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Charged-particle pseudorapidity density at mid-rapidity in p–Pb collisions at √sNN = 8.16 TeV
(2019)
The pseudorapidity density of charged particles, dNch/dη, in p-Pb collisions has been measured at a centre-of-mass energy per nucleon-nucleon pair of sNN−−−√ = 8.16 TeV at mid-pseudorapidity for non-single-diffractive events. The results cover 3.6 units of pseudorapidity, |η|<1.8. The dNch/dη value is 19.1±0.7 at |η|<0.5. This quantity divided by ⟨Npart⟩/2, is 4.73±0.20, which is 9.5% higher than the corresponding value for p-Pb collisions at sNN−−−√ = 5.02 TeV. Measurements are compared with models based on different mechanisms for particle production. All models agree within uncertainties with data in the Pb-going side, while HIJING overestimates, showing a symmetric behaviour, and EPOS underestimates the p-going side of the dNch/dη distribution. Saturation-based models reproduce the distributions well for η>−1.3. The dNch/dη is also measured for different centrality estimators, based both on the charged-particle multiplicity and on the energy deposited in the Zero-Degree Calorimeters. A study of the implications of the large multiplicity fluctuations due to the small number of participants for systems like p-Pb in the centrality calculation for multiplicity-based estimators is discussed, demonstrating the advantages of determining the centrality with energy deposited near beam rapidity.
The ALICE collaboration performed the first rapidity-differential measurement of coherent J/ψ photoproduction in ultra-peripheral Pb-Pb collisions at a center-of-mass energy sNN−−−√ = 5.02 TeV. The J/ψ is detected via its dimuon decay in the forward rapidity region (−4.0<y<−2.5) for events where the hadronic activity is required to be minimal. The analysis is based on an event sample corresponding to an integrated luminosity of about 750 μb−1. The cross section for coherent J/ψ production is presented in six rapidity bins. The results are compared with theoretical models for coherent J/ψ photoproduction. These comparisons indicate that gluon shadowing effects play a role in the photoproduction process. The ratio of ψ′ to J/ψ coherent photoproduction cross sections was measured and found to be consistent with that measured for photoproduction off protons.
The coherent photoproduction of J/ψ was measured in ultra-peripheral Pb-Pb collisions at a center-of-mass energy sNN−−−√=5.02 TeV with the ALICE detector. The J/ψ is detected via its dimuon decay in the forward rapidity region for events where the hadronic activity is required to be minimal. The analysis is based on an event sample corresponding to an integrated luminosity of about 750 μb−1. The cross section for coherent J/ψ production is presented in six rapidity bins, covering the interval −4.0<y<−2.5. The results are compared with theoretical models for coherent J/ψ photoproduction. The results indicate that gluon shadowing effects play a role in the photoproduction process. The ratio of ψ′ to J/ψ coherent photoproduction cross sections was measured and found to be consistent with that measured for photoproduction off protons.
Introduction: When developing bio-enabling formulations, innovative tools are required to understand and predict in vivo performance and may facilitate approval by regulatory authorities. EMEND® is an example of such a formulation, in which the active pharmaceutical ingredient, aprepitant, is nano-sized. The aims of this study were 1) to characterize the 80 mg and 125 mg EMEND® capsules in vitro using biorelevant tools, 2) to develop and parameterize a physiologically based pharmacokinetic (PBPK) model to simulate and better understand the in vivo performance of EMEND® capsules and 3) to assess which parameters primarily influence the in vivo performance of this formulation across the therapeutic dose range.
Methods: Solubility, dissolution and transfer experiments were performed in various biorelevant media simulating the fasted and fed state environment in the gastrointestinal tract. An in silico PBPK model for healthy volunteers was developed in the Simcyp Simulator, informed by the in vitro results and data available from the literature.
Results: In vitro experiments indicated a large effect of native surfactants on the solubility of aprepitant. Coupling the in vitro results with the PBPK model led to an appropriate simulation of aprepitant plasma concentrations after administration of 80 mg and 125 mg EMEND® capsules in both the fasted and fed states. Parameter Sensitivity Analysis (PSA) was conducted to investigate the effect of several parameters on the in vivo performance of EMEND®. While nano-sizing aprepitant improves its in vivo performance, intestinal solubility remains a barrier to its bioavailability and thus aprepitant should be classified as DCS IIb.
