Semantic memory is the subsystem of human memory that stores knowledge of concepts or meanings, as opposed to life-specific experiences. How humans organize semantic information remains poorly ...understood. In an effort to better understand this issue, we conducted a verbal fluency experiment on 200 participants with the aim of inferring and representing the conceptual storage structure of the natural category of animals as a network. This was done by formulating a statistical framework for co-occurring concepts that aims to infer significant concept–concept associations and represent them as a graph. The resulting network was analyzed and enriched by means of a missing links recovery criterion based on modularity. Both network models were compared to a thresholded co-occurrence approach. They were evaluated using a random subset of verbal fluency tests and comparing the network outcomes (linked pairs are clustering transitions and disconnected pairs are switching transitions) to the outcomes of two expert human raters. Results show that the network models proposed in this study overcome a thresholded co-occurrence approach, and their outcomes are in high agreement with human evaluations. Finally, the interplay between conceptual structure and retrieval mechanisms is discussed.
Dipeptidyl peptidase-4 (DPP4) inhibition is a potential strategy to increase the engraftment rate of haematopoietic stem/progenitor cells. A recent clinical trial using sitagliptin, a DPP4 inhibitor ...approved for type 2 diabetes mellitus, has been shown to be a promising approach in adults with haematological malignancies after umbilical cord blood (UCB) haematopoietic cell transplantation (HCT). On the basis of data from this clinical trial, a semi-mechanistic model was developed to simultaneously describe DPP4 activity after multiple doses of sitagliptin in subjects with haematological malignancies after a single-unit UCB HCT.
The clinical study included 24 patients who received myeloablative conditioning followed by oral sitagliptin with single-unit UCB HCT. Using a nonlinear mixed-effects approach, a semi-mechanistic pharmacokinetic-pharmacodynamic model was developed to describe DPP4 activity from these trial data, using NONMEM version 7.2 software. The model was used to drive Monte Carlo simulations to probe the various dosage schedules and the attendant DPP4 response.
The disposition of sitagliptin in plasma was best described by a two-compartment model. The relationship between sitagliptin concentrations and DPP4 activity was best described by an indirect response model with a negative feedback loop. Simulations showed that twice daily or three times daily dosage schedules were superior to a once daily schedule for maximal DPP4 inhibition at the lowest sitagliptin exposure.
This study provides the first pharmacokinetic-pharmacodynamic model of sitagliptin in the context of HCT, and provides a valuable tool for exploration of optimal dosing regimens, which are critical for improving the time to engraftment in patients after UCB HCT.
Electronic cigarettes (e-cigarettes) are a recent technology that has gained rapid acceptance. Still, little is known about them in terms of safety and effectiveness. A basic question is how ...effectively they deliver nicotine; however, the literature is surprisingly unclear on this point. Here, a population pharmacokinetic model was developed for nicotine and its major metabolite cotinine with the aim to provide a reliable framework for the simulation of nicotine and cotinine concentrations over time, based solely on inhalation airflow recordings and individual covariates i.e., weight and breath carbon monoxide (CO) levels.
This study included ten adults self-identified as heavy smokers (at least one pack of cigarettes per day). Plasma nicotine and cotinine concentrations were measured at regular 10-min intervals for 90 min while human subjects inhaled nicotine vapor from a modified e-cigarette. Airflow measurements were recorded every 200 ms throughout the session. A population pharmacokinetic model for nicotine and cotinine was developed based on previously published pharmacokinetic parameters and the airflow recordings. All of the analyses were performed with the non-linear mixed-effect modeling software NONMEM(®) version 7.2.
The results show that e-cigarettes deliver nicotine effectively, although the pharmacokinetic profiles are lower than those achieved with regular cigarettes. Our pharmacokinetic model effectively predicts plasma nicotine and cotinine concentrations from the inhalation volume, and initial breath CO.
E-cigarettes are effective at delivering nicotine. This new pharmacokinetic model of e-cigarette usage might be used for pharmacodynamic analysis where the pharmacokinetic profiles are not available.
The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply ...analytic measures of network communication to the structural connectivity of the human brain and explore the capacity of these measures to predict resting-state functional connectivity across three independently acquired datasets. We focus on the layout of shortest paths across the network and on two communication measures—search information and path transitivity—which account for how these paths are embedded in the rest of the network. Search information is an existing measure of information needed to access or trace shortest paths; we introduce path transitivity to measure the density of local detours along the shortest path. We find that both search information and path transitivity predict the strength of functional connectivity among both connected and unconnected node pairs. They do so at levels that match or significantly exceed path length measures, Euclidean distance, as well as computational models of neural dynamics. This capacity suggests that dynamic couplings due to interactions among neural elements in brain networks are substantially influenced by the broader network context adjacent to the shortest communication pathways.
