An age-dependent branching process model for the analysis of CFSE-labeling experiments

<p>Abstract</p> <p>Background</p> <p>Over the past decade, flow cytometric CFSE-labeling experiments have gained considerable popularity among experimentalists, especially immunologists and hematologists, for studying the processes of cell proliferation and cell death. Several mathematical models have been presented in the literature to describe cell kinetics during these experiments.</p> <p>Results</p> <p>We propose a multi-type age-dependent branching process to model the temporal development of populations of cells subject to division and death during CFSE-labeling experiments. We discuss practical implementation of the proposed model; we investigate a competing risk version of the process; and we identify the classes of cellular dependencies that may influence the expectation of the process and those that do not. An application is presented where we study the proliferation of human CD8+ T lymphocytes using our model and a competing risk branching process.</p> <p>Conclusions</p> <p>The proposed model offers a widely applicable approach to the analysis of CFSE-labeling experiments. The model fitted very well our experimental data. It provided reasonable estimates of cell kinetics parameters as well as meaningful insights into the processes of cell division and cell death. In contrast, the competing risk branching process could not describe the kinetics of CD8+ T cells. This suggested that the decision of cell division or cell death may be made early in the cell cycle if not in preceding generations. Also, we show that analyses based on the proposed model are robust with respect to cross-sectional dependencies and to dependencies between fates of linearly filiated cells.</p> <p>Reviewers</p> <p>This article was reviewed by Marek Kimmel, Wai-Yuan Tan and Peter Olofsson.</p

Predicting Acute Kidney Injury at Hospital Re-entry Using High-dimensional Electronic Health Record Data

Acute Kidney Injury (AKI), a sudden decline in kidney function, is associated with increased mortality, morbidity, length of stay, and hospital cost. Since AKI is sometimes preventable, there is great interest in prediction. Most existing studies consider all patients and therefore restrict to features available in the first hours of hospitalization. Here, the focus is instead on rehospitalized patients, a cohort in which rich longitudinal features from prior hospitalizations can be analyzed. Our objective is to provide a risk score directly at hospital re-entry. Gradient boosting, penalized logistic regression (with and without stability selection), and a recurrent neural network are trained on two years of adult inpatient EHR data (3,387 attributes for 34,505 patients who generated 90,013 training samples with 5,618 cases and 84,395 controls). Predictions are internally evaluated with 50 iterations of 5-fold grouped cross-validation with special emphasis on calibration, an analysis of which is performed at the patient as well as hospitalization level. Error is assessed with respect to diagnosis, race, age, gender, AKI identification method, and hospital utilization. In an additional experiment, the regularization penalty is severely increased to induce parsimony and interpretability. Predictors identified for rehospitalized patients are also reported with a special analysis of medications that might be modifiable risk factors. Insights from this study might be used to construct a predictive tool for AKI in rehospitalized patients. An accurate estimate of AKI risk at hospital entry might serve as a prior for an admitting provider or another predictive algorithm.Comment: In revisio

Re-engineering The Clinical Research Enterprise in Response to COVID-19: The Clinical Translational Science Award (CTSA) experience and proposed playbook for future pandemics

The 2020 COVID-19 pandemic has had a profound impact on the clinical research enterprises at the 60 Clinical and Translational Science Award (CTSA) Hubs throughout the nation. There was simultaneously a need to expand research to obtain crucial data about disease prognosis and therapy and enormous limitations on conducting research as localities and institutions limited travel and person-to-person contact. These imperatives resulted in major changes in the way research was conducted, including expediting Institutional Review Board review, shifting to remote interactions with participants, centralizing decision-making in prioritizing research protocols, establishing biobanks, adopting novel informatics platforms, and distributing study drugs in unconventional ways. National CTSA Steering Committee meetings provided an opportunity to share best practices and develop the idea of capturing the CTSA program experiences in a series of papers. Here we bring together the recommendations from those papers in a list of specific actions that research sites can take to strengthen operations and prepare for similar future public health emergencies. Most importantly, creative innovations developed in response to the COVID-19 pandemic deserve serious consideration for adoption as new standards, thus converting the painful trauma of the pandemic into “post-traumatic growth” that makes the clinical research enterprise stronger, more resilient, and more effective

