Physical activity, sitting and depression during pregnancy

Aims The aim of this cross sectional study is to explore levels of physical activity and sitting behaviour amongst a sample of pregnant Australian women (n = 81), and investigate whether reported levels of physical activity and/or time spent sitting were associated with depressive symptom scores after controlling for potential covariates. Methods Study participants were women who attended the antenatal clinic of a large Brisbane maternity hospital between October and November 2006. Data relating to participants. current levels of physical activity, sitting behaviour, depressive symptoms, demographic characteristics and exposure to known risk factors for depression during pregnancy were collected; via on-site survey, follow-up telephone interview (approximately one week later) and post delivery access to participant hospital records. Results Participants were aged 29.5 (¡¾ 5.6) years and mostly partnered (86.4%) with a gross household income above $26,000 per annum (88.9%). Levels of physical activity were generally low, with only 28.4 % of participants reporting sufficient total activity and 16% of participants reporting sufficient planned (leisure-time) activity. The sample mean for depressive symptom scores measured by the Hospital Anxiety and Depression Scale (HADS-D) was 6.38 (¡¾ 2.55). The mean depressive symptom scores for participants who reported total moderate-to-vigorous activity levels of sufficient, insufficient, and none, were 5.43 (¡¾ 1.56), 5.82 (¡¾ 1.77) and 7.63 (¡¾ 3.25), respectively. Hierarchical multivariable linear regression modelling indicated that after controlling for covariates, a statistically significant difference of 1.09 points was observed between mean depressive symptom scores of participants who reported sufficient total physical activity, compared with participants who reported they were engaging in no moderate-to-vigorous activity in a typical week (p = 0.05) but this did not reach the criteria for a clinically meaningful difference. Total physical activity was contributed 2.2% to the total 30.3% of explained variance within this model. The other main contributors to explained variance in multivariable regression models were anxiety symptom scores and the number of existing children. Further, a trend was observed between higher levels of planned sitting behaviour and higher depressive symptom scores (p = 0.06); this correlation was not clinically meaningful. Planned sitting contributed 3.2% to the total 31.3 % of explained variance. The number of regression covariates and limited sample size led to a less than ideal ratio of covariates to participants, probably attenuating this relationship. Specific information about the sitting-based activities in which participants engaged may have provided greater insight about the relationship between planned sitting and depressive symptoms, but these data were not captured by the present study. Conclusions The finding that higher levels of physical activity were associated with lower levels of depressive symptoms is consistent with the current body of existing literature in pregnant women, and with a larger body of evidence based in general population samples. Although this result was not considered clinically meaningful, the criterion for a clinically meaningful result was an a priori decision based on quality of life literature in non-pregnant populations and may not truly reflect a difference in symptoms that is meaningful to pregnant women. Further investigation to establish clinically meaningful criteria for continuous depressive symptom data in pregnant women is required. This result may have implications relating to prevention and management options for depression during pregnancy. The observed trend between planned sitting and depressive symptom scores is consistent with literature based on leisure-time sitting behaviour in general population samples, and suggests that further research in this area, with larger samples of pregnant women and more specific sitting data is required to explore potential associations between activities such as television viewing and depressive symptoms, as this may be an area of behaviour that is amenable to modification.

A comparison of alternative bankruptcy prediction models

Early models of bankruptcy prediction employed financial ratios drawn from pre-bankruptcy financial statements and performed well both in-sample and out-of-sample. Since then there has been an ongoing effort in the literature to develop models with even greater predictive performance. A significant innovation in the literature was the introduction into bankruptcy prediction models of capital market data such as excess stock returns and stock return volatility, along with the application of the Black–Scholes–Merton option-pricing model. In this note, we test five key bankruptcy models from the literature using an upto- date data set and find that they each contain unique information regarding the probability of bankruptcy but that their performance varies over time. We build a new model comprising key variables from each of the five models and add a new variable that proxies for the degree of diversification within the firm. The degree of diversification is shown to be negatively associated with the risk of bankruptcy. This more general model outperforms the existing models in a variety of in-sample and out-of-sample tests.

Library and information science education 2.0: guiding principles and models of best practice. Interview with Sue Reynolds.

In 2005, Stephen Abram, vice president of Innovation at SirsiDynix, challenged library and information science (LIS) professionals to start becoming “librarian 2.0.” In the last few years, discussion and debate about the “core competencies” needed by librarian 2.0 have appeared in the “biblioblogosphere” (blogs written by LIS professionals). However, beyond these informal blog discussions few systematic and empirically based studies have taken place. A project funded by the Australian Learning and Teaching Council fills this gap. The project identifies the key skills, knowledge, and attributes required by “librarian 2.0.” Eighty-one members of the Australian LIS profession participated in a series of focus groups. Eight themes emerged as being critical to “librarian 2.0”: technology, communication, teamwork, user focus, business savvy, evidence based practice, learning and education, and personal traits. Guided by these findings interviews with 36 LIS educators explored the current approaches used within contemporary LIS education to prepare graduates to become “librarian 2.0”. This video presents an example of ‘great practice’ in current LIS educative practice in helping to foster web 2.0 professionals.

