .10) the M gilts (19.41 mm). Subgrouping had no effect. Fat deposition and protein deposition were higher (P < .05) in those animals that attained puberty. We conclude that the rate of fat and protein deposition seems to be one of the determinants of puberty attainment.

The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.