Individual Time Courses Research Articles

Characterising the Time Course of the Dilatory Response of Healthy Retinal Arteries during Flicker-Light Provocation

Introduction: The dilatory response of healthy retinal arterioles to flicker-light (FL) provocation appears to be biphasic. The vessel diameter rapidly increases (acute phase) over 5–10 s, then barely increases thereafter (maintenance phase) until FL cessation. This reaction is usually characterised at a single point by two parameters: maximum dilation (MD) relative to baseline diameter (MD, %) and time to MD (RT, s). This paper describes the biphasic reaction of retinal arteries during FL provocation using a bi-linear function. Methods: Retinal arterioles from 45 adults were examined during flicker provocation. Each individual time course of arterial diameter change during FL provocation was characterised by a bi-linear equation and compared with MD and RT. Results: Slopes of the acute phase were 0.506%/s, and the maintenance phase was nearly flat (0.012%/s). The mean time at which the reaction changed from acute to maintenance phase was 7.4 s which is significantly different from RT (16.0 s). Mean dilation at this point (2.987%) was significantly different from MD (3.734%), but it was still 80% of MD in less than half of RT. Conclusion: Bi-linear fitting parameters better characterises the arterial dilatory response than MD and RT. Further stratification of clinical groups using bi-linear fitting may provide insight of the underlying physiology of vessel dilation for different pathologies.

Assessing the degree of hepatic ischemia-reperfusion injury using physiologically based pharmacokinetic modeling of sodium fluorescein disposition in ex vivo machine-perfused livers.

Ischemia-reperfusion injury (IRI) is an intrinsic risk associated with liver transplantation. Ex vivo hepatic machine perfusion (MP) is an emerging organ preservation technique that can mitigate IRI, especially in livers subjected to prolonged warm ischemia time (WIT). However, a method to quantify the biological response to WIT during MP has not been established. Previous studies used physiologically based pharmacokinetic (PBPK) modeling to demonstrate that a decrease in hepatic transport and biliary excretion of the tracer molecule sodium fluorescein (SF) could correlate with increasing WIT in situ. Furthermore, these studies proposed intracellular sequestration of the hepatocyte canalicular membrane transporter multidrug resistance-associated protein 2 (MRP2) leading to decreased MRP2 activity (maximal transport velocity; Vmax) as the potential mechanism for decreased biliary SF excretion. We adapted an extant PBPK model to account for ex vivo hepatic MP and fit a six-parameter version of this model to control time-course measurements of SF in MP perfusate and bile. We then identified parameters whose values were likely insensitive to changes in WIT and fixed them to generate a reduced model with only three unknown parameters. Finally, we fit the reduced model to each individual biological replicate SF time course with differing WIT, found the mean estimated value for each parameter, and compared them using a one-way ANOVA. We demonstrated that there was a significant decrease in the estimated value of Vmax for MRP2 at the 30-min WIT. These studies provide the foundation for future studies investigating real-time assessment of liver viability during ex vivo MP.NEW & NOTEWORTHY We developed a computational model of sodium fluorescein (SF) biliary excretion in ex vivo machine perfusion and used this model to assess changes in model parameters associated with the activity of MRP2, a hepatocyte membrane transporter, in response to increasing warm ischemia time. We found a significant decrease in the parameter value describing MRP2 activity, consistent with a role of decreased MRP2 function in ischemia-reperfusion injury leading to decreased secretion of SF into bile.

Power output at the moderate-to-heavy intensity transition decreases in a non-linear fashion during prolonged exercise

