Using transcranial direct-current stimulation (tDCS) to understand cognitive processing

Noninvasive brain stimulation methods are becoming increasingly common tools in the kit of the cognitive scientist. In particular, transcranial direct-current stimulation (tDCS) is showing great promise as a tool to causally manipulate the brain and understand how information is processed. The popularity of this method of brain stimulation is based on the fact that it is safe, inexpensive, its effects are long lasting, and you can increase the likelihood that neurons will fire near one electrode and decrease the likelihood that neurons will fire near another. However, this method of manipulating the brain to draw causal inferences is not without complication. Because tDCS methods continue to be refined and are not yet standardized, there are reports in the literature that show some striking inconsistencies. Primary among the complications of the technique is that the tDCS method uses two or more electrodes to pass current and all of these electrodes will have effects on the tissue underneath them. In this tutorial, we will share what we have learned about using tDCS to manipulate how the brain perceives, attends, remembers, and responds to information from our environment. Our goal is to provide a starting point for new users of tDCS and spur discussion of the standardization of methods to enhance replicability.The authors declare that they had no conflicts of interest with respect to their authorship or the publication of this article. This work was supported by grants from the National Institutes of Health (R01-EY019882, R01-EY025272, P30-EY08126, F31-MH102042, and T32-EY007135). (R01-EY019882 - National Institutes of Health; R01-EY025272 - National Institutes of Health; P30-EY08126 - National Institutes of Health; F31-MH102042 - National Institutes of Health; T32-EY007135 - National Institutes of Health)Accepted manuscrip

Human Cytomegalovirus glycoprotein UL16 causes intracellular sequestration of NKG2D ligands, protecting against NK cell cytotoxicity.

The activating receptor, NKG2D, is expressed on a variety of immune effector cells and recognizes divergent families of major histocompatibility complex (MHC) class I-related ligands, including the MIC and ULBP proteins. Infection, stress, or transformation can induce NKG2D ligand expression, resulting in effector cell activation and killing of the ligand-expressing target cell. The human cytomegalovirus (HCMV) membrane glycoprotein, UL16, binds to three of the five known ligands for human NKG2D. UL16 is retained in the endoplasmic reticulum and cis-Golgi apparatus of cells and causes MICB to be similarly retained and stabilized within cells. Coexpression of UL16 markedly reduces cell surface levels of MICB, ULBP1, and ULBP2, and decreases susceptibility to natural killer cell-mediated cytotoxicity. Domain swapping experiments demonstrate that the transmembrane and cytoplasmic domains of UL16 are important for intracellular retention of UL16, whereas the ectodomain of UL16 participates in down-regulation of NKG2D ligands. The intracellular sequestration of NKG2D ligands by UL16 represents a novel HCMV immune evasion mechanism to add to the well-documented viral strategies directed against antigen presentation by classical MHC molecules

Coilin interacts with Ku proteins and inhibits in vitro non-homologous DNA end joining

AbstractCoilin is a nuclear protein that plays a role in Cajal body formation. The function of nucleoplasmic coilin is unknown. Here we report that coilin interacts with Ku70 and Ku80, which are major players in the DNA repair process. Ku proteins compete with SMN and SmB′ proteins for coilin interaction sites. The binding domain on coilin for Ku proteins cannot be localized to one discrete region, and only full-length coilin is capable of inhibiting in vitro non-homologous DNA end joining (NHEJ). Since Ku proteins do not accumulate in CBs, these findings suggest that nucleoplasmic coilin participates in the regulation of DNA repair.Structured summaryMINT-8052983:coilin (uniprotkb:P38432) physically interacts (MI:0915) with SmB′ (uniprotkb:P14678) by pull down (MI:0096)MINT-8052941:coilin (uniprotkb:P38432) physically interacts (MI:0915) with Ku70 (uniprotkb:P12956) by competition binding (MI:0405)MINT-8052765:coilin (uniprotkb:P38432) physically interacts (MI:0915) with Ku80 (uniprotkb:P13010) by pull down (MI:0096)MINT-8052971:coilin (uniprotkb:P38432) physically interacts (MI:0915) with SMN (uniprotkb:Q16637) by pull down (MI:0096)MINT-8052957:coilin (uniprotkb:P38432) physically interacts (MI:0915) with Ku80 (uniprotkb:P13010) by competition binding (MI:0405)MINT-8052894, MINT-8052908:coilin (uniprotkb:P38432) binds (MI:0407) to Ku80 (uniprotkb:P13010) by pull down (MI:0096)MINT-8052804:coilin (uniprotkb:P38432) physically interacts (MI:0915) with Ku80 (uniprotkb:P13010) by anti bait coimmunoprecipitation (MI:0006)MINT-8052925:coilin (uniprotkb:P38432) binds (MI:0407) to Ku70 (uniprotkb:P12956) by pull down (MI:0096)MINT-8052786:Ku80 (uniprotkb:P13010) physically interacts (MI:0914) with coilin (uniprotkb:P38432) and Ku70 (uniprotkb:P12956) by anti bait coimmunoprecipitation (MI:0006)MINT-8052776:coilin (uniprotkb:P38432) physically interacts (MI:0915) with Ku70 (uniprotkb:P12956) by pull down (MI:0096

