Considering context in psychological leadership research

Despite Lewin's identification of the importance of context in behavioral research over 70 years ago, leadership psychology tended to ignore the context. Only in the past 10 years has the context been more routinely included in psychological leadership research. We provide examples of leadership research that has explored the context, introduce the special issue articles, and provide suggestions for future research on the context of leadership.

Symptoms, comorbidity, and clinical course of depression in immigrants: Putting psychopathology in context.

BACKGROUND: Migration is considered a depression risk factor when associated with psychosocial adversity, but its impact on depression's clinical characteristics has not been specifically studied. We compared 85 migrants to 34 controls, examining depression's severity, symptomatology, comorbidity profile and clinical course. METHOD: A MINI interview modified to assess course characteristics was used to assign DSM-IV axis I diagnoses; medical files were used for Somatoform Disorders. Severity was assessed with the Montgomery-Asberg scale. Wherever possible, we adjusted comparisons for age and gender using logistic and linear regressions. RESULTS: Depression in migrants was characterized by higher comorbidity (mostly somatoform and anxiety disorders), higher severity, and a non-recurrent, chronic course. LIMITATIONS: Our sample comes from a single center, and should be replicated in other health care facilities and other countries. Somatoform disorder diagnoses were solely based on file-content. CONCLUSION: Depression in migrants presented as a complex, chronic clinical picture. Most of our migrant patients experienced significant psychosocial adversity before and after migration: beyond cultural issues, our results suggest that psychosocial adversity impacts on the clinical expression of depression. Our study also suggests that migration associated with psychosocial adversity might play a specific etiological role, resulting in a distinct clinical picture, questioning the DSM-IV unitarian model of depression. The chronic course might indicate a resistance to standard therapeutic regimen and hints at the necessity of developing specific treatment strategies, adapted to the individual patients and their specific context.

Tissue biomarker development in a multicentre trial context: a feasibility study on the PETACC3 stage II and III colon cancer adjuvant treatment trial.

PURPOSE: We evaluated the feasibility of biomarker development in the context of multicenter clinical trials. EXPERIMENTAL DESIGN: Formalin-fixed, paraffin-embedded (FFPE) tissue samples were collected from a prospective adjuvant colon cancer trial (PETACC3). DNA was isolated from tumor as well as normal tissue and used for analysis of microsatellite instability, KRAS and BRAF genotyping, UGT1A1 genotyping, and loss of heterozygosity of 18 q loci. Immunohistochemistry was used to test expression of TERT, SMAD4, p53, and TYMS. Messenger RNA was retrieved and tested for use in expression profiling experiments. RESULTS: Of the 3,278 patients entered in the study, FFPE blocks were obtained from 1,564 patients coming from 368 different centers in 31 countries. In over 95% of the samples, genomic DNA tests yielded a reliable result. Of the immmunohistochemical tests, p53 and SMAD4 staining did best with reliable results in over 85% of the cases. TERT was the most problematic test with 46% of failures, mostly due to insufficient tissue processing quality. Good quality mRNA was obtained, usable in expression profiling experiments. CONCLUSIONS: Prospective clinical trials can be used as framework for biomarker development using routinely processed FFPE tissues. Our results support the notion that as a rule, translational studies based on FFPE should be included in prospective clinical trials.

