Maternal-Fetal Immune Tolerance, Block by Block

How difficult is to go from egg to implanted embryo? The evolution of placentation in eutherian mammals created enormous challenges, in particular to the maternal immune system, as the fetus expresses paternal antigens that are capable of triggering immune rejection. Samstein et al. reveal a role for inducible regulatory T cells in the enforcement of maternal-fetal immune tolerance

New measurement paradigms

This collection of New Measurement Paradigms papers represents a snapshot of the variety of measurement methods in use at the time of writing across several projects funded by the National Science Foundation (US) through its REESE and DR K–12 programs. All of the projects are developing and testing intelligent learning environments that seek to carefully measure and promote student learning, and the purpose of this collection of papers is to describe and illustrate the use of several measurement methods employed to achieve this. The papers are deliberately short because they are designed to introduce the methods in use and not to be a textbook chapter on each method. The New Measurement Paradigms collection is designed to serve as a reference point for researchers who are working in projects that are creating e-learning environments in which there is a need to make judgments about students’ levels of knowledge and skills, or for those interested in this but who have not yet delved into these methods

Towards Scalable Assessment of Performance-Based Skills: Generalizing a Detector of Systematic Science Inquiry to a Simulation with a Complex Structure

Abstract. There are well-acknowledged challenges to scaling computerized performance-based assessments. One such challenge is reliably and validly identifying ill-defined skills. We describe an approach that leverages a data mining framework to build and validate a detector that evaluates an ill-defined inquiry process skill, designing controlled experiments. The detector was originally built and validated for use with physical science simulations that have a simpler, linear causal structure. In this paper, we show that the detector can be used to identify demonstration of skill within a life science simulation on Ecosystems that has a complex underlying causal structure. The detector is evaluated in three ways: 1) identifying skill demonstration for a new student cohort, 2) handling the variability in how students conduct experiments, and 3) using it to determine when students are off-track before they finish collecting data

Discovery with Models: A Case Study on Carelessness in Computer-based Science Inquiry

In recent years, an increasing number of analyses in Learning Analytics and Educational Data Mining (EDM) have adopted a "Discovery with Models" approach, where an existing model is used as a key component in a new EDM/analytics analysis. This article presents a theoretical discussion on the emergence of discovery with models, its potential to enhance research on learning and learners, and key lessons learned in how discovery with models can be conducted validly and effectively. We illustrate these issues through discussion of a case study where discovery with models was used to investigate a form of disengaged behavior, i.e., carelessness, in the context of middle school computer-based science inquiry. This behavior has been acknowledged as a problem in education as early as the 1920s. With the increasing use of high-stakes testing, the cost of student carelessness can be higher. For instance, within computer-based learning environments careless errors can result in reduced educational effectiveness, with students continuing to receive material they have already mastered. Despite the importance of this problem, it has received minimal research attention, in part due to difficulties in operationalizing carelessness as a construct. Building from theory on carelessness and a Bayesian framework for knowledge modeling, we use machine-learned detectors to predict carelessness within authentic use of a computer-based learning environment. We then use a discovery with models approach to link these validated carelessness measures to survey data, to study the correlations between the prevalence of carelessness and student goal orientation. The second construct, carelessness, refers to incorrect answers given by a student on material that the student should be able to answer correctly Rodriguez-Fornells & Maydeu-Olivares, 2000). The application of discovery with models involves two main phases. First, a model of a construct is developed using machine learning or knowledge engineering techniques, and is then validated, as discussed below. Second, this validated model is applied to data and used as a component in another analysis: For example, for identifying outliers through model predictions; examining which variables best predict the modeled construct; finding relationships between the construct and other variables using correlations, predictions, associations rules, causal relationships or other methods; or studying the contexts where the construct occurs, including its prevalence across domains, systems, or populations. For example, in One essential question to pose prior to a discovery with model analysis is whether the model adopted is valid, both overall, and for the specific situation in which it is being used. Ideally, a model should be validated using an approach such as cross-validation, where the model is repeatedly trained on one portion of the data and tested on a different portion, with model predictions compared to appropriate external measures, for example assessments made by humans with acceptably high inter-rater reliability, such as field observations of student behavior for gaming the system (cf. Even after validating in this fashion, validity should be re-considered if the model is used for a substantially different population or context than was used when developing the model.. An alternative approach is to use a simpler knowledge-engineered definition, rationally deriving a function/rule that is then applied to the data. In this case, the model can be inferred to have face validity. However, knowledge-engineered models often DISCOVERY WITH MODELS: A CASE STUDY ON CARELESSNESS 6 produce different results than machine learning-based models, for example in the case of gaming the system. Research studying whether student or content is a better predictor of gaming the system identified different results, depending on which model was applied (cf. Baker, 2007a

Exploring emergent properties in cellular homeostasis using OnGuard to model K+ and other ion transport in guard cells

