Incidence, clinical spectrum, diagnostic features, treatment and predictors of paradoxical reactions during antibiotic treatment of Mycobacterium ulcerans infections

Background: Paradoxical reactions from antibiotic treatment of Mycobacterium ulcerans have recently been recognized. Data is lacking regarding their incidence, clinical and diagnostic features, treatment, outcomes and risk factors in an Australian population.

Methods: Data was collected prospectively on all confirmed cases of M. ulcerans infection managed at Barwon Health Services, Australia, from 1/1/1998-31/12/2011. Paradoxical reactions were defined on clinical and histological criteria and cases were determined by retrospectively reviewing the clinical history and histology of excised lesions. A Poisson regression model was used to examine associations with paradoxical reactions.

Results: Thirty-two of 156 (21%) patients developed paradoxical reactions a median 39 days (IQR 20-73 days) from antibiotic initiation. Forty-two paradoxical episodes occurred with 26 (81%) patients experiencing one and 6 (19%) multiple episodes. Thirty-two (76%) episodes occurred during antibiotic treatment and 10 (24%) episodes occurred a median 37 days after antibiotic treatment. The reaction site involved the original lesion (wound) in 23 (55%), was separate to but within 3 cm of the original lesion (local) in 11 (26%) and was more than 3 cm from the original lesion (distant) in 8 (19%) episodes. Mycobacterial cultures were negative in 33/33 (100%) paradoxical episodes. Post-February 2009 treatment involved more cases with no antibiotic modifications (12/15 compared with 11/27, OR 5.82, 95% CI 1.12-34.07, p = 0.02) and no further surgery (9/15 compared with 2/27, OR 18.75, 95% CI 2.62-172.73, p < 0.001). Six severe cases received prednisone with marked clinical improvement. On multivariable analysis, age ≥ 60 years (RR 2.84, 95% CI 1.12-7.17, p = 0.03), an oedematous lesion (RR 3.44, 95% CI 1.11-10.70, p=0.03) and use of amikacin in the initial antibiotic regimen (RR 6.33, 95% CI 2.09-19.18, p < 0.01) were associated with an increased incidence of paradoxical reactions.

Conclusions: Paradoxical reactions occur frequently during or after antibiotic treatment of M. ulcerans infections in an Australian population and may be increased in older adults, oedematous disease forms, and in those treated with amikacin. Recognition of paradoxical reactions led to changes in management with less surgery, fewer antibiotic modifications and use of prednisolone for severe reactions.

A cross-disciplinary analysis of thematic structure of dissertation abstracts

The ways by which the academic texts are investigated differ from time to time with legacies of each tradition influencing the subsequent approaches. One of the approaches that has not lost its favor ever since it was established is the Australian Systemic Functional tradition. Based on the descriptions provided by this tradition, in this study, the thematic structure (Halliday, 1994) of the gap indication move and the Introduction section (Swales, 2004) of 120 dissertation abstracts from six disciplines was investigated at two levels, i.e. choice of theme type and thematic progression. The simple topical theme was recognized as the typical theme of the rhetorical units in focus across the six disciplines. With respect to the thematic progression, the theme-reiteration and zig-zag patterns were found to be the characteristic patterns. These results indicate that the language of abstracts is remarkably factual and far from abstraction.

Information structure and the flow of translation

Translators often follow the established conventions of translations set out by founders like Nida and Taber (1969) or Newmark (1988). The principal convention, one could say, is to adhere to the source text in form and meaning. Another major convention is to keep the flow of the translated text natural, often referred to as ‘readability’ (Baker and Saldanha, 2009; Hatim and Munday, 2004). These two conventions are hard to go together, and one of them is often flouted. To maintain the same position of discoursal elements or information structure of the source text which include thematic information, left-dislocation, contrastiveness, and passive voice in the translated text is not an easy task. This exacerbates the task especially if the source and the target language have different typological features. This paper argues that discoursal elements are determinant in understanding the flow of the texts in the source language and should not, therefore, be frequently switched around in the translated texts to fit the norm of the target language. The order of these information structure elements should be maximally maintained when translating a text into a target language. It is after all the employment of such information structure units by the writer of the source text which is significant at any given point in discourse both cognitively, when processing the text, and interactionally, when communicating with the reader.