Source wavelet estimation for waveform inversion of crosshole georadar data

AbstractFor a wide range of environmental, hydrological, and engineering applications there is a fast growing need for high-resolution imaging. In this context, waveform tomographic imaging of crosshole georadar data is a powerful method able to provide images of pertinent electrical properties in near-surface environments with unprecedented spatial resolution. In contrast, conventional ray-based tomographic methods, which consider only a very limited part of the recorded signal (first-arrival traveltimes and maximum first-cycle amplitudes), suffer from inherent limitations in resolution and may prove to be inadequate in complex environments. For a typical crosshole georadar survey the potential improvement in resolution when using waveform-based approaches instead of ray-based approaches is in the range of one order-of- magnitude. Moreover, the spatial resolution of waveform-based inversions is comparable to that of common logging methods. While in exploration seismology waveform tomographic imaging has become well established over the past two decades, it is comparably still underdeveloped in the georadar domain despite corresponding needs. Recently, different groups have presented finite-difference time-domain waveform inversion schemes for crosshole georadar data, which are adaptations and extensions of Tarantola's seminal nonlinear generalized least-squares approach developed for the seismic case. First applications of these new crosshole georadar waveform inversion schemes on synthetic and field data have shown promising results. However, there is little known about the limits and performance of such schemes in complex environments. To this end, the general motivation of my thesis is the evaluation of the robustness and limitations of waveform inversion algorithms for crosshole georadar data in order to apply such schemes to a wide range of real world problems.One crucial issue to making applicable and effective any waveform scheme to real-world crosshole georadar problems is the accurate estimation of the source wavelet, which is unknown in reality. Waveform inversion schemes for crosshole georadar data require forward simulations of the wavefield in order to iteratively solve the inverse problem. Therefore, accurate knowledge of the source wavelet is critically important for successful application of such schemes. Relatively small differences in the estimated source wavelet shape can lead to large differences in the resulting tomograms. In the first part of my thesis, I explore the viability and robustness of a relatively simple iterative deconvolution technique that incorporates the estimation of the source wavelet into the waveform inversion procedure rather than adding additional model parameters into the inversion problem. Extensive tests indicate that this source wavelet estimation technique is simple yet effective, and is able to provide remarkably accurate and robust estimates of the source wavelet in the presence of strong heterogeneity in both the dielectric permittivity and electrical conductivity as well as significant ambient noise in the recorded data. Furthermore, our tests also indicate that the approach is insensitive to the phase characteristics of the starting wavelet, which is not the case when directly incorporating the wavelet estimation into the inverse problem.Another critical issue with crosshole georadar waveform inversion schemes which clearly needs to be investigated is the consequence of the common assumption of frequency- independent electromagnetic constitutive parameters. This is crucial since in reality, these parameters are known to be frequency-dependent and complex and thus recorded georadar data may show significant dispersive behaviour. In particular, in the presence of water, there is a wide body of evidence showing that the dielectric permittivity can be significantly frequency dependent over the GPR frequency range, due to a variety of relaxation processes. The second part of my thesis is therefore dedicated to the evaluation of the reconstruction limits of a non-dispersive crosshole georadar waveform inversion scheme in the presence of varying degrees of dielectric dispersion. I show that the inversion algorithm, combined with the iterative deconvolution-based source wavelet estimation procedure that is partially able to account for the frequency-dependent effects through an "effective" wavelet, performs remarkably well in weakly to moderately dispersive environments and has the ability to provide adequate tomographic reconstructions.

Noise in Brain Activity Engenders Perception and Influences Discrimination Sensitivity.

Behavioral and brain responses to identical stimuli can vary with experimental and task parameters, including the context of stimulus presentation or attention. More surprisingly, computational models suggest that noise-related random fluctuations in brain responses to stimuli would alone be sufficient to engender perceptual differences between physically identical stimuli. In two experiments combining psychophysics and EEG in healthy humans, we investigated brain mechanisms whereby identical stimuli are (erroneously) perceived as different (higher vs lower in pitch or longer vs shorter in duration) in the absence of any change in the experimental context. Even though, as expected, participants' percepts to identical stimuli varied randomly, a classification algorithm based on a mixture of Gaussians model (GMM) showed that there was sufficient information in single-trial EEG to reliably predict participants' judgments of the stimulus dimension. By contrasting electrical neuroimaging analyses of auditory evoked potentials (AEPs) to the identical stimuli as a function of participants' percepts, we identified the precise timing and neural correlates (strength vs topographic modulations) as well as intracranial sources of these erroneous perceptions. In both experiments, AEP differences first occurred ∼100 ms after stimulus onset and were the result of topographic modulations following from changes in the configuration of active brain networks. Source estimations localized the origin of variations in perceived pitch of identical stimuli within right temporal and left frontal areas and of variations in perceived duration within right temporoparietal areas. We discuss our results in terms of providing neurophysiologic evidence for the contribution of random fluctuations in brain activity to conscious perception.

Mineralogical, petrographic and geochemical characterisation of white and coloured Iberian marbles in the context of the provenancing of some artefacts from Thamusida (Kenitra, Morocco)

A multi-analytical study has been carried out on a collection of white and coloured Iberian marbles. A total of 135 marble specimens were collected in Spain and Portugal from the Betic chain (Alhaurin de la Torre, Mijas, Macael), Ossa Morena (Alconera, Almaden de la Plata and Viana do Alentejo), and the Estremoz Anticline (Bencatel, Borba and Estremoz) areas. X-ray diffractometry and carbon and oxygen stable isotope analysis were carried out on these samples; 38 samples were also investigated by optical and scanning electron microscopy. The results provide a set of diagnostic parameters that allow discriminating the sampled marble quarries. The carbonate minerals composition is distinctive for the Mijas and Alhaurin de la Torre marbles; the isotopic analysis allows discriminating also between these two dolomitic marble quarries. The Ossa Morena and Estremoz Anticline marbles share a similar stable isotope composition; the accessory mineral content, the maximum grain size (MGS) and the fabric are particularly useful in the distinction between them. In the framework of archaeometric provenance studies on Thamusida (Kenitra, Morocco) Roman marble artefacts, a specific comparison between this new Iberian database and archaeological findings has been carried out. The hypothesis of commercial exchanges between the Iberian regions and Roman Morocco is supported by the results of the provenance study, which suggested the Almaden de la Plata and Mijas quarries as possible sources of raw materials for the production of archaeological artefacts.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.

