A Model to Predict 24-Hour Urinary Creatinine Level Using Repeated Measurements

Creatinine is a metabolic waste product, removed from the blood by the kidneys, and excreted in the urine. The measurement of creatinine is used in the assessment and monitoring of many medical conditions as well as in the determination or adjustment of absorbed dosage of pesticides. Earlier models to predict 24-hour urinary creatinine used ordinary least squares regression and assumed that the subjects\u27 observations were uncorrelated. However, many of these studies had repeated creatinine measurements for each of their subjects. Repeated measures on the same subject frequently are correlated. Using data from the NIOSH-CDC Pesticide Dose Monitoring in Turf Applicators study, this thesis project built a model to predict 24-hour urinary creatinine using the Mixed Model methodology. A covariance structure, that permitted multiple observations for any one individual to be correlated, was identified and utilized. The predictive capabilities of this model were then compared to the earlier models investigated

SDE-driven modeling of phenotypically heterogeneous tumors: The influence of cancer cell stemness

We deduce cell population models describing the evolution of a tumor (possibly interacting with its environment of healthy cells) with the aid of differential equations. Thereby, different subpopulations of cancer cells allow accounting for the tumor heterogeneity. In our settings these include cancer stem cells known to be less sensitive to treatment and differentiated cancer cells having a higher sensitivity towards chemo- and radiotherapy. Our approach relies on stochastic differential equations in order to account for randomness in the system, arising e.g., due to the therapy-induced decreasing number of clonogens, which renders a pure deterministic model arguable. The equations are deduced relying on transition probabilities characterizing innovations of the two cancer cell subpopulations, and similarly extended to also account for the evolution of normal tissue. Several therapy approaches are introduced and compared by way of tumor control probability (TCP) and uncomplicated tumor control probability (UTCP). A PDE approach allows to assess the evolution of tumor and normal tissue with respect to time and to cell population densities which can vary continuously in a given set of states. Analytical approximations of solutions to the obtained PDE system are provided as well.RTI2018- 093416-B-I0

Temporal excitation patterns on the cerebral cortex as a result of migraine modeling

The complex, highly individual, geometry of the cerebral cortex in humans presents a major challenge in studying the spreading of spontaneous neuronal activity. Recent computational advances [1] allow to simulate the propagation of depolarization waves on the macroscale and for individual geometries, reconstructed from accurate medical imaging as MRI, with high levels of detail. In this paper we take advantage of such technique to study the temporal excitation patterns that follow the passage of a depolarization wave on the cerebral cortex.This work was supported by the Bizkaia Talent and European Commission through COFUND under the grant BRAhMS – Brain Aura Mathematical Simulation– (AYD-000- 285), and also by the Basque Government through the BERC 2014-2017 program, and by the Spanish Ministry of Economics and Competitiveness MINECO: BCAM Severo Ochoa excellence accreditation SEV-2013-0323. JMC acknowledges financial support from Ikerbasque: The Basque Foundation for Science and Euskampus at UPV/EHU

Geometry shapes propagation: Assessing the presence and absence of cortical symmetries through a computational model of cortical spreading depression

Cortical spreading depression (CSD), a depolarization wave which originates in the visual cortex and travels toward the frontal lobe, has been suggested to be one neural correlate of aura migraine. To the date, little is known about the mechanisms which can trigger or stop aura migraine. Here, to shed some light on this problem and, under the hypothesis that CSD might mediate aura migraine, we aim to study different aspects favoring or disfavoring the propagation of CSD. In particular, by using a computational neuronal model distributed throughout a realistic cortical mesh, we study the role that the geometry has in shaping CSD. Our results are two-fold: first, we found significant differences in the propagation traveling patterns of CSD, both intra and inter-hemispherically, revealing important asymmetries in the propagation profile. Second, we developed methods able to identify brain regions featuring a peculiar behavior during CSD propagation. Our study reveals dynamical aspects of CSD, which, if applied to subject-specific cortical geometry, might shed some light on how to differentiate between healthy subjects and those suffering migraine

Patient-specific computational modeling of Cortical Spreading Depression via Diffusion Tensor Imaging

Cortical Spreading Depression (CSD), a depolarization wave originat- ing in the visual cortex and traveling towards the frontal lobe, is com- monly accepted as a correlate of migraine visual aura. As of today, little is known about the mechanisms that can trigger or stop such phenomenon. However, the complex and highly individual characteristics of the brain cortex suggest that the geometry might have a significant impact in sup- porting or contrasting the propagation of CSD. Accurate patient-specific computational models are fundamental to cope with the high variability in cortical geometries among individuals, but also with the conduction anisotropy induced in a given cortex by the complex neuronal organisa- tion in the grey matter. In this paper we integrate a distributed model for extracellular potassium concentration with patient-specific diffusivity tensors derived locally from Diffusion Tensor Imaging data.This work was supported by the Bizkaia Talent and European Commission through COFUND under the grant BRAhMS - Brain Aura Mathematical Sim- ulation (AYD-000-285), by the Basque Government through the BERC 2014- 2017 program, and by the Spanish Ministry of Economics and Competitiveness MINECO through the BCAM Severo Ochoa excellence accreditation SEV-2013- 0323 and the Spanish "Plan Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad" under Grant BELEMET - Brain ELEctro- METabolic modeling and numerical approximation (MTM2015-69992-R). JMC acknowledges financial support from Ikerbasque: The Basque Foundation for Science and Euskampus at UPV/EHU

