A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy

We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing ‘slide-level’ diagnosis by using individual ‘cell-level’ diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform.     

Selection for High Oridonin Yield in the Chinese Medicinal Plant Isodon (Lamiaceae) Using a Combined Phylogenetics and Population Genetics Approach

Oridonin is a diterpenoid with anti-cancer activity that occurs in the Chinese medicinal plant Isodon rubescens and some related species. While the bioactivity of oridonin has been well studied, the extent of natural variation in the production of this compound is poorly known. This study characterizes natural variation in oridonin production in order to guide selection of populations of Isodon with highest oridonin yield. Different populations of I. rubescens and related species were collected in China, and their offspring were grown in a greenhouse. Samples were examined for oridonin content, genotyped using 11 microsatellites, and representatives were sequenced for three phylogenetic markers (ITS, rps16, trnL-trnF). Oridonin production was mapped on a molecular phylogeny of the genus Isodon using samples from each population as well as previously published Genbank sequences. Oridonin has been reported in 12 out of 74 species of Isodon examined for diterpenoids, and the phylogeny indicates that oridonin production has arisen at least three times in the genus. Oridonin production was surprisingly consistent between wild-collected parents and greenhouse-grown offspring, despite evidence of gene flow between oridonin-producing and non-producing populations of Isodon. Additionally, microsatellite genetic distance between individuals was significantly correlated with chemical distance in both parents and offspring. Neither heritability nor correlation with genetic distance were significant when the comparison was restricted to only populations of I. rubescens, but this result should be corroborated using additional samples. Based on these results, future screening of Isodon populations for oridonin yield should initially prioritize a broad survey of all species known to produce oridonin, rather than focusing on multiple populations of one species, such as I. rubescens. Of the samples examined here, I. rubescens or I. japonicus from Henan province would provide the best source of oridonin.     

Analysis of a common inheritable idiotype in IgA-deficient sera using monoclonal antibodies

In these studies we describe the production of three mAb raised to an idiotype on an IgG anticasein antibody isolated from the serum of one IgA-deficient blood donor. These are IgM kappa and block the binding of casein Ag to anticasein antibody. Sera of unrelated IgA-deficient donors were tested for the presence of the idiotype; 15 of 56 IgA-deficient sera (25%) contain the anticasein idiotype, whereas 1 of 45 normal sera was positive. Anticasein antibodies as a whole were predominantly of the IgG1 and IgG3 subclass; idiotype-positive anticaseins are predominantly of the IgG1 subclass. For IgA-deficient donors, the relative amount of idiotype-positive anticasein antibody was correlated with the level of anticasein present in the serum. Studies were done to investigate the potential inheritance of the idiotype in families; in three of four families the idiotype was inherited in an apparent autosomal dominant pattern. Our data show that a common cross-reactive idiotype can be detected in the sera of IgA-deficient individuals and their family members. This suggests that V region markers may be conserved in this humoral immunodeficiency disease.     

Predicting Metabolic Pathways of Small Molecules and Enzymes Based on Interaction Information of Chemicals and Proteins

Metabolic pathway analysis, one of the most important fields in biochemistry, is pivotal to understanding the maintenance and modulation of the functions of an organism. Good comprehension of metabolic pathways is critical to understanding the mechanisms of some fundamental biological processes. Given a small molecule or an enzyme, how may one identify the metabolic pathways in which it may participate? Answering such a question is a first important step in understanding a metabolic pathway system. By utilizing the information provided by chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions, a novel method was proposed by which to allocate small molecules and enzymes to 11 major classes of metabolic pathways. A benchmark dataset consisting of 3,348 small molecules and 654 enzymes of yeast was constructed to test the method. It was observed that the first order prediction accuracy evaluated by the jackknife test was 79.56% in identifying the small molecules and enzymes in a benchmark dataset. Our method may become a useful vehicle in predicting the metabolic pathways of small molecules and enzymes, providing a basis for some further analysis of the pathway systems.     