PurposeThe aims of this study were to: (i) describe the time course of the decrease in power output at the moderate-to-heavy intensity transition during prolonged exercise; (ii) investigate the association between durability of the moderate-to-heavy intensity transition and exercise capacity; and (iii) explore physiological correlates of durability of the moderate-to-heavy intensity transition.MethodsTwelve trained cyclists (age: 40 ± 8 y, V˙\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\dot{\ ext{V}}$$\\end{document}O2peak: 52.3 ± 5.2 mL·min−1·kg−1) performed an exhaustive cycling protocol involving alternating incremental exercise tests to determine power output at the moderate-to-heavy intensity transition via the first ventilatory threshold (VT1), and 30-min bouts at 90% of the power output at the previously estimated VT1 in the rested state. The individual time course of VT1 was modelled using linear and second-order polynomial functions, and time to a 5% decrease in VT1 (Δ5%VT1) was estimated using the best-fitting model.ResultsPower output at VT1 decreased according to a second-order polynomial function in 11 of 12 participants. Time-to-task failure (234 ± 66 min) was correlated with Δ5%VT1 (139 ± 78 min, rs = 0.676, p = 0.016), and these were strongly correlated with absolute and relative rates of fat oxidation at specific exercise intensities measured during the incremental test performed in the rested state.ConclusionsThese data: (i) identify a non-linear time course of decreases in the moderate-to-heavy intensity transition during prolonged exercise; (ii) support the importance of durability of the moderate-to-heavy intensity transition in prolonged exercise capacity; and (iii) suggest durability of the moderate-to-heavy intensity transition is related to fat oxidation rates.

Kinetics of RNA-LNP delivery and protein expression

Lipid nanoparticles (LNPs) employing ionizable lipids are the most advanced technology for delivery of RNA, most notably mRNA, to cells. LNPs represent well-defined core–shell particles with efficient nucleic acid encapsulation, low immunogenicity and enhanced efficacy. While much is known about the structure and activity of LNPs, less attention is given to the timing of LNP uptake, cytosolic transfer and protein expression. However, LNP kinetics is a key factor determining delivery efficiency. Hence quantitative insight into the multi-cascaded pathway of LNPs is of interest to elucidate the mechanism of delivery. Here, we review experiments as well as theoretical modeling of the timing of LNP uptake, mRNA-release and protein expression. We describe LNP delivery as a sequence of stochastic transfer processes and review a mathematical model of subsequent protein translation from mRNA. We compile probabilities and numbers obtained from time resolved microscopy. Specifically, live-cell imaging on single cell arrays (LISCA) allows for high-throughput acquisition of thousands of individual GFP reporter expression time courses. The traces yield the distribution of mRNA life-times, expression rates and expression onset. Correlation analysis reveals an inverse dependence of gene expression efficiency and transfection onset-times. Finally, we discuss why timing of mRNA release is critical in the context of codelivery of multiple nucleic acid species as in the case of mRNA co-expression or CRISPR/Cas gene editing.

Optimization of nutritional strategies using a mechanistic computational model in prediabetes: Application to the J-DOIT1 study data.

Lifestyle interventions have been shown to prevent or delay the onset of diabetes; however, inter-individual variability in responses to such interventions makes lifestyle recommendations challenging. We analyzed the Japan Diabetes Outcome Intervention Trial-1 (J-DOIT1) study data using a previously published mechanistic simulation model of type 2 diabetes onset and progression to understand the causes of inter-individual variability and to optimize dietary intervention strategies at an individual level. J-DOIT1, a large-scale lifestyle intervention study, involved 2607 subjects with a 4.2-year median follow-up period. We selected 112 individuals from the J-DOIT1 study and calibrated the mechanistic model to each participant's body weight and HbA1c time courses. We evaluated the relationship of physiological (e.g., insulin sensitivity) and lifestyle (e.g., dietary intake) parameters with variability in outcome. Finally, we used simulation analyses to predict individually optimized diets for weight reduction. The model predicted individual body weight and HbA1c time courses with a mean (±SD) prediction error of 1.0 kg (±1.2) and 0.14% (±0.18), respectively. Individuals with the most and least improved biomarkers showed no significant differences in model-estimated energy balance. A wide range of weight changes was observed for similar model-estimated caloric changes, indicating that caloric balance alone may not be a good predictor of body weight. The model suggests that a set of optimal diets exists to achieve a defined weight reduction, and this set of diets is unique to each individual. Our diabetes model can simulate changes in body weight and glycemic control as a result of lifestyle interventions. Moreover, this model could help dieticians and physicians to optimize personalized nutritional strategies according to their patients' goals.

Pharmacodynamic Model-Based Safety Management of Eribulin-Induced Myelosuppression in Patients With Breast Cancer.