Multiple Sclerosis (MS) is considered a T-cell-mediated autoimmune disease with a prototypical oscillatory behavior, as evidenced by the presence of clinical relapses. Understanding the dynamics of ...immune cells governing the course of MS, therefore, has many implications for immunotherapy. Here, we used flow cytometry to analyze the time-dependent behavior of antigen-specific effector (T(eff)) and regulatory (T(reg)) T cells and microglia in mice model of MS, Experimental Autoimmune Encephalomyelitis (EAE), and compared the observations with a mathematical cross-regulation model of T-cell dynamics in autoimmune disease.
We found that T(eff) and T(reg) cells specific to myelin olygodendrocyte glycoprotein (MOG) developed coupled oscillatory dynamics with a 4- to 5-day period and decreasing amplitude that was always higher for the T(eff) populations, in agreement with the mathematical model. Microglia activation followed the oscillations of MOG-specific T(eff) cells in the secondary lymphoid organs, but they were activated before MOG-specific T-cell peaks in the CNS. Finally, we assessed the role of B-cell depletion induced by anti-CD20 therapy in the dynamics of T cells in an EAE model with more severe disease after therapy. We observed that B-cell depletion decreases T(eff) expansion, although its oscillatory behavior persists. However, the effect of B cell depletion was more significant in the T(reg) population within the CNS, which matched with activation of microglia and worsening of the disease. Mathematical modeling of T-cell cross-regulation after anti-CD20 therapy suggests that B-cell depletion may influence the dynamics of T cells by fine-tuning their activation.
The oscillatory dynamics of T-cells have an intrinsic origin in the physiological regulation of the adaptive immune response, which influences both disease phenotype and response to immunotherapy.
Understanding the contribution of the brain white matter pathways to declarative verbal memory processes has been hindered by the lack of an adequate model in humans. An attractive and underexplored ...approach to study white matter region functionality in the living human brain is through the use of non-aprioristic models which specifically search disrupted white matter pathways. For this purpose, we employed voxel-based lesion–function mapping to correlate white matter lesions on the magnetic resonance images of 46 multiple sclerosis patients with their performance on declarative verbal memory storage and retrieval. White matter correlating with storage was in the temporal lobe–particularly lateral to the hippocampus and in the anterior temporal stem–, in the thalamic region and in the anterior limb of the internal capsule, all on the left hemisphere, and also in the right anterior temporal stem. The same volumes were relevant for retrieval, but to them were added temporo-parieto-frontal paramedian bundles, particularly the cingulum and the fronto-occipital fasciculus. These 3D maps indicate the white matter regions most critically involved in declarative verbal memory in humans.
The relapsing-remitting dynamics is a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). Although current understanding of both cellular and molecular mechanisms involved in the ...pathogenesis of autoimmune diseases is significant, how their activity generates this prototypical dynamics is not understood yet. In order to gain insight about the mechanisms that drive these relapsing-remitting dynamics, we developed a computational model using such biological knowledge. We hypothesized that the relapsing dynamics in autoimmunity can arise through the failure in the mechanisms controlling cross-regulation between regulatory and effector T cells with the interplay of stochastic events (e.g. failure in central tolerance, activation by pathogens) that are able to trigger the immune system.
The model represents five concepts: central tolerance (T-cell generation by the thymus), T-cell activation, T-cell memory, cross-regulation (negative feedback) between regulatory and effector T-cells and tissue damage. We enriched the model with reversible and irreversible tissue damage, which aims to provide a comprehensible link between autoimmune activity and clinical relapses and active lesions in the magnetic resonances studies in patients with Multiple Sclerosis. Our analysis shows that the weakness in this negative feedback between effector and regulatory T-cells, allows the immune system to generate the characteristic relapsing-remitting dynamics of autoimmune diseases, without the need of additional environmental triggers. The simulations show that the timing at which relapses appear is highly unpredictable. We also introduced targeted perturbations into the model that mimicked immunotherapies that modulate effector and regulatory populations. The effects of such therapies happened to be highly dependent on the timing and/or dose, and on the underlying dynamic of the immune system.
The relapsing dynamic in MS derives from the emergent properties of the immune system operating in a pathological state, a fact that has implications for predicting disease course and developing new therapies for MS.
Background
Tadalafil 40 mg once daily is approved for adult patients with pulmonary arterial hypertension (PAH). To investigate and potentially fulfill an unmet need in pediatric patients with PAH, ...pharmacokinetic (PK) data were explored in a pediatric phase Ib/II study and pooled with prior phase III (pulmonary arterial hypertension and response to tadalafil PHIRST-1) adult data to develop the first population PK model for tadalafil in pediatric patients with PAH.
Methods
H6D-MC-LVIG (NCT01484431) was an open-label, multicenter, multiple ascending dose study in pediatric patients with PAH, while PHIRST-1 was a phase III, multicenter, randomized, double-blind, placebo-controlled, parallel design study in adults with PAH who received one of five treatments (tadalafil 2.5, 10, 20, or 40 mg, or placebo orally, once daily). PK data from the studies were pooled to develop a pediatric population PK model for tadalafil that characterized relationships among dose, exposure, and the effects of covariates with an aim to develop a population PK model that could simulate concentration–time profiles and assess exposure-matched dosing strategies in a pediatric PAH population.
