Varicella Coinfection in Patients with Active Monkeypox in the Democratic Republic of the Congo

From 2006 to 2007, an active surveillance program for human monkeypox (MPX) in the Democratic Republic of the Congo identified 151 cases of coinfection with monkeypox virus and varicella zoster virus from 1158 suspected cases of human MPX (13%). Using clinical and socio-demographic data collected with standardized instruments by trained, local nurse supervisors, we examined a variety of hypotheses to explain the unexpectedly high proportion of coinfections among the sample, including the hypothesis that the two viruses occur independently. The probabilities of disease incidence and selection necessary to yield the observed sample proportion of coinfections under an assumption of independence are plausible given what is known and assumed about human MPX incidence. Cases of human MPX are expected to be underreported, and more coinfections are expected with improved surveillance.     

Macrophages Recognize Size and Shape of Their Targets

Recognition by macrophages is a key process in generating immune response against invading pathogens. Previous studies have focused on recognition of pathogens through surface receptors present on the macrophage''s surface. Here, using polymeric particles of different geometries that represent the size and shape range of a variety of bacteria, the importance of target geometry in recognition was investigated. The studies reported here reveal that attachment of particles of different geometries to macrophages exhibits a strong dependence on size and shape. For all sizes and shapes studied, particles possessing the longest dimension in the range of 2–3 µm exhibited highest attachment. This also happens to be the size range of most commonly found bacteria in nature. The surface features of macrophages, in particular the membrane ruffles, might play an important role in this geometry-based target recognition by macrophages. These findings have significant implications in understanding the pathogenicity of bacteria and in designing drug delivery carriers.     

A second serogroup of Legionella erythra serologically indistinguishable from Legionella rubrilucens

N.A. SAUNDERS, N. DOSHI AND T.G. HARRISON. 1992. Twenty-two red-autofluorescent Legionella strains were identified serologically as either Legionella rubrilucens or L. erythra. A rRNA probe was used for restriction fragment length polymorphism (RFLP) analysis of the strains and the patterns generated were used as an additional method of identifying the strains to species level. In two instances strains which were identified as L. rubrilucens by serology appeared to belong to the species L. erythra by RFLP analysis. This apparent contradiction was resolved by measurements of DNA/DNA homology which confirmed the existence of a second serogroup of L. erythra serologically indistinguishable from L. rubrilucens.     

An optimal strategy to model microbial growth in a multiple substrate environment

A comprehensive model is developed based on an optimal strategy describing varied microbial growth phenomenon involving sequential and simultaneous utilization of substrate. The model mimics the complex regulatory process of a cell which results in diverse growth process with the help of simple multi-variable constrained optimization, which aims at maximizing the specific cell growth. The metabolic processes of a cell are represented by simple flux balance equations. The different growth phenomenon exhibited by a microorganism are attributed to different levels of control present inside the cell. Provision is made in the model for these controls, in the form of constraints in the optimization formulation. The model prediction matches well with the experimental data of simultaneous growth of E. coli K12 on a mixture of glucose and organic acids like lactate, pyruvate, and acetate. Moreover, the model predictions are well in agreement with earlier published experimental data for the growth of E. coli K12 on other organic acids like fumarate, alpha-ketoglutarate, and succinate. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 56: 635-644, 1997.     

Second serogroup of Legionella quinlivanii isolated from two unrelated sources in the United Kingdom.

A series of strains, presumptively identified as legionellas on the basis of their nutritional requirements and biochemical reactivity, were isolated from two unrelated environmental sources in the UK. Representatives of each of these series had a restriction endonuclease digest pattern indistinguishable from that of the Legionella quinlivanii type strain (1442-AUS-E) and the identity of these strains was confirmed by DNA homology studies. Serological examination of the two strains showed that they were distinct from the type strain 1442-AUS-E but indistinguishable from each other. A second serogroup, L. quinlivanii serogroup 2 (type strain LC870; NCTC 12434), is proposed to accommodate these strains.     

Classification of Rotylenchulus reniformis Numbers in Cotton Using Remotely Sensed Hyperspectral Data on Self-Organizing Maps

Rotylenchulus reniformis is one of the major nematode pests capable of reducing cotton yields by more than 60%, causing estimated losses that may exceed millions of dollars U.S. Therefore, early detection of nematode numbers is necessary to reduce these losses. This study investigates the feasibility of using remotely sensed hyperspectral data (reflectances) of cotton plants affected with different nematode population numbers with self-organizing maps (SOM) in correlating and classifying nematode population numbers extant in a plant's rhizosphere. The hyperspectral reflectances were classified into three classes based on R. renifomis population numbers present in plant's rhizosphere. Hyperspectral data (350-2500 nm) were also sub-divided into Visible, Red Edge + Near Infrared (NIR) and Mid-IR region to determine the sub-region most effective in spectrally classifying the nematode population numbers. Various combinations of different feature extraction and dimensionality reduction methods were applied in different regions to extract reduced sets of features. These features were then classified using a supervised-SOM classification method. Our results suggest that the overall classification accuracies, in general, for most methods in most regions (except visible region) varied from 60% to 80%, thereby, indicating a positive correlation between the nematode numbers present in plant's rhizosphere and the corresponding plant's hyperspectral signatures. Results showed that classification accuracies in the Mid-IR region were comparable to the accuracies obtained in other sub-regions. Finally, based on our findings, the use of remotely-sensed hyperspectral data with SOM could prove to be extremely time efficient in detecting nematode numbers present in the soil.     

Geoseq: a tool for dissecting deep-sequencing datasets

Background  

Datasets generated on deep-sequencing platforms have been deposited in various public repositories such as the Gene Expression Omnibus (GEO), Sequence Read Archive (SRA) hosted by the NCBI, or the DNA Data Bank of Japan (ddbj). Despite being rich data sources, they have not been used much due to the difficulty in locating and analyzing datasets of interest.     

n-3 Polyunsaturated fatty acid (PUFA) deficiency elevates and n-3 PUFA enrichment reduces brain 2-arachidonoylglycerol level in mice

2-arachidonoylglycerol (2-AG) is a putative endogenous ligand for cannabinoid receptors and was suggested to play an important role in both physiological and pathological events in the central nervous system (CNS) as well as in peripheral organs. The sequential hydrolysis of arachidonic acid (20:4n-6, AA)-containing phospholipids has been proposed as a major biosynthetic route of 2-AG. On the other hand, the manipulation of the dietary n-3 polyunsaturated fatty acid (PUFA) status changes the AA level in tissue phospholipids. We, therefore, conducted two separate experiments to confirm whether the dietary n-3 PUFA status influences the 2-AG level in the mouse brain. In the first experiment, we fed mice with n-3 PUFA-deficient diet, which resulted in a marked decrease in the docosahexaenoic acid (22:6n-3, DHA) levels without a change in the AA level in brain phospholipids as compared with the mice fed with an n-3 PUFA-sufficient diet. The brain 2-AG level in the n-3 PUFA-deficient group was significantly higher than in the n-3 PUFA sufficient group. In the second experiment, we found that short-term supplementation of DHA-rich fish oil reduced brain 2-AG level as compared with the supplementation with low n-3 PUFA. The decrease in the AA level and the increase in the DHA level in the major phospholipids occurred in the brains of the mice fed the fish oil diet compared with those fed the low n-3 PUFA diet. Our results indicate that the n-3 PUFA deficiency elevates and n-3 PUFA enrichment reduces the brain 2-AG level in mice, suggesting that physiological and pathological events mediated by 2-AG through cannabinoid receptor in the CNS could be modified by the manipulation of the dietary n-3 PUFA status.