Neutropenia is a major dose-limiting toxicity of cancer chemotherapy. Semimechanistic mathematical models have been applied to describe the time course of neutrophil counts. The objectives of this study were to develop a mathematical model describing changes in neutrophil counts during eribulin treatment, to apply the empirical Bayes method to predict the probability of developing neutropenia ≥ grade 3 during eribulin treatment in each patient, and to propose the implementation of this mathematical tool in clinical practice for individual safety management. The present model analysis and subsequent external evaluation were performed using the data of 481 patients with breast cancer, previously obtained from a postmarketing surveillance (training set) and a phase 2 clinical study (validation set). The model we previously reported (Kawamura et al 2018) was modified to improve its predictive capability. The individual time course of neutrophil changes during the treatment period was predicted by the empirical Bayes method using the observed neutrophil counts at baseline and the first measurement after the first eribulin dose. To evaluate the predictability of this method, the predicted neutrophil counts were compared with those of the observed values. The developed model provided good individual predictions, as indicated by the goodness-of-fit plots between the predicted and observed neutrophil counts, especially for a lower neutrophil count range. Days required to reach the nadir after the dose were also well-predicted. The sensitivity, specificity, and accuracy of the prediction of neutropenia grade ≥3 were 76%, 53%, and 71%, respectively. We developed a mathematical method for predicting and managing the risk of neutropenia during eribulin treatment. This method is generally applicable to other cases of chemotherapy-induced neutropenia and can be a new practical tool for individual safety management.

Ustekinumab Trough Concentrations Are Associated with Biochemical Outcomes in Patients with Crohn’s Disease

ObjectiveIt is unknown whether ustekinumab (UST) levels can predict clinical outcomes in Crohn’s disease (CD) patients. We assessed the exposure–response relationship of UST trough concentrations with biochemical outcomes at week 24 in a prospective, real-world setting.MethodsWe performed a prospective study in patients with CD starting UST in four academic centres in the Netherlands. All patients received a weight-adjusted intravenous (IV) UST induction dose, followed by one subcutaneous (SC) dose of 90 mg UST at 8 weeks. Maintenance therapy consisted of 90 mg subcutaneous UST every 8 or 12 weeks. Individual UST concentration time course during treatment were estimated using a population pharmacokinetic (PK) model. Quartile analysis and logistic regression were performed to analyse if UST concentrations at week 8 were associated with biochemical remission rates at week 24 (C-reactive protein (CRP) ≤ 5 mg/L and / or faecal calprotectin (FC) ≤ 250 mg/kg).ResultsIn total, 124 patients with CD were included. Patients achieving biochemical remission at week 12 and 24 had significantly higher UST levels at week 8 compared to patients without biochemical remission (6.6 µg/mL versus 3.9 µg/mL, P < 0.01 and 6.3 µg/mL versus 3.9 µg/mL, P < 0.01, respectively). In quartile analysis, patients with UST levels in the highest quartile (≥ 6.3 µg/mL at week 8) had higher biochemical remission rates at week 12 and week 24. There was no association between UST levels at and corticosteroid-free clinical remission rates.ConclusionIn this real-world cohort of patients with CD, UST levels in the highest quartile (≥ 6.3 µg/mL) at week 8 were associated with higher biochemical remission rates at week 24.

“Life-changing”: the experience of super-responders to biologics in severe asthma

BackgroundThere is limited information on the patient’s perspective of how biologic treatments impact their lives. We conducted a qualitative study to explore the patient’s experience of being considered a super-responder from a quality of life perspective.MethodsPatients with severe asthma identified as super-responders were invited to semi-structured interviews conducted online. Participants could bring a family member/friend to the interview. The interviews explored experiences of biologic treatment, were transcribed and underwent thematic analysis.ResultsTwenty-five participants took part in this study. Themes emerged on the impact of biologic treatment for participants and for their friends/family: (i) Words used to describe their often life-changing experiences and (ii) the positive changes noted. Biologic treatment stopped the disruption of family life and social life caused by exacerbations. Improvements in mental health were also noted. Marked individual variations in the way it affected their lives were noted. Most participants noticed improvements 2–3 months after starting their biologic, but some noticed improvement within a few days and others after 6 months.ConclusionsSuper-responders reported profound but heterogeneous improvements following biologic treatment beyond asthma symptoms and exacerbations including important benefits to social and family life. Improvements may be underestimated as social and family benefits are not reliably measured in current studies with implications for health economic evaluations. Not all patients are super-responders, and excellent responses may be lost in group mean data in trials. Individual time course and response patterns need further elucidation to identify who will respond best to biologics.

