Maternal antecedents for cerebral palsy in extremely preterm babies: A case-controlled study

The study aimed to identify significant antenatal risk factors for cerebral palsy (CP) among extremely preterm infants with a matched case-control design. Infants born between 1989 and 1996 at 24 to 27 weeks' gestation who survived to hospital discharge were evaluated: 30 with a proven diagnosis of CP at 2 years corrected for prematurity and 120 control children matched for gestational age without CP. Information on maternal obstetric risk factors and medication was obtained. Matched analyses were performed and odds ratios (OR) and 95% confidence intervals (CI) were calculated. An antenatal diagnosis of intrauterine growth restriction was associated with an increased risk of CP (OR 6.6; 95% CI 1.8 to 25.2), while maternal administration of corticosteroids was associated with a reduced risk of CP (OR 0.4; 95% CI 0.1 to 0.98). A high rate of placental histopathology was achieved but no relation between clinical or histological chorioamnionitis or funisitis and CP was demonstrated. Maternal preeclampsia was not associated with a statistically significant reduction in the risk of CP. It is concluded that a reduced risk of CP in extremely preterm infants is associated with the antenatal use of corticosteroids.

Isolation of microsatellite loci from spotted gum (Corymbia variegata), and cross-species amplification in Corymbia and Eucalyptus

Corymbia variegata (spotted gum) is an important commercial hardwood timber species in Australia. Fourteen polymorphic microsatellite loci were isolated from C. variegata, with 3-5 alleles amplified in three individuals examined. Cross-species amplification in Corymbia was successful for all primer pairs, while 10 loci (71%) were successfully transferred to at least one species in the closely related genus Eucalyptus.

Inferring population history from microsatellite and enzyme data in serially introduced cane toads, Bufo marinus

Much progress has been made on inferring population history from molecular data. However, complex demographic scenarios have been considered rarely or have proved intractable. The serial introduction of the South-Central American cane Load Bufo marinas in various Caribbean and Pacific islands involves four major phases: a possible genetic admixture during the first introduction, a bottleneck associated with founding, a transitory, population boom, and finally, a demographic stabilization. A large amount of historical and demographic information is available for those introductions and can be combined profitably with molecular data. We used a Bayesian approach to combine this information With microsatellite (10 loci) and enzyme (22 loci) data and used a rejection algorithm to simultaneously estimate the demographic parameters describing the four major phases of the introduction history,. The general historical trends supported by microsatellites and enzymes were similar. However, there was a stronger support for a larger bottleneck at introductions for microsatellites than enzymes and for a more balanced genetic admixture for enzymes than for microsatellites. Verb, little information was obtained from either marker about the transitory population boom observed after each introduction. Possible explanations for differences in resolution of demographic events and discrepancies between results obtained with microsatellites and enzymes were explored. Limits Of Our model and method for the analysis of nonequilibrium populations were discussed.

Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.

Increasing profits and reducing risks in crop production using participatory systems simulation approaches

The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.

A cross-sectional study of the association between Heberden's nodes, radiographic osteoarthritis of the hands, grip strength, disability and pain

Objective: To describe the associations between hand osteoarthritis (OA), pain and disability in males and females and to further validate the Australian/Canadian CA hand index (AUSCAN LK3.0). Design: Cross-sectional study of 522 subjects from 101 Tasmanian families (males N=174, females N=348). Hand OA was assessed by two observers using the Altman atlas for joint space narrowing and osteophytes at distal interphalangeal and first carpometacarpal joints as well as a score for Heberden's nodes based on hand photography. Hand pain and function were assessed by the AUSCAN LK3.0 and grip strength by dynamometry in both hands on two occasions. Results: The prevalence of hand CA was high in this sample at 44-71% (depending on site). Pain and dysfunction increased with age while grip strength decreased (all P <0.001). All three measures were markedly worse in women, even after taking the severity of arthritis into account. Hand CA explained 5.7-10% of the variation in function, grip strength and pain scores, even after adjustment for age and sex. Further adjustment suggested that the osteoarthritic associations with function and grip strength were largely mediated by pain. Severity of disease was more strongly associated with these scores than presence or absence. Lastly, the AUSCAN LK3.0 showed a comparable association to grip strength with structural damage providing further evidence of index validity. Conclusions: Hand CA at these two sites makes substantial contributions to hand function, strength and pain. The associations with function and strength measures appear mediated by pain. Gender differences in all three measures persist after adjustment for variation in age and CA severity indicating that factors apart from radiographic disease are responsible. (C) 2001 OsteoArthritis Research Society International.

Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data

Binning and truncation of data are common in data analysis and machine learning. This paper addresses the problem of fitting mixture densities to multivariate binned and truncated data. The EM approach proposed by McLachlan and Jones (Biometrics, 44: 2, 571-578, 1988) for the univariate case is generalized to multivariate measurements. The multivariate solution requires the evaluation of multidimensional integrals over each bin at each iteration of the EM procedure. Naive implementation of the procedure can lead to computationally inefficient results. To reduce the computational cost a number of straightforward numerical techniques are proposed. Results on simulated data indicate that the proposed methods can achieve significant computational gains with no loss in the accuracy of the final parameter estimates. Furthermore, experimental results suggest that with a sufficient number of bins and data points it is possible to estimate the true underlying density almost as well as if the data were not binned. The paper concludes with a brief description of an application of this approach to diagnosis of iron deficiency anemia, in the context of binned and truncated bivariate measurements of volume and hemoglobin concentration from an individual's red blood cells.

Clinicopathological significance of the 'keloid-like' collagen and myxoid stroma in advanced rectal cancer

Aim: To establish the histological categorization of fibrotic stroma which reflects the biological behaviour of advanced rectal cancer. Methods and results: Six hundred and twenty-seven surgically resected cases of advanced rectal carcinoma were examined. We histologically categorized fibrotic stroma in the invasive frontal region into three groups: type A, multiple fine and mature fibres were stratified into layers: type B, broad bands of eosinophilic hyalinized collagen ('keloid-like' collagen) were intermingled: type C, myxoid stroma. Type A stroma was observed in 63% of patients, type B stroma in 25%, type C stroma in 12%.. The incidence of type A stroma decreased in accordance with Dukes stage (98% in Dukes A: 73% in B: 41%, in C1: 29% in C2) and conversely, there was an increase of C type (0%, in Dukes A; 4%, in B: 20% in C1: 54% in C2). Stroma type had a significant correlation with long-term survival (80% of 5-year survival in type A stroma: 54% in type B: 26% in type C). Based on multivariate analysis. it was found that the stromal pattern had independent prognostic value, together with nodal involvement. growth pattern. and lymphocyte infiltration. Conclusions: Tumour fibrotic stroma may play an important role as a regulator of neoplastic behaviour. Pathological categorization of the fibrotic stroma is helpful for predicting the prognostic outcome of patients with rectal carcinoma.

A real-time PCR assay for the detection of Neisseria gonorrhoeae by LightCycler

The detection of Neisseria gonorrhoeae by the polymerase chain reaction (PCR) is now recognized as a sensitive and specific method of diagnosing infection by the organism. In this Study 152 urine specimens were examined for N. gonorrhoeae by a real-time PCR method using the LightCycler platform and results were compared to an in-house PCR assay using an ELISA-based detection method. N. gonorrhoeae DNA was detected in 29 (19%) specimens by LightCycler PCR (LC-PCR) and in 31 (20%) specimens by the in house PCR method. The LightCycler assay proved to be specific and 94% sensitive when compared to the in house PCR method. These features combined with the rapid turn-around time for results makes the LC-PCR particularly suitable for the detection of N. gonorrhoeae in a routine clinical laboratory. (C) 2002 Elsevier Science Inc. All rights reserved.

Reasoning about real-time repetitions: terminating and nonterminating

It is common for a real-time system to contain a nonterminating process monitoring an input and controlling an output. Hence, a real-time program development method needs to support nonterminating repetitions. In this paper we develop a general proof rule for reasoning about possibly nonterminating repetitions. The rule makes use of a Floyd-Hoare-style loop invariant that is maintained by each iteration of the repetition, a Jones-style relation between the pre- and post-states on each iteration, and a deadline specifying an upper bound on the starting time of each iteration. The general rule is proved correct with respect to a predicative semantics. In the case of a terminating repetition the rule reduces to the standard rule extended to handle real time. Other special cases include repetitions whose bodies are guaranteed to terminate, nonterminating repetitions with the constant true as a guard, and repetitions whose termination is guaranteed by the inclusion of a fixed deadline. (C) 2002 Elsevier Science B.V. All rights reserved.