Role of kilometer-scale weak circular heterogeneities on upper crustal deformation patterns: Evidence from scaled analogue modeling and the Sudbury Basin, Canada

The Sudbury Basin is a non-cylindrical fold basin occupying the central portion of the Sudbury Impact Structure. The impact structure lends itself excellently to explore the structural evolution of continental crust containing a circular region of long-term weakness. In a series of scaled analogue experiments various model crustal configurations were shortened horizontally at a constant rate. In mechanically weakened crust, model basins formed that mimic several first-order structural characteristics of the Sudbury Basin: (1) asymmetric, non-cylindrical folding of the Basin, (2) structures indicating concentric shortening around lateral basin termini and (3) the presence of a zone of strain concentration near the hinge zones of model basins. Geometrically and kinematically this zone corresponds to the South Range Shear Zone of the Sudbury Basin. According to our experiments, this shear zone is a direct mechanical consequence of basin formation, rather than the result of thrusting following folding. Overall, the models highlight the structurally anomalous character of the Sudbury Basin within the Paleoproterozoic Eastern Penokean Orogen. In particular, our models suggest that the Basin formed by pure shear thickening of crust, whereas transpressive deformation prevailed elsewhere in the orogen. The model basin is deformed by thickening and non-cylindrical synformal buckling, while conjugate transpressive shear zones propagated away from its lateral tips. This is consistent with pure shear deformation of a weak circular inclusion in a strong matrix. The models suggest that the Sudbury Basin formed as a consequence of long-term weakening of the upper crust by meteorite impact.

Outcomes following inpatient rehabilitation of lower limb amputees

Introduction: Lower-limb amputations are a serious adverse consequence of lifestyle related chronic conditions and a serious concern among the aging population in Australia. Lower limb amputations have severe personal, social and economic impacts on the individual, healthcare system and broader community. This study aimed to address a critical gap in the research literature by investigating the physical functioning and social characteristics of lower limb amputees at discharge from tertiary hospital inpatient rehabilitation. Method: A cohort study was implemented among patients with lower limb amputations admitted to a Geriatric Assessment and Rehabilitation Unit for rehabilitation at a tertiary hospital. Conventional descriptive statistics were used to examine patient demographic, physical functioning and social living outcomes recorded for patients admitted between 2005 and 2011. Results: A total of 423 admissions occurred during the study period, 313 (74%) were male. This sample included admissions for left (n = 189, 45%), right (n = 220, 52%) and bilateral (n = 14, 3%) lower limb amputations, with 15 (3%) patients dying whilst an inpatient. The mean (standard deviation) age was 65 (13.9) years. Amputations attributed to vascular causes accounted for 333 (78%) admissions; 65 (15%) of these had previously had an amputation. The mean (SD) length of stay in the rehabilitation unit was 56 (42) days. Prior to this admission, 123 (29%) patients were living alone, 289 (68%) were living with another and 3 (0.7%) were living in residential care. Following this amputation related admission, 89 (21%) patients did not return to their prior living situation. Of those admitted, 187 (44%) patients were discharged with a lower limb prosthesis. Conclusion: The clinical group is predominately older adults. The ratio of males to females was approximately 3:1. Over half did not return to walking and many were not able to return to their prior accommodation. However, few patients died during their admission.

Upper-body morbidity after breast cancer : incidence and evidence for evaluation, prevention, and management within a prospective surveillance model of care

The purpose of this paper is to review the incidence of upper-body morbidity (arm and breast symptoms, impairments, and lymphedema), methods for diagnosis, and prevention and treatment strategies. It was also the purpose to highlight the evidence base for integration of prospective surveillance for upper-body morbidity within standard clinical care of women with breast cancer. Between 10% and 64% of women report upper-body symptoms between 6 months and 3 years after breast cancer, and approximately 20% develop lymphedema. Symptoms remain common into longer-term survivorship, and although lymphedema may be transient for some, those who present with mild lymphedema are at increased risk of developing moderate to severe lymphedema. The etiology of morbidity seems to be multifactorial, with the most consistent risk factors being those associated with extent of treatment. However, known risk factors cannot reliably distinguish between those who will and will not develop upper-body morbidity. Upper-body morbidity may be treatable with physical therapy. There is also evidence in support of integrating regular surveillance for upper-body morbidity into the routine care provided to women with breast cancer, with early diagnosis potentially contributing to more effective management and prevention of progression of these conditions.

Activities for Pearl Barley and Charlie Parsley by Aaron Blabey Puffin Books 2007 Target group: Upper Primary

An upper primary multiliteracies project based on the children’s book “Pearl Barley and Charlie Parsley” by Aaron Blabey. The main theme explored is same and different.

The incidence and predictors of lower limb split skin graft failure and primary closure dehiscence in day case surgical patients

This project was an observational study of outpatients following lower limb surgical procedures for removal of skin cancers. Findings highlight a previously unreported high surgical site failure rate. Results also identified four potential risk factors (increasing age, presence of leg pain, split skin graft and haematoma) which negatively impact on surgical site healing in this population.