Development of a Quantitative Systems Pharmacology Model to Explore Hemostatic Equivalency of Antithrombin Lowering

Fitusiran is an investigational siRNA therapeutic that targets antithrombin (AT) to rebalance hemostasis in people with hemophilia A (PwHA) or B (PwHB), irrespective of inhibitor status. Phase 3 clinical studies have demonstrated that fitusiran prophylaxis significantly reduced bleeding events compared to on-demand or prophylaxis treatment with factor concentrates or bypassing agents (Srivastava et al. Blood 2021; Young et al. Blood 2021; Kenet et al. ISTH 2022). To better understand the hemostatic equivalency of fitusiran prophylaxis (i.e., AT lowering), a quantitative systems pharmacology (QSP) model was developed to investigate thrombin generation in PwHA and PwHB in the context of AT lowering. QSP modeling is a mechanistic approach that integrates clinical and nonclinical data of the coagulation pathway to simulate the results of multiple in vitro coagulation assays, including the thrombin generation assay (TGA) and to mechanistically understand the readouts of these assays. The QSP model builds on prior published models of the coagulation cascade (Attarwala et al. ISTH 2017; Sridharan et al. Blood 2017), updated to represent reported steady-state levels of coagulation factors and accessory proteins in the plasma of healthy individuals and PwHA and PwHB (Figure 1). In addition, the model was extended to describe the impact of α-2-macroglobulin, a key regulator of thrombin, with increased influence at reduced AT levels that is critical to understand the impact of fitusiran on thrombin generation (Kattula et al. Blood 2020). After representing coagulation dynamics from plasma from healthy individuals, PwHA, and PwHB, the QSP model was applied to simulate TGA and relevant metrics, including thrombin peak height (Figure 1). TGA simulations were performed across different percentages of AT and FVIII. These simulations reproduced experimental TGA data from AT- and FVIII-double depleted plasma that was spiked with different levels of AT and/or FVIII. For these in vitro experiments, Factor VIII (FVIII) and AT-double depleted plasma was generated from congenital FVIII-deficient plasma by immunodepleting AT using an anti-AT antibody and recombinant AT protein was spiked back in to achieve different levels of AT. The QSP simulations also reproduced the reported formation of α-2-macroglobulin complexes with thrombin in each condition. Subsequently, the model was validated using both internal and published TGA and activated partial thromboplastin time (aPTT) datasets that were not used during model development. Next, a large (n=1000) virtual population (VP) of severe PwHA (<1% FVIII) was generated based on calibration of the model to individual patient data from completed fitusiran clinical studies. This analysis considered individual patient pharmacokinetic and AT time courses to describe thrombin peak height associated with different levels of AT reduction from fitusiran prophylaxis within a representative population of severe PwHA. The target therapeutic AT range of fitusiran prophylaxis treatment at steady state is 15-35%. Based on this model, the peak thrombin generated at 15-35% AT was similar to peak thrombin observed at 10-20 IU/kg FVIII in PwHA. In summary, by considering the impact of α-2-macroglobulin, the QSP model provides a mechanistic representation of thrombin generation under conditions of AT lowering, consistent with internal TGA data from donor-derived spiked plasma and clinical TGA data from both PwHA and PwHB. The VP analysis of fitusiran prophylaxis provided hemostatic equivalency with FVIII in a representative population of severe PwHA, with a targeted therapeutic range of AT of 15-35% resulting in a thrombin peak profile which was comparable to 10-20 IU/kg FVIII. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Determination of free heme in stored red blood cells with an apo-horseradish peroxidase-based assay.

