-Species within the genus, Campylobacter, have emerged over the last three decades as significant clinical pathogens, particularly of human public health concern, where the majority of acute bacterial enteritis in the Western world is due to these organisms. Of particular concern are the species, C. jejuni and C. coli, which are responsible for most of these gastrointestinal-related infections. Although these organisms have already emerged as causative agents of zoonoses, several aspects of their epidemiology and pathophysiology are only beginning to emerge. Trends in increasing antibiotic resistance are beginning to emerge with oral antibiotics, which may be the drug of choice for when it is necessary to intervene chemotherapeutically. This review wishes to examine (i) emerging clinical aspects of the disease, such as Guillain Barré syndrome (GBS), (ii) the association between these organisms and poultry as a natural host, (iii) environmental aspects of Campylobacter epidemiology, (iv) the emergence of atypical campylobacters (v) emerging trends in antibiotic resistance, (vi) adoption of modern methods for the detection of campylobacters.

Three rapid spectroscopic approaches for whole-organism fingerprintingpyrolysis mass spectrometry (PyMS), Fourier transform infra-red spectroscopy (FT-IR) and dispersive Raman microscopy -were used to analyse a group of 59 clinical bacterial isolates associated with urinary tract infection. Direct visual analysis of these spectra was not possible, highlighting the need to use methods to reduce the dimensionality of these hyperspectral data. The unsupervised methods of discriminant function and hierarchical cluster analyses were employed to group these organisms based on their spectral fingerprints, but none produced wholly satisfactory groupings which were characteristic for each of the five bacterial types. In contrast, for PyMS and FT-IR, the artificial neural network (ANN) approaches exploiting multi-layer perceptrons or radial basis functions could be trained with representative spectra of the five bacterial groups so that isolates from clinical bacteriuria in an independent unseen test set could be correctly identified. Comparable ANNs trained with Raman spectra correctly identified some 80% of the same test set. PyMS and FT-IR have often been exploited within microbial systematics, but these are believed to be the first published data showing the ability of dispersive Raman microscopy to discriminate clinically significant intact bacterial species. These results demonstrate that modern analytical spectroscopies of high intrinsic dimensionality can provide rapid accurate microbial characterization techniques, but only when combined with appropriate chemometrics. ~~

Three recent drinking-water–associated cryptosporidiosis outbreaks in Northern Ireland were investigated by using genotyping and subgenotyping tools. One Cryptosporidium parvum outbreak was caused by the bovine genotype, and two were caused by the human genotype . Subgenotyping analyses indicate that two predominant subgenotypes were associated with these outbreaks and had been circulating in the community.

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The high level of faecal carriage of MDR E. coli in nursing home residents demonstrates their importance as a reservoir population. Public health measures to combat spread of these organisms should address the needs of this group.

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Diffuse reflectance‐absorbance Fourier transform infrared spectroscopy (FT‐IR) was used to analyse 19 hospital isolates which had been identified by conventional means to one of Enterococcus faecalis, E. faecium, Streptococcus bovis, S. mitis, S. pneumoniae, or S. pyogenes. Principal components analysis of the FT‐IR spectra showed that this ‘unsupervised’ learning method failed to form six separable clusters (one for each species) and thus could not be used to identify these bacteria based on their FT‐IR spectra. By contrast, artificial neural networks (ANNs) could be trained by ‘supervised’ learning (using the back‐propagation algorithm) with the principal components scores of derivatised spectra to recognise the strains from their FT‐IR spectra. These results demonstrate that the combination of FT‐IR and ANNs provides a rapid, novel and accurate bacterial identification technique.

This review discusses characteristics of the genus Cryptosporidium and addresses the pathogenesis, reservoirs, public health significance and current applications for the detection and typing of this important pathogen. By increasing knowledge in key areas of Cryptosporidium research such as aetiology, epidemiology, transmission and host interactions, the numbers of cases of human cryptosporidiosis should be reduced.