Attentional capture under high perceptual load.

Attentional capture by abrupt onsets can be modulated by several factors, including the complexity, or perceptual load, of a scene. We have recently demonstrated that observers are less likely to be captured by abruptly appearing, task-irrelevant stimuli when they perform a search that is high, as opposed to low, in perceptual load Scenes contain a tremendous amount of information, often more than an observer can process at one time. As a result, selective attention mechanisms have developed that allow us to focus only on the information most relevant for carrying out our goals. For example, when attempting to read a newspaper in a crowded coffeehouse, we focus on the words on the page and ignore the irrelevant sights and sounds around us. Such goal-directed attentional control allows us to focus on the task at hand without interruption from extraneous information. However, sometimes our attention is captured by salient information in the environment regardless of its relevance to our goals. This type of stimulus-driven attentional capture is ubiquitous and can cause us to shift away from our primary goals and attend to information outside of our current focus

The Relationship Between Driving Behavior and Entropy

OBJECTIVES High variability in the lateral control of a vehicle may result in an increased likelihood of accidents. Boer (2000) proposed a method of quantifying variability in steering wheel position, termed “entropy” (scaled between 0 and 1). In this approach, the steering wheel position at each time point is predicted based on the position at the three preceding time points, and the discrepancies between the predicted and observed values are utilized to define a baseline distribution of prediction errors within a subject. This distribution is then used as a reference for calculating a summary “entropy” metric in follow-up segments of driving, such as when a driver may be distracted when using a cell phone. This same concept has also been applied to the lateral position of a vehicle (Dawson et al., 2006). The objective of this study was to ascertain whether entropy was affected by behavioral factors such as steering techniques and speed. We hoped to gain insight regarding the usefulness of entropy measures, and the appropriate interpretation of statistical tests based on entropy. METHODS We designed a simple driving route in a simulator known as SIREN (Rizzo, 2004), with a straight road segment of 3.7 km, followed by an S-curved road segment of 3.8 km. Using an expert driver familiar with the simulator, we performed a factorial experiment with different steering techniques (normal driving, swerving, and steering using a rigid grip and sudden “jerks”) and driving speeds (35 mph, 55 mph, and 75 mph). Data on steering wheel position and lane position were collected at 30 frames per second, and then reduced to 5-frame blocks of 167 msec each. Based on these blocks, we estimated the baseline parameter to characterize the prediction errors for each drive during the straight road section, and then applied this parameter to the straight and curved road sections in order to calculate entropy. This approach was used for both steering and lane position entropy. The data were analyzed using multiple linear regresssion to assess the affects of steering technique and speed, adjusting for road curvature. We also calculated Pearson correlation coefficients to measure the association between steering and lane position entropy. RESULTS Data were obtained on a total of 40 drive segments. Steering entropy ranged from 0.34 to 0.90, with a mean (SD) of 0.56 (0.16). Lane position entropy ranged from 0.34 to 0.93, with a mean (SD) of 0.61 (0.15). Compared to normal driving, steering behavior involving jerking motions tended to lower the steering entropy by 0.14 (p=0.012), and tended to lower the lane position entropy by 0.25 (p<0.001). Swerving in wide lateral motions had no effect on steering entropy, and only a minor effect on lane position entropy, decreasing it by 0.07. Compared to driving at 35 mph, driving at either 55 mph or 75 mph increased the steering entropy by an average of 0.08, but had no effect on lane position entropy. Although not our primary focus, we found that driving in curved sections tended to have higher entropy measures (increase of 0.21 for steering and 0.20 for lane position; p<0.001 in both cases). Despite a few outliers, the correlation between steering and lane position entropy was found to be high (r=0.84; see Figure 1). CONCLUSIONS Although entropy is often considered as an increasing function of workload, and would presumably increase in non-optimal conditions, some unsafe driving behaviors are actually negatively associated with entropy. Safe driving often involves making frequent minor steering adjustments, especially in curved sections of the road, which might lead to an increase in the entropy measure. If a driver rigidly holds onto the steering wheel and then makes large corrections when approaching or crossing a lane boundary, the fixed steering wheel position over several seconds may actually cause an apparent decrease in entropy. In summary, entropy may be a useful tool in quantifying vehicular control, but caution should be exercised when interpreting the results, as the associations involving entropy are not always in the anticipated direction