Properties of Healthcare Teaming Networks as a Function of Network Construction Algorithms

Network models of healthcare systems can be used to examine how providers collaborate, communicate, refer patients to each other. Most healthcare service network models have been constructed from patient claims data, using billing claims to link patients with providers. The data sets can be quite large, making standard methods for network construction computationally challenging and thus requiring the use of alternate construction algorithms. While these alternate methods have seen increasing use in generating healthcare networks, there is little to no literature comparing the differences in the structural properties of the generated networks. To address this issue, we compared the properties of healthcare networks constructed using different algorithms and the 2013 Medicare Part B outpatient claims data. Three different algorithms were compared: binning, sliding frame, and trace-route. Unipartite networks linking either providers or healthcare organizations by shared patients were built using each method. We found that each algorithm produced networks with substantially different topological properties. Provider networks adhered to a power law, and organization networks to a power law with exponential cutoff. Censoring networks to exclude edges with less than 11 shared patients, a common de-identification practice for healthcare network data, markedly reduced edge numbers and greatly altered measures of vertex prominence such as the betweenness centrality. We identified patterns in the distance patients travel between network providers, and most strikingly between providers in the Northeast United States and Florida. We conclude that the choice of network construction algorithm is critical for healthcare network analysis, and discuss the implications for selecting the algorithm best suited to the type of analysis to be performed.Comment: With links to comprehensive, high resolution figures and networks via figshare.co

The indirect action of ions upon amino acid transport system L in the S37 cell

The uptake into S37 ascites cells of an L-system specific analog, 2-amino-bicyclo-(3,2,1)-octanecarboxylic acid (ABOCA), wasinconsistently inhibited by deletion of sodium ion from the incubation medium. We note that there have been conflicting reports from various other laboratories as to the effect of sodium ion on the transport of L-system specific analogs. The uptake of labeled exo-2-aminobicyclo-(2.2,1)-heptane-2-carboxylic acid (BCH) wasalso diminished by the removal of sodium from the medium. The Km values for these substrates were increased and [nu]max values decreased as the sodium ion concentration was decreased or abolished. Transport behavior was also found to be affected by varying the medium potassium ion concentration with valinomycin present. The sodium effect was abolished by preincubation with cyanide and deoxyglucose. The results suggest an indirect effect of sodium ion upon transport system L: system L is energetically supported by a membrane potential.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24714/1/0000136.pd

Impaired HA-specific T follicular helper cell and antibody responses to influenza vaccination are linked to inflammation in humans.

Funder: National Institute for Health Research (NIHR)Antibody production following vaccination can provide protective immunity to subsequent infection by pathogens such as influenza viruses. However, circumstances where antibody formation is impaired after vaccination, such as in older people, require us to better understand the cellular and molecular mechanisms that underpin successful vaccination in order to improve vaccine design for at-risk groups. Here, by studying the breadth of anti-haemagglutinin (HA) IgG, serum cytokines, and B and T cell responses by flow cytometry before and after influenza vaccination, we show that formation of circulating T follicular helper (cTfh) cells was associated with high-titre antibody responses. Using Major Histocompatability Complex (MHC) class II tetramers, we demonstrate that HA-specific cTfh cells can derive from pre-existing memory CD4+ T cells and have a diverse T cell receptor (TCR) repertoire. In older people, the differentiation of HA-specific cells into cTfh cells was impaired. This age-dependent defect in cTfh cell formation was not due to a contraction of the TCR repertoire, but rather was linked with an increased inflammatory gene signature in cTfh cells. Together, this suggests that strategies that temporarily dampen inflammation at the time of vaccination may be a viable strategy to boost optimal antibody generation upon immunisation of older people

Hematopoietic Cell Types: Prototype for a Revised Cell Ontology

The Cell Ontology (CL) is an OBO Foundry candidate ontology intended for the representation of cell types from all of biology. A recent workshop sponsored by NIAID on hematopoietic cell types in the CL addressed issues of both the content and structure of the CL. The section of the ontology dealing with hematopoietic cells was extensively revised, and plans were made for restructuring these cell type terms as cross-products with logical definitions based on relationships to external ontologies, such as the Protein Ontology and the Gene Ontology. The improvements to the CL in this area represent a paradigm for the future revision of the whole of the CL