Clinicopathologic and molecular analysis of a choroidal pigmented schwannoma in the context of a PTEN hamartoma tumor syndrome.

PURPOSE: To report the first case of choroidal schwannoma in a patient affected by PTEN hamartoma tumor syndrome (PHTS) and investigate the molecular involvement of the phosphatase and tensin homolog (PTEN) and neurofibromin 2 (NF2) genes in this rare intraocular tumor. DESIGN: Observational case report. PARTICIPANT: A 10-year-old girl diagnosed with PHTS. METHODS: The enucleated specimen underwent histologic, immunohistochemical, and transmission electronic microscopy. The expression of PTEN and NF2 and their protein products were evaluated by reverse transcription-polymerase chain reaction and immunohistochemistry. Somatic mutations of PTEN and NF2, as well as allelic loss, were investigated by direct sequencing of DNA extracted from the tumor. PTEN epigenetic silencing was investigated by pyrosequencing. MAIN OUTCOME MEASURES: Histopathologic and molecular characterization of a choroidal pigmented schwannoma. RESULTS: Histopathologic, immunohistochemical, and electron microscopic analysis demonstrated features consistent with a pigmented cellular schwannoma of the choroid. We found no loss of heterozygosity at the genomic level for the PTEN germline mutation and no promoter hypermethylation or other somatic intragenic mutations. However, we observed an approximate 40% reduction of PTEN expression at both the mRNA and the protein level, indicating that the tumor was nonetheless functionally deficient for PTEN. Although DNA sequencing of NF2 failed to identify any pathologic variants, its expression was abolished within the tumor. CONCLUSIONS: We report the first description of a pigmented choroidal schwannoma in the context of a PHTS. This rare tumor showed a unique combination of reduction of PTEN and absence of NF2 expression.

Post-detection analysis for grating-based ultra-small angle X-ray scattering.

Until recently, the hard X-ray, phase-sensitive imaging technique called grating interferometry was thought to provide information only in real space. However, by utilizing an alternative approach to data analysis we demonstrated that the angular resolved ultra-small angle X-ray scattering distribution can be retrieved from experimental data. Thus, reciprocal space information is accessible by grating interferometry in addition to real space. Naturally, the quality of the retrieved data strongly depends on the performance of the employed analysis procedure, which involves deconvolution of periodic and noisy data in this context. The aim of this article is to compare several deconvolution algorithms to retrieve the ultra-small angle X-ray scattering distribution in grating interferometry. We quantitatively compare the performance of three deconvolution procedures (i.e., Wiener, iterative Wiener and Lucy-Richardson) in case of realistically modeled, noisy and periodic input data. The simulations showed that the algorithm of Lucy-Richardson is the more reliable and more efficient as a function of the characteristics of the signals in the given context. The availability of a reliable data analysis procedure is essential for future developments in grating interferometry.

Validation of a clinical algorithm to identify low-risk patients with pulmonary embolism.

Summary Background: We previously derived a clinical prognostic algorithm to identify patients with pulmonary embolism (PE) who are at low-risk of short-term mortality who could be safely discharged early or treated entirely in an outpatient setting. Objectives: To externally validate the clinical prognostic algorithm in an independent patient sample. Methods: We validated the algorithm in 983 consecutive patients prospectively diagnosed with PE at an emergency department of a university hospital. Patients with none of the algorithm's 10 prognostic variables (age >/= 70 years, cancer, heart failure, chronic lung disease, chronic renal disease, cerebrovascular disease, pulse >/= 110/min., systolic blood pressure < 100 mm Hg, oxygen saturation < 90%, and altered mental status) at baseline were defined as low-risk. We compared 30-day overall mortality among low-risk patients based on the algorithm between the validation and the original derivation sample. We also assessed the rate of PE-related and bleeding-related mortality among low-risk patients. Results: Overall, the algorithm classified 16.3% of patients with PE as low-risk. Mortality at 30 days was 1.9% among low-risk patients and did not differ between the validation and the original derivation sample. Among low-risk patients, only 0.6% died from definite or possible PE, and 0% died from bleeding. Conclusions: This study validates an easy-to-use, clinical prognostic algorithm for PE that accurately identifies patients with PE who are at low-risk of short-term mortality. Low-risk patients based on our algorithm are potential candidates for less costly outpatient treatment.