It is widely recognized that the nature and characteristics of transport across eukaryotic membranes are so complex as to defy intuitive understanding. In these circumstances, quantitative mathematical modeling is an essential tool, both to integrate detailed knowledge of individual transporters and to extract the properties emergent from their interactions. As the first, fully integrated and quantitative modeling environment for the study of ion transport dynamics in a plant cell, OnGuard offers a unique tool for exploring homeostatic properties emerging from the interactions of ion transport, both at the plasma membrane and tonoplast in the guard cell. OnGuard has already yielded detail sufficient to guide phenotypic and mutational studies, and it represents a key step toward ‘reverse engineering’ of stomatal guard cell physiology, based on rational design and testing in simulation, to improve water use efficiency and carbon assimilation. Its construction from the HoTSig libraries enables translation of the software to other cell types, including growing root hairs and pollen. The problems inherent to transport are nonetheless challenging, and are compounded for those unfamiliar with conceptual ‘mindset’ of the modeler. Here we set out guidelines for the use of OnGuard and outline a standardized approach that will enable users to advance quickly to its application both in the classroom and laboratory. We also highlight the uncanny and emergent property of OnGuard models to reproduce the ‘communication’ evident between the plasma membrane and tonoplast of the guard cell

Spleen plays a major role in DLL4-driven acute T-cell lymphoblastic leukemia.

The Notch pathway is highly active in almost all patients with T-cell acute lymphoblastic leukemia (T-ALL), but the implication of Notch ligands in T-ALL remains underexplored. Methods: We used a genetic mouse model of Notch ligand delta like 4 (DLL4)-driven T-ALL and performed thymectomies and splenectomies in those animals. We also used several patient-derived T-ALL (PDTALL) models, including one with DLL4 expression on the membrane and we treated PDTALL cells in vitro and in vivo with demcizumab, a blocking antibody against human DLL4 currently being tested in clinical trials in patients with solid cancer. Results: We show that surgical removal of the spleen abrogated T-ALL development in our preclinical DLL4-driven T-ALL mouse model. Mechanistically, we found that the spleen, and not the thymus, promoted the accumulation of circulating CD4+CD8+ T cells before T-ALL onset, suggesting that DLL4-driven T-ALL derives from these cells. Then, we identified a small subset of T-ALL patients showing higher levels of DLL4 expression. Moreover, in mice xenografted with a DLL4-positive PDTALL model, treatment with demcizumab had the same therapeutic effect as global Notch pathway inhibition using the potent γ-secretase inhibitor dibenzazepine. This result demonstrates that, in this PDTALL model, Notch pathway activity depends on DLL4 signaling, thus validating our preclinical mouse model. Conclusion: DLL4 expression in human leukemic cells can be a source of Notch activity in T-ALL, and the spleen plays a major role in a genetic mouse model of DLL4-driven T-ALL.We thank Drs. Susan Schwab, Dan Littman, Sherif Ibrahim, Angel Pellicer, Susanne Tranguch and Adolfo Ferrando for helpful discussions and/or critically comments on the manuscript. Elisabetta Andermarcher professionally edited the manuscript. We are indebted to Dr. M. Yan (Genentech) for the anti-DLL4 antibody for cytometry. We are also in debt with Christopher Murriel from Oncomed who provided the therapeutic murine anti-DLL4 antibody and demcizumab (anti-human DLL4 antibody). We thank the NYU School of Medicine Flow Cytometry Core facility, particularly Dr. Peter Lopez, Keith Kobylarz and Michael Gregory, and also the NYU School of Medicine Confocal imaging facility, particularly Yan Deng. We also thank Henry Alexandre Michaud for his great help with the FACS analysis of PDTALL cells. We thank Nelly Pirot and the rest of members of the IRCM IHC platform for their fantastic work. M.M. is supported by a contract from Fondation ARC. The NYU Cancer Institute Center Support Grant partially funded this core through grant NIH/NCI 5 P30CA16087-31. Work in JJL's laboratory is supported by the NIH/NIAID, National Multiple Sclerosis Society, and the Helmsley Charitable Trust. Work in AM's laboratory is supported by the Fondation ARC (PJA 20131200405), the European Commission (CIG631431), the Institute de Cancer de Montpellier Fondation, and the Institut National du Cancer (INCa_9257 and INCa-DGOS-Inserm 12553).S

Distribution of immune cells in head and neck cancer: CD8+ T-cells and CD20+ B-cells in metastatic lymph nodes are associated with favourable outcome in patients with oro- and hypopharyngeal carcinoma