Transfusion effectiveness of red blood cells (RBCs)has been associated with duration of the storage period. Storage-dependent RBC alterations lead to hemolysis and release of toxic free heme, but the increase of free hemelevels over time is largely unknown. In the current study, an apo-horseradish peroxidase (apoHRP)-based assay was applied to measure levels of free heme atregular intervals or periodically in supernatants of RBCs until a maximum storage period of 42days. Free heme levelsincreased with linear time-dependent kinetics up to day 21 and accelerated disproportionally after day 28 until day 42, as determined with the apoHRP assay. Individual timecourses of free heme in different RBC units exhibited high variability. Notably, levels of free hemoglobin, an established indicator of RBC damage, and those of total hemeincreased with continuous time-dependent linear kinetics over the entire 42day storage period, respectively. Supernatants from RBC units with high levels of free heme ledto inflammatory activation of human neutrophils. In conclusion, determining free heme in stored RBCs with the applied apoHRP assay may become feasible for testing ofRBC storage quality in clinical transfusion medicine.

P317 Ustekinumab Trough Concentrations Associated with Biochemical Outcomes in Patients with Crohn’s Disease

Abstract Background Ustekinumab (UST) is a monoclonal antibody which binds to the p40 subunit of interleukins-12/23 and is an effective and safe treatment for patients with Crohn’s disease (CD). An association between serum drug concentrations and therapeutic outcomes is required to justify Therapeutic Drug Monitoring (TDM). However, it is currently unknown if TDM is of additional value in UST treatment. We assessed the exposure-biochemical response relationship of UST trough concentrations at week, 8 in a prospective, real-world setting. Methods We performed a prospective study in CD patients with biochemical, radiologic or endoscopic disease activity in four academic centers in the Netherlands. All patients (n=90) received weight adjusted intravenously (IV) UST induction. First subcutaneous (SC), 90 mg induction dose was administered at week, 8 followed by a maintenance dose of, 90 mg SC every, 8 or, 12 weeks, at the discretion of the physician. Blood for drug levels were drawn at different time points during follow up (median follow up was, 52 weeks (IQR, 50–52)) with a median amount of, 2 measurements (IQR, 1–4) per patient. Plasma concentrations of UST were determined by means of a validated enzyme-linked immune assay. A population pharmacokinetic (PK) model was developed based on these measurements and the UST FDA review documents. Subsequently, the individual UST concentration time course during treatment were predicted using the developed model. Corticosteroid-free clinical remission (HBI ≤, 4) and biochemical remission (C-reactive protein (CRP) ≤5 mg/L or faecal calprotectin (FC) ≤, 250) were assessed at week, 12 and, 24. Quartile analysis and logistic regression was performed to analyse if UST concentration at week, 8 was associated with biochemical remission rates at week, 24. An independent cohort of, 34 patients was used to validate the primary outcomes. Results Basis characteristics of all patients are shown in table 1. Median estimated trough concentrations of UST were, 4.23 µg/mL (IQR, 2.79–5.83) and, 7.19 µg/mL (IQR, 3.30–10.67) at week, 8 in the primary and validation cohort respectively. Patients achieving biochemical remission at week, 12 and, 24 had statistically significantly higher UST levels at week, 8 (P&amp;lt;0.01) compared to patients without biochemical remission (fig, 1). Also, higher UST levels at week, 8 were associated with better biochemical remission rates at week, 12 and, 24 in quartile analysis and logistic regression (fig, 2,3). Associations of UST levels at week, 8 and biochemical remission at week, 12 and, 24 were confirmed in the validation cohort. No UST antibodies were detected. Conclusion In this real-world cohort of CD patients, ustekinumab levels of ≥5.9 µg/mL at week, 8 were associated with higher biochemical remission rates at week, 12 and, 24.

The Frequent Stressor and Mental Health Monitoring-Paradigm: A Proposal for the Operationalization and Measurement of Resilience and the Identification of Resilience Processes in Longitudinal Observational Studies.

Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing debate and of critical importance for the advancement of the field. One of the biggest challenges for implementing an outcome-based definition of resilience in longitudinal observational study designs lies in the fact that real-life adversity is usually unpredictable and that its substantial qualitative as well as temporal variability between subjects often precludes defining circumscribed time windows of inter-individually comparable stressor exposure relative to which the maintenance or recovery of mental health can be determined. To address this pertinent issue, we propose to frequently and regularly monitor stressor exposure (E) and mental health problems (P) throughout a study's observation period [Frequent Stressor and Mental Health Monitoring (FRESHMO)-paradigm]. On this basis, a subject's deviation at any single monitoring time point from the study sample's normative E–P relationship (the regression residual) can be used to calculate that subject's current mental health reactivity to stressor exposure (“stressor reactivity,” SR). The SR score takes into account the individual extent of experienced adversity and is comparable between and within subjects. Individual SR time courses across monitoring time points reflect intra-individual temporal variability in SR, where periods of under-reactivity (negative SR score) are associated with accumulation of fewer mental health problems than is normal for the sample. If FRESHMO is accompanied by regular measurement of potential resilience factors, temporal changes in resilience factors can be used to predict SR time courses. An increase in a resilience factor measurement explaining a lagged decrease in SR can then be considered to index a process of adaptation to stressor exposure that promotes a resilient outcome (an allostatic resilience process). This design principle allows resilience research to move beyond merely determining baseline predictors of resilience outcomes, which cannot inform about how individuals successfully adjust and adapt when confronted with adversity. Hence, FRESHMO plus regular resilience factor monitoring incorporates a dynamic-systems perspective into resilience research.

Modeling Time-Varying Random Objects and Dynamic Networks

Samples of dynamic or time-varying networks and other random object data such as time-varying probability distributions are increasingly encountered in modern data analysis. Common methods for time-varying data such as functional data analysis are infeasible when observations are time courses of networks or other complex non-Euclidean random objects that are elements of general metric spaces. In such spaces, only pairwise distances between the data objects are available and a strong limitation is that one cannot carry out arithmetic operations due to the lack of an algebraic structure. We combat this complexity by a generalized notion of mean trajectory taking values in the object space. For this, we adopt pointwise Fréchet means and then construct pointwise distance trajectories between the individual time courses and the estimated Fréchet mean trajectory, thus representing the time-varying objects and networks by functional data. Functional principal component analysis of these distance trajectories can reveal interesting features of dynamic networks and object time courses and is useful for downstream analysis. Our approach also makes it possible to study the empirical dynamics of time-varying objects, including dynamic regression to the mean or explosive behavior over time. We demonstrate desirable asymptotic properties of sample based estimators for suitable population targets under mild assumptions. The utility of the proposed methodology is illustrated with dynamic networks, time-varying distribution data and longitudinal growth data.

Pharmacokinetic-Pharmacodynamic Modelling of Systemic IL13 Blockade by Monoclonal Antibody Therapy: A Free Assay Disguised as Total.

A sequential pharmacokinetic (PK) and pharmacodynamic (PD) model was built with Nonlinear Mixed Effects Modelling based on data from a first-in-human trial of a novel biologic, MEDI7836. MEDI7836 is a human immunoglobulin G1 lambda (IgG1λ-YTE) monoclonal antibody, with an Fc modification to reduce metabolic clearance. MEDI7836 specifically binds to, and functionally neutralizes interleukin-13. Thirty-two healthy male adults were enrolled into a dose-escalation clinical trial. Four active doses were tested (30, 105, 300, and 600 mg) with 6 volunteers enrolled per cohort. Eight volunteers received placebo as control. Following single subcutaneous administration (SC), individual time courses of serum MEDI7836 concentrations, and the resulting serum IL13 modulation in vivo, were quantified. A binding pharmacokinetic-pharmacodynamic (PK-PD) indirect response model was built to characterize the exposure-driven modulation of the target over time by MEDI7836. While the validated bioanalytical assay specification quantified the level of free target (i.e., a free IL13 assay), emerging clinical data suggested dose-dependent increase in systemic IL13 concentration over time, indicative of a total IL13 assay. The target time course was modelled as a linear combination of free target and a percentage of the drug-target complex to fit the clinical data. This novel PK-PD modelling approach integrates independent knowledge about the assay characteristics to successfully elucidate apparently complex observations.

Postnatal Developmental Expression Profile Classifies the Indusium Griseum as a Distinct Subfield of the Hippocampal Formation.