RANK/RANKL/OPG pathway: genetic associations with stress fracture period prevalence in elite athletes

Context: The RANK/RANKL/OPG signalling pathway is important in the regulation of bone turnover, with single nucleotide polymorphisms (SNPs) in genes within this pathway associated with bone phenotypic adaptations. Objective: To determine whether four SNPs associated with genes in the RANK/RANKL/OPG signalling pathway were associated with stress fracture injury in elite athletes. Design, Participants, and Methods: Radiologically confirmed stress fracture history was reported in 518 elite athletes, forming the Stress Fracture Elite Athlete (SFEA) cohort. Data were analysed for the whole group, and were sub-stratified into male and cases of multiple stress fracture group. Genotypes were determined using proprietary fluorescence-based competitive allele-specific PCR assays. Results: SNPs rs3018362 (RANK) and rs1021188 (RANKL) were associated with stress fracture injury (p<0.05). 8.1% of stress fracture group and 2.8% of the non-stress fracture group were homozygote for the rare allele of rs1021188. Allele frequency, heterozygotes and homozygotes for the rare allele of rs3018362 were associated with stress fracture period prevalence (p<0.05). Analysis of the male only group showed 8.2% of rs1021188 rare allele homozygotes to have suffered a stress fracture while 2.5% of the non-stress fracture group were homozygous. In cases of multiple stress fractures, homozygotes for the rare allele of rs1021188, and individuals possessing at least one copy of the rare allele of rs4355801 (OPG) were shown to be associated with stress fracture injury (p<0.05). Conclusions: The data support an association between SNPs in the RANK/RANKL/OPG signalling pathway and the development of stress fracture injury. The association of rs3018362 (RANK) and rs1021188 (RANKL) with stress fracture injury susceptibility supports their role in the maintenance of bone health, and offers potential targets for therapeutic interventions

Impaired in vivo binding of MeCP2 to chromatin in the absence of its DNA methyl-binding domain

MeCP2 is a methyl-CpG-binding protein that is a main component of brain chromatin in vertebrates. In vitro studies have determined that in addition to its specific methyl-CpG-binding domain (MBD) MeCP2 also has several chromatin association domains. However, the specific interactions of MeCP2 with methylated or non-methylated chromatin regions and the structural characteristics of the resulting DNA associations in vivo remain poorly understood. We analysed the role of the MBD in MeCP2-chromatin associations in vivo using an MeCP2 mutant Rett syndrome mouse model (Mecp2(tm1.1Jae)) in which exon 3 deletion results in an N-terminal truncation of the protein, including most of the MBD. Our results show that in mutant mice, the truncated form of MeCP2 (delta MeCP2) is expressed in different regions of the brain and liver, albeit at 50% of its wild-type (wt) counterpart. In contrast to the punctate nuclear distribution characteristic of wt MeCP2, delta MeCP2 exhibits both diffuse nuclear localization and a substantial retention in the cytoplasm, suggesting a dysfunction of nuclear transport. In mutant brain tissue, neuronal nuclei are smaller, and delta MeCP2 chromatin is digested faster by nucleases, producing a characteristic nuclease-resistant dinucleosome. Although a fraction of delta MeCP2 is found associated with nucleosomes, its interaction with chromatin is transient and weak. Thus, our results unequivocally demonstrate that in vivo the MBD of MeCP2 together with its adjacent region in the N-terminal domain are critical for the proper interaction of the protein with chromatin, which cannot be replaced by any other of its protein domains