Heterogeneity of Signaling Complex Nanostructure in T Cells Activated Via the T Cell Antigen Receptor.

Activation of the T cell antigen receptor (TCR) is a key step in initiating the adaptive immune response. Single-molecule localization techniques have been used to investigate the arrangement of proteins within the signaling complexes formed around activated TCRs, but a clear picture of nanoscale organization in stimulated T cells has not emerged. Here, we have improved the examination of T cell nanostructure by visualizing individual molecules of six different proteins in a single sample of activated Jurkat T cells using the multiplexed antibody-size limited direct stochastic optical reconstruction microscopy (madSTORM) technique.

Nonparametric estimation of recursive point processes with application to mumps in Pennsylvania.

The self-exciting Hawkes point process model (Hawkes, 1971) has been used to describe and forecast communicable diseases. A variant of the Hawkes model, called the recursive model, was proposed by Schoenberg et al. (2019) and has been shown to fit well to various epidemic disease datasets.

Point Process Models for the Spread of Coccidioidomycosis in California.

Coccidioidomycosis is an infectious disease of humans and other mammals that has seen a recent increase in occurrence in the southwestern United States, particularly in California. A rise in cases and risk to public health can serve as the impetus to apply newly developed methods that can quickly and accurately predict future caseloads. The recursive and Hawkes point process models with various triggering functions were fit to the data and their goodness of fit evaluated and compared.

A non-parametric Hawkes model of the spread of Ebola in west Africa.

Recently developed methods for the non-parametric estimation of Hawkes point process models facilitate their application for describing and forecasting the spread of epidemic diseases. We use data from the 2014 Ebola outbreak in West Africa to evaluate how well a simple Hawkes point process model can forecast the spread of Ebola virus in Guinea, Sierra Leone, and Liberia. For comparison, SEIR models that fit previously to the same data are evaluated using identical metrics.

Real-time predictions of the 2018-2019 Ebola virus disease outbreak in the Democratic Republic of the Congo using Hawkes point process models.

As of June 16, 2019, an Ebola virus disease (EVD) outbreak has led to 2136 reported cases in the northeastern region of the Democratic Republic of the Congo (DRC). As this outbreak continues to threaten the lives and livelihoods of people already suffering from civil strife and armed conflict, relatively simple mathematical models and their short-term predictions have the potential to inform Ebola response efforts in real time. We applied recently developed non-parametrically estimated Hawkes point processes to model the expected cumulative case count using daily case counts from May 3, 2018, to June 16, 2019, initially reported by the Ministry of Health of DRC and later confirmed in World Health Organization situation reports.

Placenta and appetite genes GDF15 and IGFBP7 are associated with hyperemesis gravidarum.

Hyperemesis gravidarum (HG), severe nausea and vomiting of pregnancy, occurs in 0.3-2% of pregnancies and is associated with maternal and fetal morbidity. The cause of HG remains unknown, but familial aggregation and results of twin studies suggest that understanding the genetic contribution is essential for comprehending the disease etiology.

Living with avian FLU--Persistence of the H5N1 highly pathogenic avian influenza virus in Egypt.

H5N1 highly pathogenic avian influenza virus (HPAIV) continues to cause mortality in poultry and threaten human health at a panzootic scale in Egypt since it was reported in 2006. While the early focus has been in Asia, recent evidence suggests that Egypt is an emerging epicenter for the disease. Despite control measures, epizootic transmission of the disease continues.

Neurodevelopmental delay in children exposed in utero to hyperemesis gravidarum.

Objective: The purpose of this study is to determine the frequency of emotional, behavioral, and learning disorders in children exposed in utero to hyperemesis gravidarum (HG) and to identify prognostic factors for these disorders.

Study Design: Neurodevelopmental outcomes of 312 children from 203 mothers with HG were compared to neurodevelopmental outcomes from 169 children from 89 unaffected mothers. Then the clinical profiles of patients with HG and a normal child outcome were compared to the clinical profiles of patients with HG and a child with neurodevelopmental delay to identify prognostic factors.

On measures of dissimilarity between point patterns: classification based on prototypes and multidimensional scaling.

This paper presents a collection of dissimilarity measures to describe and then classify spatial point patterns when multiple replicates of different types are available for analysis. In particular, we consider a range of distances including the spike-time distance and its variants, as well as cluster-based distances and dissimilarity measures based on classical statistical summaries of point patterns. We review and explore, in the form of a tutorial, their uses, and their pros and cons.

Psychiatric factors do not affect recurrence risk of hyperemesis gravidarum.

Aim: The aim of this study is to determine whether psychiatric symptoms affect recurrence risk of hyperemesis gravidarum (HG).

Methods: The study sample included 108 women with HG treated with i.v.

Antihistamines and other prognostic factors for adverse outcome in hyperemesis gravidarum.

Objective: The purpose of this study is to determine the frequency of adverse perinatal outcome in women with hyperemesis gravidarum and identify prognostic factors.

Study Design: This is a case-control study in which outcomes of first pregnancies were compared between 254 women with hyperemesis gravidarum treated with intravenous fluids and 308 controls. Prognostic factors were identified by comparing the clinical profile of patients with hyperemesis gravidarum with a normal and an adverse pregnancy outcome.

Change in paternity and recurrence of hyperemesis gravidarum.

Objective: To determine whether change in paternity changes recurrence risk of hyperemesis gravidarum (HG).

Study Design: Survey data on recurrence of HG was compared between cases who had a paternity change between pregnancies and cases who did not.

Results: The percentage of HG pregnancies in women with the same partner for all pregnancies was not significantly different from the percentage of HG pregnancies in women who changed partners for at least one pregnancy (78% vs 71%, p > 0.

Algorithms for computing spike time distance and point process prototypes with application to feline neuronal responses to acoustic stimuli.

The spike-time distance metric and the prototype of a collection of point patterns can be used to provide a metric description of repeated observations of point processes. Due to algorithmic limitations in computing spike-time distance, previous work in determining approximations of the prototype has largely been limited to single dimensional or small data sets. We develop new algorithms for each of these methods that are suitable for larger data sets.

Risk factors, treatments, and outcomes associated with prolonged hyperemesis gravidarum.

Objective: To identify factors associated with prolonged Hyperemesis Gravidarum (HG).

Study Design: About 395 women completed a survey regarding pre-existing conditions, treatments and outcomes. Responses were compared using two-sided t-tests or the F-test.

A statistical analysis of santa barbara ambulance response in 2006: performance under load.

Ambulance response times in Santa Barbara County for 2006 are analyzed using point process techniques, including kernel intensity estimates and K-functions. Clusters of calls result in significantly higher response times, and this effect is quantified. In particular, calls preceded by other calls within 20 km and within the previous hour are significantly more likely to result in violations.

Testing separability in spatial-temporal marked point processes.

Nonparametric tests for investigating the separability of a spatial-temporal marked point process are described and compared. It is shown that a Cramer-von Mises-type test is very powerful at detecting gradual departures from separability, and that a residual test based on randomly rescaling the process is powerful at detecting nonseparable clustering or inhibition of the marks. An application to Los Angeles County wildfire data is given, in which it is shown that the separability hypothesis is invalidated largely due to clustering of fires of similar sizes within periods of up to 3.