Topic model kernel : an empirical study towards probabilistically reduced features for classification

Probabilistic topic models have become a standard in modern machine learning with wide applications in organizing and summarizing ‘documents’ in high-dimensional data such as images, videos, texts, gene expression data, and so on. Representing data by dimensional reduction of mixture proportion extracted from topic models is not only richer in semantics than bag-of-word interpretation, but also more informative for classification tasks. This paper describes the Topic Model Kernel (TMK), a high dimensional mapping for Support Vector Machine classification of data generated from probabilistic topic models. The applicability of our proposed kernel is demonstrated in several classification tasks from real world datasets. We outperform existing kernels on the distributional features and give the comparative results on non-probabilistic data types.

Investigating machine learning techniques for detection of depression using structural MRI volumetric features

Structural MRI offers anatomical details and high sensitivity to pathological changes. It can demonstrate certain patterns of brain changes present at a structural level. Research to date has shown that volumetric analysis of brain regions has importance in depression detection. However, such analysis has had very minimal use in depression detection studies at individual level. Optimally combining various brain volumetric features/attributes, and summarizing the data into a distinctive set of variables remain difficult. This study investigates machine learning algorithms that automatically identify relevant data attributes for depression detection. Different machine learning techniques are studied for depression classification based on attributes extracted from structural MRI (sMRI) data. The attributes include volume calculated from whole brain, white matter, grey matter and hippocampus. Attributes subset selection is performed aiming to remove redundant attributes using three filtering methods and one hybrid method, in combination with ranker search algorithms. The highest average classification accuracy, obtained by using a combination of both SVM-EM and IG-Random Tree algorithms, is 85.23%. The classification approach implemented in this study can achieve higher accuracy than most reported studies using sMRI data, specifically for detection of depression.

Clinical features and risk factors of oedematous Mycobacterium ulcerans lesions in an Australian population: beware cellulitis in an endemic area

Introduction
Oedematous lesions are a less common but more severe form of Mycobacterium ulcerans disease. Misdiagnosis as bacterial cellulitis can lead to delays in treatment. We report the first comprehensive descriptions of the clinical features and risk factors of patients with oedematous disease from the Bellarine Peninsula of south-eastern Victoria, Australia.

Methods
Data on all confirmed Mycobacterium ulcerans cases managed at Barwon Health, Victoria, were collected from 1/1/1998–31/12/2012. A multivariate logistic regression model was used to assess associations with oedematous forms of Mycobacterium ulcerans disease.

Results
Seventeen of 238 (7%) patients had oedematous Mycobacterium ulcerans lesions. Their median age was 70 years (IQR 17–82 years) and 71% were male. Twenty-one percent of lesions were WHO category one, 35% category two and 41% category three. 16 (94%) patients were initially diagnosed with cellulitis and received a median 14 days (IQR 9–17 days) of antibiotics and 65% required hospitalization prior to Mycobacterium ulcerans diagnosis. Fever was present in 50% and pain in 87% of patients. The WCC, neutrophil count and CRP were elevated in 54%, 62% and 75% of cases respectively. The median duration of antibiotic treatment was 84 days (IQR 67–96) and 94% of cases required surgical intervention. On multivariable analysis, there was an increased likelihood of a lesion being oedematous if on the hand (OR 85.62, 95% CI 13.69–535.70; P<0.001), elbow (OR 7.83, 95% CI 1.39–43.96; p<0.001) or ankle (OR 7.92, 95% CI 1.28–49.16; p<0.001), or if the patient had diabetes mellitus (OR 9.42, 95% CI 1.62–54.74; p = 0.02).

Conclusions
In an Australian population, oedematous Mycobacterium ulcerans lesions present with similar symptoms, signs and investigation results to, and are commonly mistakenly diagnosed for, bacterial limb cellulitis. There is an increased likelihood of oedematous lesions affecting the hand, elbow or ankle, and in patients with diabetes.

Complexities of teaching — features of teacher education programs and professional learning practices to support their development

This publication is the editorial for Vol 15.2 of MTED which summarises and synthesises the articles published in the issue. The extent to which those whose learning is the focus controlled the learning situations in which they participated is the key concept discussed and the factors contributing to the extent of control are elucidated.