A phase II study of mitomycin C and oral etoposide for advanced adenocarcinoma of the upper gastrointestinal tract

Background: Mitomycin C and etoposide have both demonstrated activity against gastric carcinoma. Etoposide is a topoisomerase II inhibitor with evidence for phase-specific and schedule-dependent activity. Patients and method. Twenty-eight consecutive patients with advanced upper gastrointestinal adenocarcinoma were treated with intravenous (i.v.) bolus mitomycin C 6 mg/m2 on day 1 every 21 days to a maximum of four courses. Oral etoposide capsules 50 mg b.i.d. (or 35 mg b.i.d. liquid) were administered days 1 to 10 extending to 14 days in subsequent courses if absolute neutrophil count >1.5 x 109/l on day 14 of first course, for up to six courses. Results: Twenty-six patients were assessed for response of whom 12 had measurable disease and 14 evaluable disease. Four patients had a documented response (one complete remission, three partial remissions) with an objective response rate of 15% (95% confidence interval (95% CI) 4%-35%). Eight patients had stable disease and 14 progressive disease. The median survival was six months. The schedule was well tolerated with no treatment-related deaths. Nine patients experienced leucopenia (seven grade II and two grade III). Nausea and vomiting (eight grade II, one grade III), fatigue (eight grade II, two grade III) and anaemia (seven grade II, two grade III) were the predominant toxicities. Conclusion: This out-patient schedule is well tolerated and shows modest activity in the treatment of advanced upper gastrointestinal adenocarcinoma. Further studies using protracted schedules of etoposide both orally and as infusional treatment should be developed.

Chemotherapy for upper gastrointestinal tumours

The aim of this review is to identify current chemotherapy treatment for tumours of the oesophagus, stomach, pancreas, and liver. The role of both neoadjuvant, adjuvant, and palliative chemotherapy regimens will be discussed. This review will be of interest to oncologists in clarifying current issues regarding chemotherapy, and to physicians in other medical specialties, to increase their general understanding of benefits and drawbacks of chemotherapy in this patient group.

Upper Murrumbidgee : Talking fish - making connections with the rivers of the Murray-Darling Basin

The Upper Murrumbidgee cuts its way through the Snowy Mountains in south‐eastern New South Wales, snaking its way south, then turning north before dropping into the lowland and heading west to join the Murray downstream of Swan Hill. The Upper ‘Bidgee floodplain is only a couple of hundred metres wide, a stark contrast to the kilometres‐wide floodplains in other parts of the Murray‐ Darling Basin. When the floods come, they come up quickly and roar through the narrow valleys. These are the traditional lands of the Ngunnawal and Ngarigo peoples. They fished the river and surrounding waterways and hunted the wetlands. The seasonal rise and fall of the water guided their travels and featured in their stories. The Ngunnawal and Ngarigo people have seen their land and the river change...

Upper Darling: Brewarrina to Bourke : Talking fish - making connections with the rivers of the Murray-Darling Basin

To say ‘Back o’ Bourke’ means ‘miles from anywhere’ to most Australians, however the Barwon and Darling Rivers that pass by the townships of Brewarrina and Bourke, respectively, are at the heart of the Murray‐Darling Basin. These are the traditional lands of the Ngiyampaa, Murawari and Yuwalaraay peoples (refer Aboriginal language groups in the Bringing back the fish section at the back of this booklet). They fished the river and surrounding waterways and hunted the wetlands. The Ngiyampaa, Murawari and Yuwalaraay people have seen their land and the rivers change...

Quality of life of women with lower limb swelling or lymphedema 3-5 years following endometrial cancer

Objective To quantitatively assess and compare the quality of life (QoL) of women with a self-reported diagnosis of lower limb lymphedema (LLL), to women with lower limb swelling (LLS), and to women without LLL or LLS following treatment for endometrial cancer. Methods 1399 participants in the Australian National Endometrial Cancer Study were sent a follow-up questionnaire 3–5 years after diagnosis. Women were asked if they had experienced swelling in the lower limbs and, if so, whether they had received a diagnosis of lymphedema by a health professional. The 639 women who responded were categorised as: Women with LLL (n = 68), women with LLS (n = 177) and women without LLL or LLS (n = 394). Multivariable-adjusted generalized linear models were used to compare women’s physical and mental QoL by LLL status. Results On average, women were 65 years of age and 4 years after diagnosis. Women with LLL had clinically lower physical QoL (M= 41.8, SE= 1.4) than women without LLL or LLS (M= 45.1, SE= 0.8, p = .07), however, their mental QoL was within the normative range (M= 49.6; SE= 1.1 p = 1.0). Women with LLS had significantly lower physical (M= 41.0, SE= 1.0, p = .003) and mental QoL (M= 46.8; SE= 0.8, p < .0001) than women without LLL or LLS (Mental QoL: M= 50.6, SE= 0.8). Conclusion Although LLL was associated with reductions in physical QoL, LLS was related to reductions in both physical and mental QoL 3-5 years after cancer treatment. Early referral to evidence-based lymphedema programs may prevent long-term impairments to women’s QoL.

Clinician-driven automated classification of limb fractures from free-text radiology reports

The aim of this research is to report initial experimental results and evaluation of a clinician-driven automated method that can address the issue of misdiagnosis from unstructured radiology reports. Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to disperse information resources and vast amounts of manual processing of unstructured information, a point-of-care accurate diagnosis is often difficult. A rule-based method that considers the occurrence of clinician specified keywords related to radiological findings was developed to identify limb abnormalities, such as fractures. A dataset containing 99 narrative reports of radiological findings was sourced from a tertiary hospital. The rule-based method achieved an F-measure of 0.80 and an accuracy of 0.80. While our method achieves promising performance, a number of avenues for improvement were identified using advanced natural language processing (NLP) techniques.

Automatic classification of free-text radiology reports to identify limb fractures using machine learning and the SNOMED CT ontology

Objective To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. Materials and Methods 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. Result Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. Discussion Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. Conclusion This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.

Automated classification of limb fractures from free-text radiology reports using a clinician-informed gazetteer methodology

Background Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. Aims The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. Method A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. Results The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. Conclusion While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.