Conclusions: The present study underlines the importance of combining in vitro and in silico biopharmaceutical tools to understand and predict the absorption of this poorly soluble compound from an enabling formulation. The approach can be applied to other poorly soluble compounds to support rational formulation design and to facilitate regulatory assessment of the bio-performance of enabling formulations.
In ultrarelativistic heavy-ion collisions, the event-by-event variation of the elliptic flow v2 reflects fluctuations in the shape of the initial state of the system. This allows to select events with the same centrality but different initial geometry. This selection technique, Event Shape Engineering, has been used in the analysis of charge-dependent two- and three-particle correlations in Pb-Pb collisions at sNN−−−√=2.76 TeV. The two-particle correlator ⟨cos(φα−φβ)⟩, calculated for different combinations of charges α and β, is almost independent of v2 (for a given centrality), while the three-particle correlator ⟨cos(φα+φβ−2Ψ2)⟩ scales almost linearly both with the event v2 and charged-particle pseudorapidity density. The charge dependence of the three-particle correlator is often interpreted as evidence for the Chiral Magnetic Effect (CME), a parity violating effect of the strong interaction. However, its measured dependence on v2 points to a large non-CME contribution to the correlator. Comparing the results with Monte Carlo calculations including a magnetic field due to the spectators, the upper limit of the CME signal contribution to the three-particle correlator in the 10-50% centrality interval is found to be 26-33% at 95% confidence level.
Context information supports serial dependence of multiple visual objects across memory episodes
(2019)
Visual perception operates in an object-based manner, by integrating associated features via attention. Working memory allows a flexible access to a limited number of currently relevant objects, even when they are occluded or physically no longer present. Recently, it has been shown that we compensate for small changes of an object’s feature over memory episodes, which can support its perceptual stability. This phenomenon was termed ‘serial dependence’ and has mostly been studied in situations that comprised only a single relevant object. However, since we are typically confronted with situations where several objects have to be perceived and held in working memory, the central question of how we selectively create temporal stability of several objects has remained unsolved. As different objects can be distinguished by their accompanying context features, like their color or temporal position, we tested whether serial dependence is supported by the congruence of context features across memory episodes. Specifically, we asked participants to remember the motion directions of two sequentially presented colored dot fields per trial. At the end of a trial one motion direction was cued for continuous report either by its color (Experiment 1) or serial position (Experiment 2). We observed serial dependence, i.e., an attractive bias of currently toward previously memorized objects, between current and past motion directions that was clearly enhanced when items had the same color or serial position across trials. This bias was particularly pronounced for the context feature that was used for cueing and for the target of the previous trial. Together, these findings demonstrate that coding of current object representations depends on previous representations, especially when they share similar content and context features. Apparently the binding of content and context features is not completely erased after a memory episode, but it is carried over to subsequent episodes. As this reflects temporal dependencies in natural settings, the present findings reveal a mechanism that integrates corresponding bundles of content and context features to support stable representations of individualized objects over time.
Word familiarity and predictive context facilitate visual word processing, leading to faster recognition times and reduced neuronal responses. Previously, models with and without top-down connections, including lexical-semantic, pre-lexical (e.g., orthographic/ phonological), and visual processing levels were successful in accounting for these facilitation effects. Here we systematically assessed context-based facilitation with a repetition priming task and explicitly dissociated pre-lexical and lexical processing levels using a pseudoword familiarization procedure. Experiment 1 investigated the temporal dynamics of neuronal facilitation effects with magnetoencephalography (MEG; N=38 human participants) while Experiment 2 assessed behavioral facilitation effects (N=24 human participants). Across all stimulus conditions, MEG demonstrated context-based facilitation across multiple time windows starting at 100 ms, in occipital brain areas. This finding indicates context based-facilitation at an early visual processing level. In both experiments, we furthermore found an interaction of context and lexical familiarity, such that stimuli with associated meaning showed the strongest context-dependent facilitation in brain activation and behavior. Using MEG, this facilitation effect could be localized to the left anterior temporal lobe at around 400 ms, indicating within-level (i.e., exclusively lexical-semantic) facilitation but no top-down effects on earlier processing stages. Increased pre-lexical familiarity (in pseudowords familiarized utilizing training) did not enhance or reduce context effects significantly. We conclude that context based-facilitation is achieved within visual and lexical processing levels. Finally, by testing alternative hypotheses derived from mechanistic accounts of repetition suppression, we suggest that the facilitatory context effects found here are implemented using a predictive coding mechanism.