Results
In line with the observed data, modeling and simulation demonstrated that the doses studied in the pediatric population produced area under the concentration–time curves (AUCs) within the range of those associated with improved exercise ability in adults with PAH. The analyses included 1430 observations from 305 adult patients (PHIRST-1: 69 males and 236 females, 1102 observations) and 19 pediatric patients (LVIG: 6 males and 13 females, 328 observations) who received tadalafil once daily at different dose levels. The best-fit base model retained an effect of weight on apparent volume of distribution (
V
/
F
), fixed to the allometric scaling value of 1, and did not include an effect of weight on apparent clearance (
CL
/
F
). Other covariate effects were that bosentan increased
CL
/
F
,
V
/
F
decreased with decreasing body weight, and bioavailability (
F
) decreased with increasing dose and decreasing age. The PK model reliably predicted the observed concentrations and overall variability evident from the overlap of the individual observed concentrations with the distributions of simulated concentrations.
Conclusions
A one-compartment model parameterized in terms of
F
, absorption rate constant,
CL
/
F
, and
V
/
F
described the data well. The model demonstrated that plasma tadalafil concentrations in pediatric patients aged 2 to < 18 years were similar to those in adults at similar doses, and confirmed that dosing of 40 mg once daily in pediatric patients with a bodyweight ≥ 40 kg, and a dose of 20 mg once daily in patients with a body weight < 40 kg and aged ≥ 2 years are suitable for phase III evaluation.
Trial Registration Number (Date of Registration)
LVIG: ClinicalTrials.gov identifier: NCT01484431 (2 December 2011). PHIRST-1: ClinicalTrials.gov identifier: NCT00125918 (2 August 2005).
T-cell immunoglobulin and mucin-domain-containing molecule-3 (TIM-3) blunts anticancer immunity and mediates resistance to programmed death 1 (PD-1) and PD ligand 1 (PD-L1) inhibitors. We assessed a ...novel, first-in-class, TIM-3 mAb, LY3321367, alone or in combination with the anti-PD-L1 antibody, LY300054 in patients with advanced solid tumor.
This open-label, multicenter, phase Ia/b study aimed to define the safety/tolerability and recommended phase II dose (RP2D) of LY3321367 with or without LY300054. Secondary objectives included pharmacokinetics/pharmacodynamics, immunogenicity, and efficacy. Biomarkers were assessed in exploratory analysis.
No dose-limiting toxicities were observed in the monotherapy (
= 30) or combination (
= 28) dose escalation. LY3321367 treatment-related adverse events (≥2 patients) included pruritus, rash, fatigue, anorexia, and infusion-related reactions. Dose-proportional increase in LY3321367 concentrations was not affected by either LY300054 or antidrug antibodies (observed in 50%-70% of patients). Pharmacokinetic/pharmacodynamic modeling indicated 100% target engagement at doses ≥600 mg. LY3321367 RP2D was 1,200 mg biweekly for four doses followed by 600 mg every 2 weeks thereafter. In the non-small cell lung cancer monotherapy expansion cohort, outcomes varied by prior anti-PD-1 therapy response status: anti-PD-1/L1 refractory patients
= 23, objective response rate (ORR) 0%, disease control rate (DCR) 35%, progression-free survival (PFS) 1.9 months versus anti-PD-1/L1 responders (
= 14, ORR 7%, DCR 50%, PFS 7.3 months). In combination expansion cohorts (
= 91), ORR and DCR were 4% and 42%; CD8 infiltration in paired biopsies increased in approximately half these patients.
LY3321367 exhibited acceptable safety profile with favorable pharmacokinetics/pharmacodynamics but only modest antitumor activity. The therapeutic relevance of TIM-3 blockade requires further investigation.
Graph theoretical analysis has played a key role in characterizing global features of the topology of complex networks, describing diverse systems such as protein interactions, food webs, social ...relations and brain connectivity. How system elements communicate with each other depends not only on the structure of the network, but also on the nature of the system's dynamics which are constrained by the amount of knowledge and resources available for communication processes. Complementing widely used measures that capture efficiency under the assumption that communication preferentially follows shortest paths across the network ("routing"), we define analytic measures directed at characterizing network communication when signals flow in a random walk process ("diffusion"). The two dimensions of routing and diffusion efficiency define a morphospace for complex networks, with different network topologies characterized by different combinations of efficiency measures and thus occupying different regions of this space. We explore the relation of network topologies and efficiency measures by examining canonical network models, by evolving networks using a multi-objective optimization strategy, and by investigating real-world network data sets. Within the efficiency morphospace, specific aspects of network topology that differentially favor efficient communication for routing and diffusion processes are identified. Charting regions of the morphospace that are occupied by canonical, evolved or real networks allows inferences about the limits of communication efficiency imposed by connectivity and dynamics, as well as the underlying selection pressures that have shaped network topology.
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