The log multinomial regression model for nominal outcomes with more than two attributes

An estimate of the risk or prevalence ratio, adjusted for confounders, can be obtained from a log binomial model (binomial errors, log link) fitted to binary outcome data. We propose a modification of the log binomial model to obtain relative risk estimates for nominal outcomes with more than two attributes (the "log multinomial model"). Extensive data simulations were undertaken to compare the performance of the log multinomial model with that of an expanded data multinomial logistic regression method based on the approach proposed by Schouten et al. (1993) for binary data, and with that of separate fits of a Poisson regression model based on the approach proposed by Zou (2004) and Carter, Lipsitz and Tilley (2005) for binary data. Log multinomial regression resulted in "inadmissable" solutions (out-of-bounds probabilities) exceeding 50% in some data settings. Coefficient estimates by the alternative methods produced out-of-bounds probabilities for the log multinomial model in up to 27% of samples to which a log multinomial model had been successfully fitted. The log multinomial coefficient estimates generally had lesser relative bias and mean squared error than the alternative methods. The practical utility of the log multinomial regression model was demonstrated with a real data example. The log multinomial model offers a practical solution to the problem of obtaining adjusted estimates of the risk ratio in the multinomial setting, but must be used with some care and attention to detail.     

Age-Specific Mortality During the 1918 Influenza Pandemic: Unravelling the Mystery of High Young Adult Mortality

The worldwide spread of a novel influenza A (H1N1) virus in 2009 showed that influenza remains a significant health threat, even for individuals in the prime of life. This paper focuses on the unusually high young adult mortality observed during the Spanish flu pandemic of 1918. Using historical records from Canada and the U.S., we report a peak of mortality at the exact age of 28 during the pandemic and argue that this increased mortality resulted from an early life exposure to influenza during the previous Russian flu pandemic of 1889–90. We posit that in specific instances, development of immunological memory to an influenza virus strain in early life may lead to a dysregulated immune response to antigenically novel strains encountered in later life, thereby increasing the risk of death. Exposure during critical periods of development could also create holes in the T cell repertoire and impair fetal maturation in general, thereby increasing mortality from infectious diseases later in life. Knowledge of the age-pattern of susceptibility to mortality from influenza could improve crisis management during future influenza pandemics.

“The war is over – and I must go” Egon Schiele, 1890–1918.

     

Identifying the primary site of pathogenesis in amyotrophic lateral sclerosis – vulnerability of lower motor neurons to proximal excitotoxicity

There is a desperate need for targeted therapeutic interventions that slow the progression of amyotrophic lateral sclerosis (ALS). ALS is a disorder with heterogeneous onset, which then leads to common final pathways involving multiple neuronal compartments that span both the central and peripheral nervous system. It is believed that excitotoxic mechanisms might play an important role in motor neuron death in ALS. However, little is known about the mechanisms by which excitotoxicity might lead to the neuromuscular junction degeneration that characterizes ALS, or about the site at which this excitotoxic cascade is initiated. Using a novel compartmentalised model of site-specific excitotoxin exposure in lower motor neurons in vitro, we found that spinal motor neurons are vulnerable to somatodendritic, but not axonal, excitotoxin exposure. Thus, we developed a model of somatodendritic excitotoxicity in vivo using osmotic mini pumps in Thy-1-YFP mice. We demonstrated that in vivo cell body excitotoxin exposure leads to significant motor neuron death and neuromuscular junction (NMJ) retraction. Using confocal real-time live imaging of the gastrocnemius muscle, we found that NMJ remodelling preceded excitotoxin-induced NMJ degeneration. These findings suggest that excitotoxicity in the spinal cord of individuals with ALS might result in a die-forward mechanism of motor neuron death from the cell body outward, leading to initial distal plasticity, followed by subsequent pathology and degeneration.KEY WORDS: Motor neuron disease, Amyotrophic lateral sclerosis, Excitotoxicity, Lower motor neuron, Excitotoxin exposure     

Current advances in training orthopaedic patients to comply with partial weight-bearing instructions

Partial weight-bearing instructions are commonly given to orthopaedic patients and are an important part of post-injury and/or post-operative care. However, the ability of patients to comply with these instructions is poorly defined. Training methods for instructing these patients vary widely among institutions. Traditional methods of training include verbal instruction and use of a bathroom scale. Recent technological advances have created biofeedback devices capable of offering feedback to partial weight-bearing patients. Biofeedback devices have shown great promise in training patients to better comply with partial weight-bearing instructions. This review examines the background and significance of partial weight bearing and offers insights into current advances in training methods for partial weight-bearing patients.     

<Emphasis Type=Italic>ScreenMill</Emphasis>: A freely available software suite for growth measurement,analysis and visualization of high-throughput screen data

Background  

Many high-throughput genomic experiments, such as Synthetic Genetic Array and yeast two-hybrid, use colony growth on solid media as a screen metric. These experiments routinely generate over 100,000 data points, making data analysis a time consuming and painstaking process. Here we describe ScreenMill, a new software suite that automates image analysis and simplifies data review and analysis for high-throughput biological experiments.     

Development of cell surface saccharides on embryonic pancreatic cells

Using a battery of seven lectin-ferritin conjugates as probes for cell surface glycoconjugates, we have studied the pattern of plasmalemmal differentiation of cells in the embryonic rat pancreas from day 15 in utero to the early postpartum stage. Our results indicate that differentiation of plasmalemmal glycoconjugates on acinar, endocrine, and centroacinar cells is temporally correlated with development and is unique for each cell type, as indicated by lectin-ferritin binding. Specifically, (a) expression of adult cell surface saccharide phenotype can be detected on presumptive acinar cells as early as 15 d in utero, as indicated by soybean agglutinin binding, and precedes development of intracellular organelles characteristic of mature acinar cells; (b) maturation of the plasmalemma of acinar cells is reached after intracellular cytodifferentiation is completed, as indicated by appearance of Con A and fucoselectin binding sites only at day 19 of development; conversely, maturation of the endocrine cell plasmalemma is accompanied by "loss" (masking) of ricinus communis II agglutinin receptors; and (c) binding sites for fucose lectins and for soybean agglutinin are absent on endocrine and centroacinar cells at all stages examined. We conclude that acinar, centroacinar, and endocrine cells develop from a common progenitor cell(s) whose plasmalemmal carbohydrate composition resembles most closely that of the adult centroacinar cell. Finally, appearance of acinar lumina beginning at approximately 17 d in utero is accompanied by differenetiation of apical and basolateral plasmalemmal domains of epithelial cells, as indicated by enhanced binding of several lectin-ferritin conjugates to the apical plasmalemmal, a pattern that persists from this stage through adult life.     

Summary goodness‐of‐fit statistics for binary generalized linear models with noncanonical link functions

Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness‐of‐fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer–Lemeshow () and Pigeon–Heyse (J²) statistics can be applied directly. In a simulation study, , , and J² were used to evaluate the fit of probit, log–log, complementary log–log, and log models, all calculated with a common grouping method. The statistic consistently maintained Type I error rates, while those of and J² were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, had more power than or J².