<p>Abstract</p> <p>Background</p> <p>Tumour infiltrating lymphocytes (TIL) are generally considered to represent a host immune response directed against tumour antigens. TIL are also increasingly recognised as possible prognostic parameters. However, the effects observed are variable indicating that results cannot be extrapolated from type of tumour to another. Moreover, it has been suggested that primary solid tumours may be ignored by the immune system and that a meaningful immune response is only mounted in regional lymph nodes.</p> <p>Methods</p> <p>We have examined the local distribution of immune cells in tumour-related compartments in head and neck squamous cell carcinomas (HNSCC). In a second step, the prognostic impact of these cells on disease-free survival (DFS) was analysed. A total of 198 tissue cores from 33 patients were evaluated using tissue mircroarray technique and immunohistochemistry. Tumour-infiltrating immune cells were identified using antibodies specific for CD3, CD8, GranzymeB, FoxP3, CD20 and CD68 and quantified using an image analysis system.</p> <p>Results</p> <p>We demonstrate a relative expansion of FoxP3⁺regulatory T-cells (Treg) and of cytotoxic T-cells among tumour infitrating T-cells. We also show that intratumoural CD20⁺B-cells are significantly more frequent in metastatic deposits than in primary tumours. Furthermore, we observed a reduced number of peritumoural CD8⁺T-cells in metastatic lymph nodes as compared to univolved regional nodes suggesting a local down-modulation of cellular immunity. All other immune cells did not show significant alterations in distribution. We did not observe an association of tumour infiltrating immune cells at the primary site with outcome. However, increased numbers of intraepithelial CD8⁺TIL in metastatic tumours as well as large numbers of peritumoural B-cells in lymph node metastases were associated with favourable outcome. Unexpectedly, no effect on patient outcome was observed for Treg in any compartment.</p> <p>Conclusion</p> <p>Our results suggest that alterations in lymphocyte distribution in regional lymph nodes rather than at the primary tumour site may be relevant for patient prognosis. Moreover, we demonstrate that in addition to cellular immunity humoral immune responses may be clinically relevant in anti-tumour immunity.</p

Stromal fibroblasts support dendritic cells to maintain IL-23/Th17 responses after exposure to ionizing radiation

Dendritic cell function is modulated by stromal cells, including fibroblasts. Although poorly understood, the signals delivered through this crosstalk substantially alter dendritic cell biology. This is well illustrated with release of TNF-0/IL-113 from activated dendritic cells, promoting PGE2 secretion from stromal fibroblasts. This instructs dendritic cells to up-regulate IL-23, a key Th17-polarizing cytokine. We previously showed that ionizing radiation inhibited IL-23 production by human dendritic cells in vitro. In the present study, we investigated the hypothesis that dendritic cell-fibroblast crosstalk over¬comes the suppressive effect of ionizing radiation to support appropriately polarized Th17 responses. Radia¬tion (1–6 Gy) markedly suppressed IL-23 secretion by activated dendritic cells (P < 0.0001) without adversely impacting their viability and consequently, inhibited the generation of Th17 responses. Cytokine suppression by ionizing radiation was selective, as there was no effect on IL-10, -6, -10, and -27 or TNF-a and only a modest (11%) decrease in IL-12p70 secretion. Coculture with fibroblasts augmented IL-23 secretion by irradiated dendritic cells and increased Th17 responses. Impor¬tantly, in contrast to dendritic cells, irradiated fibroblasts maintained their capacity to respond to TNF-0/IL-10 and produce PGE2, thus providing the key intermediary signals for successful dendritic cell-fibroblasts crosstalk. In summary, stromal fibroblasts support Th17-polarizing cytokine production by dendritic cells that would other¬wise be suppressed in an irradiated microenvironment. This has potential ramifications for understanding the immune response to local radiotherapy. These findings underscore the need to account for the impact of microenvironmental factors, including stromal cells, in understanding the control of immunity. J. Leukoc. Biol. 100: 000–000; 2016

Prognostic significance of tumor-infiltrating lymphocytes in ductal carcinoma in situ of the breast

Tumor-infiltrating lymphocytes (TILs) provide prognostic value in invasive breast cancer and guidelines for their assessment have been published. This study aims to evaluate: (a) methods of TILs assessment, and (b) their prognostic significance in breast ductal carcinoma in situ (DCIS). Hematoxylin and eosin sections from two clinically annotated DCIS cohorts; a training set (n = 150 pure DCIS) and a validation set (n = 666 comprising 534 pure DCIS and 132 cases wherein DCIS and invasive breast carcinoma were co-existent) were assessed. Seven different scoring methods were applied to the training set to identify the most optimal reproducible method associated with strongest prognostic value. Among different methods, TILs touching ducts' basement membrane or away from it by one lymphocyte cell thickness provided the strongest significant association with outcome and highest concordance rate [inter-cluster correlation coefficient = 0.95]. Assessment of periductal TILs at increasing distances from DCIS (0.2 , 0.5 , and 1 mm) as well as percent of stromal TILs were practically challenging and showed lower concordance rates than touching TILs. TILs hotspots and lymphoid follicles did not show prognostic significance. Within the pure DCIS validation set, dense TILs were associated with younger age, symptomatic presentation, larger size, higher nuclear grade, comedo necrosis and estrogen receptor negativity as well as shorter recurrence-free interval (p = 0.002). In multivariate survival analysis, dense TILs were independent predictor of shorter recurrence-free interval (p = 0.002) in patients treated with breast conservation. DCIS associated with invasive carcinoma showed denser TILs than pure DCIS (p = 9.0 × 10-13). Dense TILs is an independent prognostic variable in DCIS. Touching TILs provides a reproducible method for their assessment that can potentially be used to guide management