171 research outputs found
Brain systems underlying the affective and social monitoring of actions: an integrative review
Digital Leg Volume Quantification: Precision Assessment of a Novel Workflow Based on Single Capture Three-dimensional Whole-Body Surface Imaging
Whole-body three-dimensional surface imaging (3DSI) offers the ability to monitor morphologic changes in multiple areas without the need to individually scan every anatomical region of interest. One area of application is the digital quantification of leg volume. Certain types of morphology do not permit complete circumferential scan of the leg surface. A workflow capable of precisely estimating the missing data is therefore required. We thus aimed to describe and apply a novel workflow to collect bilateral leg volume measurements from whole-body 3D surface scans regardless of leg morphology and to assess workflow precision. For each study participant, whole-body 3DSI was conducted twice successively in a single session with subject repositioning between scans. Paired samples of bilateral leg volume were calculated from the 3D surface data, with workflow variations for complete and limited leg surface visibility. Workflow precision was assessed by calculating the relative percent differences between repeated leg volumes. A total of 82 subjects were included in this study. The mean relative differences between paired left and right leg volumes were 0.73 ± 0.62% and 0.82 ± 0.65%. The workflow variations for completely and partially visible leg surfaces yielded similarly low values. The workflow examined in this study provides a precise method to digitally monitor leg volume regardless of leg morphology. It could aid in objectively comparing medical treatment options of the leg in a clinical setting. Whole-body scans acquired using the described 3DSI routine may allow simultaneous assessment of other changes in body morphology after further validation
Bio-precipitation of uranium by two bacterial isolates recovered from extreme environments as estimated by potentiometric titration, TEM and X-ray absorption spectroscopic analyses
This is the post-print version of the final paper published in Journal of Hazardous Materials. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2011 Elsevier B.V.This work describes the mechanisms of uranium biomineralization at acidic conditions by Bacillus sphaericus JG-7B and Sphingomonas sp. S15-S1 both recovered from extreme environments. The U–bacterial interaction experiments were performed at low pH values (2.0–4.5) where the uranium aqueous speciation is dominated by highly mobile uranyl ions. X-ray absorption spectroscopy (XAS) showed that the cells of the studied strains precipitated uranium at pH 3.0 and 4.5 as a uranium phosphate mineral phase belonging to the meta-autunite group. Transmission electron microscopic (TEM) analyses showed strain-specific localization of the uranium precipitates. In the case of B. sphaericus JG-7B, the U(VI) precipitate was bound to the cell wall. Whereas for Sphingomonas sp. S15-S1, the U(VI) precipitates were observed both on the cell surface and intracellularly. The observed U(VI) biomineralization was associated with the activity of indigenous acid phosphatase detected at these pH values in the absence of an organic phosphate substrate. The biomineralization of uranium was not observed at pH 2.0, and U(VI) formed complexes with organophosphate ligands from the cells. This study increases the number of bacterial strains that have been demonstrated to precipitate uranium phosphates at acidic conditions via the activity of acid phosphatase
Molecular Characterization and Expression of a Heat Shock Protein Gene (HSP90) from the Carmine Spider Mite, Tetranychus cinnabarinus (Boisduval)
In this study, the cDNA of Tetranychus cinnabarinus (Boisduval) (Acarina: Tetranychidae) HSP90 (designated TcHSP90) was cloned using a combination of the homology cloning and rapid amplification of cDNA ends (RACE) approaches. The full-length cDNA of TcHSP90 is 2595 bp, including a 5′-untranslated region (UTR) of 177 bp, 3′-UTR of 249 bp, and an open reading frame (ORF) of 2169 bp. The ORF encodes a polypeptide of 722 amino acids with a predicted molecular weight of 83.45 kDa and a theoretical isoelectric point of 4.81. There is an mRNA polyadenylation signal of ATTAAA at the positions 2558–2564. In addition, the expression pattern of TcHSP90 mRNA relative to that of β-actin gene in the three stains of T. cinnabarinus (AbR, abamectin-resistant strain; HR, heat-resistant strain; SS, the susceptible strain) were examined by using fluorescent real time quantitative PCR after the impact of abamectin, high and low temperature, respectively. The results showed that under the normal condition, the mRNA level of TcHSP90 was 1.64 and 1.29-fold higher in the AbR and HR than in SS, respectively. After 8 h treatment with abamectin, the TcHSP90 mRNA levels of SS, AbR, and HR were 1.25, 1.87, and 2.05-fold higher than those of their untreated controls, respectively. The TcHSP90 mRNA levels of SS, AbR, and HR were also significantly increased after being induced at 40° C for 1 h, and they were 3.76, 3.42, and 3.79-fold higher than those of their untreated controls, respectively. The mRNA level of TcHSP90 was also significantly increased after being induced at 4° C for 1 h. These results suggest that TcHSP90 might be involved in the abamectin and extreme temperature resistance or tolerance