The indusium griseum (IG) is a cortical structure overlying the corpus callosum along its anterior–posterior extent. It has been classified either as a vestige of the hippocampus or as an extension of the dentate gyrus via the fasciola cinerea, but its attribution to a specific hippocampal subregion is still under debate. To specify the identity of IG neurons more precisely, we investigated the spatiotemporal expression of calbindin, secretagogin, Necab2, PCP4, and Prox1 in the postnatal mouse IG, fasciola cinerea, and hippocampus. We identified the calcium-binding protein Necab2 as a first reliable marker for the IG and fasciola cinerea throughout postnatal development into adulthood. In contrast, calbindin, secretagogin, and PCP4 were expressed each with a different individual time course during maturation, and at no time point, IG or fasciola cinerea principal neurons expressed Prox1, a transcription factor known to define dentate granule cell fate. Concordantly, in a transgenic mouse line expressing enhanced green fluorescent protein (eGFP) in dentate granule cells, neurons of IG and fasciola cinerea were eGFP-negative. Our findings preclude that IG neurons represent dentate granule cells, as earlier hypothesized, and strongly support the view that the IG is an own hippocampal subfield composed of a distinct neuronal population.

Altered EEG Oscillatory Brain Networks During Music-Listening in Major Depression.

To examine the electrophysiological underpinnings of the functional networks involved in music listening, previous approaches based on spatial independent component analysis (ICA) have recently been used to ongoing electroencephalography (EEG) and magnetoencephalography (MEG). However, those studies focused on healthy subjects, and failed to examine the group-level comparisons during music listening. Here, we combined group-level spatial Fourier ICA with acoustic feature extraction, to enable group comparisons in frequency-specific brain networks of musical feature processing. It was then applied to healthy subjects and subjects with major depressive disorder (MDD). The music-induced oscillatory brain patterns were determined by permutation correlation analysis between individual time courses of Fourier-ICA components and musical features. We found that (1) three components, including a beta sensorimotor network, a beta auditory network and an alpha medial visual network, were involved in music processing among most healthy subjects; and that (2) one alpha lateral component located in the left angular gyrus was engaged in music perception in most individuals with MDD. The proposed method allowed the statistical group comparison, and we found that: (1) the alpha lateral component was activated more strongly in healthy subjects than in the MDD individuals, and that (2) the derived frequency-dependent networks of musical feature processing seemed to be altered in MDD participants compared to healthy subjects. The proposed pipeline appears to be valuable for studying disrupted brain oscillations in psychiatric disorders during naturalistic paradigms.

Actin-Membrane Release Initiates Cell Protrusions.

Despite the well-established role of actin polymerization as a driving mechanism for cell protrusion, upregulated actin polymerization alone does not initiate protrusions. Using a combination of theoretical modeling and quantitative live-cell imaging experiments, we show that local depletion of actin-membrane links is needed for protrusion initiation. Specifically, we show that the actin-membrane linker ezrin is depleted prior to protrusion onset and that perturbation of ezrin's affinity for actin modulates protrusion frequency and efficiency. We also show how actin-membrane release works in concert with actin polymerization, leading to a comprehensive model for actin-driven shape changes. Actin-membrane release plays a similar role in protrusions driven by intracellular pressure. Thus, our findings suggest that protrusion initiation might be governed by a universal regulatory mechanism, whereas the mechanism of force generation determines the shape and expansion properties of the protrusion.

Single Nucleotide Polymorphisms in Alzheimer's Disease Risk Genes Are Associated with Intrinsic Connectivity in Middle Age.

It is critical to identify individuals at risk for Alzheimer's disease (AD) earlier in the disease time course, such as middle age and preferably well prior to the onset of clinical symptoms, when intervention efforts may be more successful. Genome-wide association and candidate gene studies have identified single nucleotide polymorphisms (SNPs) in APOE, CLU, CR1, PICALM, and SORL1 that confer increased risk of AD. In the current study, we investigated the associations between SNPs in these genes and resting-state functional connectivity within the default mode network (DMN), frontoparietal network (FPN), and executive control network (ECN) in healthy, non-demented middle-aged adults (age 40 -60; N = 123; 74 females). Resting state networks of interest were identified through independent components analysis using a template-matching procedure and individual spatial maps and time courses were extracted using dual regression. Within the posterior DMN, functional connectivity was associated with CR1 rs1408077 and CLU rs9331888 polymorphisms (p's < 0.05). FPN connectivity was associated with CR1 rs1408077, CLU rs1136000, SORL1 rs641120, and SORL1 rs689021 (p's < 0.05). Functional connectivity within the ECN was associated with the CLU rs11136000 (p < 0.05). There were no APOE- or PICALM-related differences in any of the networks investigated (p's > 0.05). This is the first demonstration of the relationship between intrinsic network connectivity and AD risk alleles in CLU, CR1, and SORL1 in healthy, middle-aged adults. These SNPs should be considered in future investigations aimed at identifying potential preclinical biomarkers for AD.

