Establishment of a system to standardize acceptability criteria for alanine aminotransferase activity in donated blood

A multilaboratory study was conducted to develop a system for standardizing alanine aminotransferase (ALT) acceptability criteria ("cutoffs") for donated blood. Without standardized cutoffs, each laboratory must develop its own cutoff, and this may not make optimal use of ALT testing to reduce transmission of non-A, non-B hepatitis (NANB). Defining an ALT acceptability criterion in absolute terms is necessary because relative cutoffs based on local donor populations may be affected by the prevalence of NANB in each community. This study involved 16 laboratories using 23 different analytic systems. The ALT results of the analysis of a plasma reference sample could be used to translate mathematically a single, absolute cutoff to units applicable to each analytic system. The distribution of ALT results in 1.4 million donations from across the country was established; basing the cutoff on this sample avoids the problems inherent in using a local donor base to establish a cutoff. We propose the implementation of a system to standardize ALT acceptability criteria to an activity level defined by analysis of a nationwide donor sample.     

Quantitative neuromorphometry using magnetic resonance histology

Magnetic resonance imaging (MRI), now common in the clinical domain, has been adapted for use by the neuropathologist by increasing the spatial resolution over 100,000 times what is common in human clinical imaging. This increase in spatial resolution has been accomplished through a variety of technical advances-higher magnetic fields, more sensitive receivers, and clever encoding methods. Magnetic resonance histology (MRH), that is, the application of MRI to study tissue specimens, now makes three-dimensional imaging of the fixed brain in the cranium routine. Active staining (perfusion fixation with a paramagnetic contrast agent) has allowed us to reduce the scan time by more than 8 times over earlier methods. The result is a three-dimensional isotropic image array that can be viewed along any direction without loss of spatial resolution. Homologous slices can be chosen interactively. Since the tissue is still fully hydrated in the cranium, tissue shrinkage and distortion are virtually eliminated. Volume measurements of neural structures can be made with a high degree of precision and accuracy. MRH will not replace more traditional methods, but it promises enormous value in choosing particular areas and times for more traditional sectioning and assessment.     

Evolutionary-driven support vector machines for determining the degree of liver fibrosis in chronic hepatitis C

Objective

Hepatic fibrosis, the principal pointer to the development of a liver disease within chronic hepatitis C, can be measured through several stages. The correct evaluation of its degree, based on recent different non-invasive procedures, is of current major concern. The latest methodology for assessing it is the Fibroscan and the effect of its employment is impressive. However, the complex interaction between its stiffness indicator and the other biochemical and clinical examinations towards a respective degree of liver fibrosis is hard to be manually discovered. In this respect, the novel, well-performing evolutionary-powered support vector machines are proposed towards an automated learning of the relationship between medical attributes and fibrosis levels. The traditional support vector machines have been an often choice for addressing hepatic fibrosis, while the evolutionary option has been validated on many real-world tasks and proven flexibility and good performance.

Methods and materials

The evolutionary approach is simple and direct, resulting from the hybridization of the learning component within support vector machines and the optimization engine of evolutionary algorithms. It discovers the optimal coefficients of surfaces that separate instances of distinct classes. Apart from a detached manner of establishing the fibrosis degree for new cases, a resulting formula also offers insight upon the correspondence between the medical factors and the respective outcome. What is more, a feature selection genetic algorithm can be further embedded into the method structure, in order to dynamically concentrate search only on the most relevant attributes. The data set refers 722 patients with chronic hepatitis C infection and 24 indicators. The five possible degrees of fibrosis range from F0 (no fibrosis) to F4 (cirrhosis).

Results

Since the standard support vector machines are among the most frequently used methods in recent artificial intelligence studies for hepatic fibrosis staging, the evolutionary method is viewed in comparison to the traditional one. The multifaceted discrimination into all five degrees of fibrosis and the slightly less difficult common separation into solely three related stages are both investigated. The resulting performance proves the superiority over the standard support vector classification and the attained formula is helpful in providing an immediate calculation of the liver stage for new cases, while establishing the presence/absence and comprehending the weight of each medical factor with respect to a certain fibrosis level.

Conclusion

The use of the evolutionary technique for fibrosis degree prediction triggers simplicity and offers a direct expression of the influence of dynamically selected indicators on the corresponding stage. Perhaps most importantly, it significantly surpasses the classical support vector machines, which are both widely used and technically sound. All these therefore confirm the promise of the new methodology towards a dependable support within the medical decision-making.     

Van der Woude syndrome: dentofacial features and implications for clinical practice

Background:  Van der Woude syndrome (VWS) is the most common clefting syndrome in humans. It is characterized by the association of congenital lower lip fistulae with cleft lip and/or cleft palate. VWS individuals have a high prevalence of hypodontia. Although caused by a single gene mutation, VWS has variable phenotypic expression. This study aimed to describe the range of clinical presentations in 22 individuals with VWS to facilitate its diagnosis.
Methods:  A retrospective study of 22 patients with a diagnosis of VWS was undertaken at the Australian Craniofacial Unit (ACFU) in Adelaide. Three extended families with affected members were included in the study cohort.
Results:  The overall prevalence of lip pits in this study cohort was 86%. Cleft phenotypes included bilateral cleft lip and palate (32%); unilateral cleft lip and palate (32%); submucous cleft palate (23%); and isolated cleft hard and soft palate (9%). Missing permanent teeth were reported in 86% of affected individuals.
Conclusions:  Submucous cleft palate in VWS may go undiagnosed if the lower lip pits are not detected. Associated hypodontia and resultant malocclusions will also require management by a dental team.     

Italian healthcare workers' views on mandatory vaccination

Background  

Mandatory vaccination has contributed to the success of immunisation programmes but voluntary vaccination allows people to be responsible for their own health. There are benefits from both policies and the arguments between them remain subject to debate within and without the scientific community, both nationally and internationally. The aim of this study is to assess the opinions of those who actually work in the Vaccination Service.     

Automated segmentation of the actively stained mouse brain using multi-spectral MR microscopy

Magnetic resonance microscopy (MRM) has created new approaches for high-throughput morphological phenotyping of mouse models of diseases. Transgenic and knockout mice serve as a test bed for validating hypotheses that link genotype to the phenotype of diseases, as well as developing and tracking treatments. We describe here a Markov random fields based segmentation of the actively stained mouse brain, as a prerequisite for morphological phenotyping. Active staining achieves higher signal to noise ratio (SNR) thereby enabling higher resolution imaging per unit time than obtained in previous formalin-fixed mouse brain studies. The segmentation algorithm was trained on isotropic 43-mum T1- and T2-weighted MRM images. The mouse brain was segmented into 33 structures, including the hippocampus, amygdala, hypothalamus, thalamus, as well as fiber tracts and ventricles. Probabilistic information used in the segmentation consisted of (a) intensity distributions in the T1- and T2-weighted data, (b) location, and (c) contextual priors for incorporating spatial information. Validation using standard morphometric indices showed excellent consistency between automatically and manually segmented data. The algorithm has been tested on the widely used C57BL/6J strain, as well as on a selection of six recombinant inbred BXD strains, chosen especially for their largely variant hippocampus.