A Very Large Number of GABAergic Neurons Are Activated in the Tuberal Hypothalamus during Paradoxical (REM) Sleep Hypersomnia
We recently discovered, using Fos immunostaining, that the tuberal and mammillary hypothalamus contain a massive population of neurons specifically activated during paradoxical sleep (PS) hypersomnia. We further showed that some of the activated neurons of the tuberal hypothalamus express the melanin concentrating hormone (MCH) neuropeptide and that icv injection of MCH induces a strong increase in PS quantity. However, the chemical nature of the majority of the neurons activated during PS had not been characterized. To determine whether these neurons are GABAergic, we combined in situ hybridization of GAD67 mRNA with immunohistochemical detection of Fos in control, PS deprived and PS hypersomniac rats. We found that 74% of the very large population of Fos-labeled neurons located in the tuberal hypothalamus after PS hypersomnia were GAD-positive. We further demonstrated combining MCH immunohistochemistry and GAD67 in situ hybridization that 85% of the MCH neurons were also GAD-positive. Finally, based on the number of Fos-ir/GAD+, Fos-ir/MCH+, and GAD+/MCH+ double-labeled neurons counted from three sets of double-staining, we uncovered that around 80% of the large number of the Fos-ir/GAD+ neurons located in the tuberal hypothalamus after PS hypersomnia do not contain MCH. Based on these and previous results, we propose that the non-MCH Fos/GABAergic neuronal population could be involved in PS induction and maintenance while the Fos/MCH/GABAergic neurons could be involved in the homeostatic regulation of PS. Further investigations will be needed to corroborate this original hypothesis
Group-regularized individual prediction: Theory and application to pain
Multivariate pattern analysis (MVPA) has become an important tool for identifying brain representations of psychological processes and clinical outcomes using fMRI and related methods. Such methods can be used to predict or ‘decode’ psychological states in individual subjects. Single-subject MVPA approaches, however, are limited by the amount and quality of individual-subject data. In spite of higher spatial resolution, predictive accuracy from single-subject data often does not exceed what can be accomplished using coarser, group-level maps, because single-subject patterns are trained on limited amounts of often-noisy data. Here, we present a method that combines population-level priors, in the form of biomarker patterns developed on prior samples, with single-subject MVPA maps to improve single-subject prediction. Theoretical results and simulations motivate a weighting based on the relative variances of biomarker-based prediction—based on population-level predictive maps from prior groups—and individual-subject, cross-validated prediction. Empirical results predicting pain using brain activity on a trial-by-trial basis (single-trial prediction) across 6 studies (N = 180 participants) confirm the theoretical predictions. Regularization based on a population-level biomarker—in this case, the Neurologic Pain Signature (NPS)—improved single-subject prediction accuracy compared with idiographic maps based on the individuals' data alone. The regularization scheme that we propose, which we term group-regularized individual prediction (GRIP), can be applied broadly to within-person MVPA-based prediction. We also show how GRIP can be used to evaluate data quality and provide benchmarks for the appropriateness of population-level maps like the NPS for a given individual or study.FSW – Publicaties zonder aanstelling Universiteit Leide
Mistakes that affect others: An fMRI study on processing of own errors in a social context
In social contexts, errors have a special significance and often bear consequences for others. Thinking about others and drawing social inferences in interpersonal games engages the mentalizing system. We used neuroimaging to investigate the differences in brain activations between errors that affect only agents themselves and errors that additionally influence the payoffs of interaction partners. Activation in posterior medial frontal cortex (pMFC) and bilateral insula was increased for all errors, whereas errors that implied consequences for others specifically activated medial prefrontal cortex (mPFC), an important part of the mentalizing system. The results demonstrate that performance monitoring in social contexts involves additional processes and brain structures compared with individual performance monitoring where errors only have consequences for the person committing them. Taking into account how one’s behavior may affect others is particularly crucial for adapting behavior in interpersonal interactions and joint action
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