Linking longitudinal and cross-sectional biomarker data to understand host-pathogen dynamics: Leptospirain California sea lions (Zalophus californianus) as a case study.

Confronted with the challenge of understanding population-level processes, disease ecologists and epidemiologists often simplify quantitative data into distinct physiological states (e.g. susceptible, exposed, infected, recovered). However, data defining these states often fall along a spectrum rather than into clear categories. Hence, the host-pathogen relationship is more accurately defined using quantitative data, often integrating multiple diagnostic measures, just as clinicians do to assess their patients. We use quantitative data on a major neglected tropical disease (Leptospira interrogans) in California sea lions (Zalophus californianus) to improve individual-level and population-level understanding of this Leptospira reservoir system. We create a “host-pathogen space” by mapping multiple biomarkers of infection (e.g. serum antibodies, pathogen DNA) and disease state (e.g. serum chemistry values) from 13 longitudinally sampled, severely ill individuals to characterize changes in these values through time. Data from these individuals describe a clear, unidirectional trajectory of disease and recovery within this host-pathogen space. Remarkably, this trajectory also captures the broad patterns in larger cross-sectional datasets of 1456 wild sea lions in all states of health but sampled only once. Our framework enables us to determine an individual’s location in their time-course since initial infection, and to visualize the full range of clinical states and antibody responses induced by pathogen exposure. We identify predictive relationships between biomarkers and outcomes such as survival and pathogen shedding, and use these to impute values for missing data, thus increasing the size of the useable dataset. Mapping the host-pathogen space using quantitative biomarker data enables more nuanced understanding of an individual’s time course of infection, duration of immunity, and probability of being infectious. Such maps also make efficient use of limited data for rare or poorly understood diseases, by providing a means to rapidly assess the range and extent of potential clinical and immunological profiles. These approaches yield benefits for clinicians needing to triage patients, prevent transmission, and assess immunity, and for disease ecologists or epidemiologists working to develop appropriate risk management strategies to reduce transmission risk on a population scale (e.g. model parameterization using more accurate estimates of duration of immunity and infectiousness) and to assess health impacts on a population scale.

Impact of granulocyte colony-stimulating factor on FOLFIRINOX-induced neutropenia prevention: A population pharmacokinetic/pharmacodynamic approach.

Granulocyte colony-stimulating factor (G-CSF) is frequently prescribed to prevent chemotherapy-induced neutropenia, but the administration schedule remains empirical in case of bimonthly chemotherapy such as FOLFIRINOX regimen. This pharmacokinetic/pharmacodynamic (PK/PD) study was performed to determine the effect of different G-CSF regimens on the incidence and duration of neutropenia following FOLFIRINOX administration in order to propose an optimal G-CSF dosing schedule. A population PK/PD model was developed to describe individual neutrophil time course from absolute neutrophil counts (ANC) obtained in 40 advanced cancer patients receiving FOLFIRINOX regimen. The structural model considered ANC dynamics, neutropenic effect of cytotoxics and the stimulating effect of G-CSF on neutrophils. Final model estimates were used to simulate different G-CSF dosing schedules for 1000 virtual subjects. The incidence and duration of neutropenia were then calculated for different G-CSF dosing schedules. The final model successfully described the myelosuppressive effect induced by the 3 cytotoxics for all patients. Simulations showed that pegfilgrastim administration reduced the risk of severe neutropenia by 22.9% for subjects with low ANC at the start of chemotherapy. Median duration in this group was also shortened by 3.1 days when compared to absence of G-CSF. Delayed G-CSF administration was responsible for higher incidence and longer duration of neutropenia compared to absence of administration. The PK/PD model well described our population's ANC data. Simulations showed that pegylated-G-CSF administration 24 hours after the end of chemotherapy seems to be the optimal schedule to reduce FOLFIRINOX-induced neutropenia. We also underline the potential negative effect of G-CSF maladministration.