Nuclear envelope‐associated dynein drives prophase centrosome separation and enables Eg5‐independent bipolar spindle formation

The microtubule motor protein kinesin‐5 (Eg5) provides an outward force on centrosomes, which drives bipolar spindle assembly. Acute inhibition of Eg5 blocks centrosome separation and causes mitotic arrest in human cells, making Eg5 an attractive target for anti‐cancer therapy. Using in vitro directed evolution, we show that human cells treated with Eg5 inhibitors can rapidly acquire the ability to divide in the complete absence of Eg5 activity. We have used these Eg5‐independent cells to study alternative mechanisms of centrosome separation. We uncovered a pathway involving nuclear envelope (NE)‐associated dynein that drives centrosome separation in prophase. This NE‐dynein pathway is essential for bipolar spindle assembly in the absence of Eg5, but also functions in the presence of full Eg5 activity, where it pulls individual centrosomes along the NE and acts in concert with Eg5‐dependent outward pushing forces to coordinate prophase centrosome separation. Together, these results reveal how the forces are produced to drive prophase centrosome separation and identify a novel mechanism of resistance to kinesin‐5 inhibitors.     

A physiological analogy of the niche for projecting the potential distribution of plants

Aim  To develop a physiologically based model of the plant niche for use in species distribution modelling. Location  Europe. Methods  We link the Thornley transport resistance (TTR) model with functions which describe how the TTR’s model parameters are influenced by abiotic environmental factors. The TTR model considers how carbon and nutrient uptake, and the allocation of these assimilates, influence growth. We use indirect statistical methods to estimate the model parameters from a high resolution data set on tree distribution for 22 European tree species. Results  We infer, from distribution data and abiotic forcing data, the physiological niche dimensions of 22 European tree species. We found that the model fits were reasonable (AUC: 0.79–0.964). The projected distributions were characterized by a false positive rate of 0.19 and a false negative rate 0.12. The fitted models are used to generate projections of the environmental factors that limit the range boundaries of the study species. Main conclusions  We show that physiological models can be used to derive physiological niche dimensions from species distribution data. Future work should focus on including prior information on physiological rates into the parameter estimation process. Application of the TTR model to species distribution modelling suggests new avenues for establishing explicit links between distribution and physiology, and for generating hypotheses about how ecophysiological processes influence the distribution of plants.     

Short hairpin RNAs against eotaxin or interleukin‐5 decrease airway eosinophilia and hyper‐responsiveness in a murine model of asthma

Background

Eosinophilia plays the major role in the pathogenesis of asthma and correlates with the up‐regulation of eotaxin, which, together with interleukin (IL)‐5, is important for differentiation, chemo‐attraction, degranulation, and survival of eosinophils in local tissue. In a previous study, we found that administration of lentivirus‐delivered short hairpin RNA (shRNA) to suppress the expression of IL‐5 inhibited airway inflammation. The present study aimed to investigate the role of eotaxin shRNA and the synergistic effect of eotaxin and IL‐5 shRNAs on airway inflammation in an ovalbumin (OVA)‐induced murine model of asthma.

Methods

Lentivirus‐delivered shRNAs were used to suppress the expression of eotaxin and/or IL‐5 in local tissue in an OVA‐induced murine asthma model.

Results

Intra‐tracheal administration of lentivirus containing eotaxin shRNA expressing cassette (eoSEC3.3) efficiently moderated the characteristics of asthma, including airway hyper‐responsiveness, cellular infiltration of lung tissues, and eotaxin and IL‐5 levels in bronchio‐alveolar lavage fluid. Administration of lentiviruses expressing IL‐5 or eotaxin shRNAs (IL5SEC4 + eoSEC3.3) also moderated the symptoms of asthma in a mouse model.

Conclusions

Local delivery of lentiviruses expressing IL‐5 and eotaxin shRNAs provides a potential tool in moderating airway inflammation and also has the potential for developing clinical therapy based on the application of shRNAs of chemokines and cytokines involved in T helper 2 cell inflammation and eosinophilia. Copyright © 2008 John Wiley & Sons, Ltd.