Library and information science education 2.0 : guiding principles and models of best practice : interview with John Terrell

In 2005, Stephen Abram, vice president of Innovation at SirsiDynix, challenged library and information science (LIS) professionals to start becoming “librarian 2.0.” In the last few years, discussion and debate about the “core competencies” needed by librarian 2.0 have appeared in the “biblioblogosphere” (blogs written by LIS professionals). However, beyond these informal blog discussions few systematic and empirically based studies have taken place. A project funded by the Australian Learning and Teaching Council fills this gap. The project identifies the key skills, knowledge, and attributes required by “librarian 2.0.” Eighty-one members of the Australian LIS profession participated in a series of focus groups. Eight themes emerged as being critical to “librarian 2.0”: technology, communication, teamwork, user focus, business savvy, evidence based practice, learning and education, and personal traits. Guided by these findings interviews with 36 LIS educators explored the current approaches used within contemporary LIS education to prepare graduates to become “librarian 2.0”. This video presents an example of ‘great practice’ in current LIS education as it strives to foster web 2.0 professionals.

Library and information science education 2.0 : guiding principles and models of best practice : interview with Kate Davis.

In 2005, Stephen Abram, vice president of Innovation at SirsiDynix, challenged library and information science (LIS) professionals to start becoming “librarian 2.0.” In the last few years, discussion and debate about the “core competencies” needed by librarian 2.0 have appeared in the “biblioblogosphere” (blogs written by LIS professionals). However, beyond these informal blog discussions few systematic and empirically based studies have taken place. A project funded by the Australian Learning and Teaching Council fills this gap. The project identifies the key skills, knowledge, and attributes required by “librarian 2.0.” Eighty-one members of the Australian LIS profession participated in a series of focus groups. Eight themes emerged as being critical to “librarian 2.0”: technology, communication, teamwork, user focus, business savvy, evidence based practice, learning and education, and personal traits. Guided by these findings interviews with 36 LIS educators explored the current approaches used within contemporary LIS education to prepare graduates to become “librarian 2.0”. This video presents an example of ‘great practice’ in current LIS education as it strives to foster web 2.0 professionals.

Quantification of the accuracy of MRI generated 3D models of long bones compared to CT generated 3D models

Orthopaedic fracture fixation implants are increasingly being designed using accurate 3D models of long bones based on computer tomography (CT). Unlike CT, magnetic resonance imaging (MRI) does not involve ionising radiation and is therefore a desirable alternative to CT. This study aims to quantify the accuracy of MRI-based 3D models compared to CT-based 3D models of long bones. The femora of five intact cadaver ovine limbs were scanned using a 1.5T MRI and a CT scanner. Image segmentation of CT and MRI data was performed using a multi-threshold segmentation method. Reference models were generated by digitising the bone surfaces free of soft tissue with a mechanical contact scanner. The MRI- and CT-derived models were validated against the reference models. The results demonstrated that the CT-based models contained an average error of 0.15mm while the MRI-based models contained an average error of 0.23mm. Statistical validation shows that there are no significant differences between 3D models based on CT and MRI data. These results indicate that the geometric accuracy of MRI based 3D models was comparable to that of CT-based models and therefore MRI is a potential alternative to CT for generation of 3D models with high geometric accuracy.

Stochastic models and simulation of ion channel dynamics

The behaviour of ion channels within cardiac and neuronal cells is intrinsically stochastic in nature. When the number of channels is small this stochastic noise is large and can have an impact on the dynamics of the system which is potentially an issue when modelling small neurons and drug block in cardiac cells. While exact methods correctly capture the stochastic dynamics of a system they are computationally expensive, restricting their inclusion into tissue level models and so approximations to exact methods are often used instead. The other issue in modelling ion channel dynamics is that the transition rates are voltage dependent, adding a level of complexity as the channel dynamics are coupled to the membrane potential. By assuming that such transition rates are constant over each time step, it is possible to derive a stochastic differential equation (SDE), in the same manner as for biochemical reaction networks, that describes the stochastic dynamics of ion channels. While such a model is more computationally efficient than exact methods we show that there are analytical problems with the resulting SDE as well as issues in using current numerical schemes to solve such an equation. We therefore make two contributions: develop a different model to describe the stochastic ion channel dynamics that analytically behaves in the correct manner and also discuss numerical methods that preserve the analytical properties of the model.