Clinical correlates of mathematical modeling of cortical spreading depression: Single‐cases study

Introduction: Considerable connections between migraine with aura and cortical spreading depression (CSD), a depolarization wave originating in the visual cortex and traveling toward the frontal lobe, lead to the hypothesis that CSD is underlying migraine aura. The highly individual and complex characteristics of the brain cor‐ tex suggest that the geometry might impact the propagation of cortical spreading depression. Methods: In a single‐case study, we simulated the CSD propagation for five migraine with aura patients, matching their symptoms during a migraine attack to the CSD wavefront propagation. This CSD wavefront was simulated on a patient‐specific tri‐ angulated cortical mesh obtained from individual MRI imaging and personalized dif‐ fusivity tensors derived locally from diffusion tensor imaging data. Results: The CSD wave propagation was simulated on both hemispheres, despite in all but one patient the symptoms were attributable to one hemisphere. The CSD wave diffused with a large wavefront toward somatosensory and prefrontal regions, devoted to pain processing. Discussion: This case‐control study suggests that the cortical geometry may con‐ tribute to the modality of CSD evolution and partly to clinical expression of aura symptoms. The simulated CSD is a large and diffuse phenomenon, possibly capa‐ ble to activate trigeminal nociceptors and to involve cortical areas devoted to pain processing

Absence of Epstein-Barr virus DNA in anti-citrullinated protein antibody-expressing B cells of patients with rheumatoid arthritis

Objective: Rheumatoid arthritis (RA) is characterized by the presence of disease-specific autoreactive B cell responses, in particular those generating anti-citrullinated protein antibodies (ACPA). For many years, Epstein-Barr virus (EBV) has been implicated in disease pathogenesis, possibly by facilitating the development and persistence of autoreactive B cells. To test this hypothesis, the presence of EBV episomes in ACPA-expressing B cells was analyzed.Methods: ACPA-expressing B cells derived from peripheral blood (PB) of seven EBV-seropositive RA patients, and synovial fluid (SF) of one additional EBV-seropositive RA patient, were isolated by flow cytometry. PB cells were expanded for 11-12 days, after which supernatant was harvested and analyzed for cyclic citrullinated-peptide (CCP)2 reactivity. SF cells were isolated directly in a lysis buffer. DNA was isolated and qPCR reactions were performed to determine the EBV status of the cells. EBV-immortalized B cell lymphoblastoid-cell lines (EBV blasts) served as standardized controls.Results: Two hundred ninety-six PB and 60 SF ACPA-expressing B cells were isolated and divided over 16 and 3 pools containing 10-20 cells, respectively. Supernatants of all 16 cultured PB pools contained CCP2-Ig. DNA of all pools was used for qPCR analysis. While EBV-blast analysis showed sensitivity to detect EBV DNA in single B cells, no EBV DNA was detected in any of the ACPA-expressing B cell pools.Conclusion: ACPA-expressing B cells are not enriched for EBV-DNA-containing clones. These results do not support the hypothesis that EBV infection of autoreactive B cells causes or maintains autoreactive B cell populations in RA. Instead, other mechanisms might explain the association between positive EBV serology and RA.Pathophysiology and treatment of rheumatic disease

Endogenous type II cGMP-dependent protein kinase exists as a dimer in membranes and can Be functionally distinguished from the type I isoforms

In mammalian tissues two types of cGMP-dependent protein kinase (cGK) have been identified. In contrast to the dimeric cGK I, cGK II purified from pig intestine was shown previously to behave as a monomer. However, recombinant rat cGK II was found to have hydrodynamic parameters indicative of a homodimer. Chemical cross-linking studies showed that pig cGK II in intestinal membranes h

Addressing the key issue: Antigen-specific targeting of B cells in autoimmune diseases

Autoimmune diseases are heterogeneous pathologies characterized by a breakdown of immunological tolerance to self, resulting in a chronic and aberrant immune response to self-antigens. The scope and extent of affected tissues can vary greatly per autoimmune disease and can involve multiple organs and tissue types. The patho-genesis of most autoimmune diseases remains unknown but it is widely accepted that a complex interplay be-tween (autoreactive) B and T cells in the context of breached immunological tolerance drives autoimmune pathology. The importance of B cells in autoimmune disease is exemplified by the successful use of B cell tar-geting therapies in the clinic. For example, Rituximab, a depleting anti-CD20 antibody, has shown favorable results in reducing the signs and symptoms of multiple autoimmune diseases, including Rheumatoid Arthritis, Anti-Neutrophil Cytoplasmic Antibody associated vasculitis and Multiple Sclerosis. However, Rituximab depletes the entire B cell repertoire, leaving patients susceptible to (latent) infections. Therefore, multiple ways to target autoreactive cells in an antigen-specific manner are currently under investigation. In this review, we will lay out the current state of antigen-specific B cell inhibiting or depleting therapies in the context of autoimmune diseases.NWONWO-024.002.009Pathophysiology and treatment of rheumatic disease