Mental imagery provides an essential simulation tool for remembering the past and planning the future, with its strength affecting both cognition and mental health. Research suggests that neural activity spanning prefrontal, parietal, temporal, and visual areas supports the generation of mental images. Exactly how this network controls the strength of visual imagery remains unknown. Here, brain imaging and transcranial magnetic phosphene data show that lower resting activity and excitability levels in early visual cortex (V1-V3) predict stronger sensory imagery. Electrically decreasing visual cortex excitability using tDCS increases imagery strength, demonstrating a causative role of visual cortex excitability in controlling visual imagery. These data suggest a neurophysiological mechanism of cortical excitability involved in controlling the strength of mental images.
Attention-Deficit/Hyperactivity Disorder (ADHD) and obesity are frequently comorbid, genetically correlated, and share brain substrates. The biological mechanisms driving this association are unclear, but candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the genetic link between ADHD and obesity measures and investigate associations of overlapping genes with brain volumes. We tested the association of dopaminergic and circadian rhythm gene sets with ADHD, body mass index (BMI), and obesity (using GWAS data of N=53,293, N=681,275, and N=98,697, respectively). We then conducted genome-wide ADHD-BMI and ADHD-obesity gene-based meta-analyses, followed by pathway enrichment analyses. Finally, we tested the association of ADHD-BMI overlapping genes with brain volumes (primary GWAS data N=10,720–10,928; replication data N=9,428). The dopaminergic gene set was associated with both ADHD (P=5.81×10−3) and BMI (P=1.63×10−5), the circadian rhythm was associated with BMI (P=1.28×10−3). The genome-wide approach also implicated the dopaminergic system, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was enriched in both ADHD-BMI and ADHD-obesity results. The ADHD-BMI overlapping genes were associated with putamen volume (P=7.7×10−3; replication data P=3.9×10−2) – a brain region with volumetric reductions in ADHD and BMI and linked to inhibitory control. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling and involving the putamen, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering shared etiological factors underlying the frequently observed ADHD-obesity comorbidity may have important implications in terms of prevention and/or efficient treatment of these conditions.
Attention-Deficit/Hyperactivity Disorder (ADHD) is frequently comorbid with other psychiatric disorders and also with somatic conditions, such as obesity. In addition to the clinical overlap, significant genetic correlations have been found between ADHD and obesity as well as body mass index (BMI). The biological mechanisms driving this association are largely unknown, but some candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the link between ADHD and obesity measures. Using the largest GWAS summary statistics currently available for ADHD (N=53,293), BMI (N=681,275), and obesity (N=98,697), we first tested the association of dopaminergic and circadian rhythm gene sets with each phenotype. This hypothesis-driven approach showed that the dopaminergic gene set was associated with both ADHD (P=5.81×10−3) and BMI (P=1.63×10−5), while the circadian rhythm gene set was associated with BMI only (P=1.28×10−3). We then took a data-driven approach by conducting genome-wide ADHD-BMI and ADHD-obesity gene-based meta-analyses, followed by pathway enrichment analyses. This approach further supported the implication of dopaminergic signaling in the link between ADHD and obesity measures, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was significantly enriched in both the ADHD-BMI and ADHD-obesity gene-based meta-analysis results. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering the shared etiological factors underlying the frequently observed ADHD-obesity comorbidity may have important implications in terms of preventive interventions and/or efficient treatment of these conditions.