title: Vacuum-assisted infiltration of chitosan or polycaprolactone as a structural reinforcement for sintered cancellous bovine bone graft

authors: Laird, Dougal Frazer

subjects: Sintered cancellous bovine bone

abstract: Sintered cancellous bovine bone (SCBB) offers numerous advantages as a bone graft substitute material; however, its mechanical properties require improvement. In this study, SCBB was infiltrated with ε-polycaprolactone (PCL) or chitosan/monetite to improve mechanical properties while retaining valuable SCBB structure. Organic infiltrating solutions consisted of (i) chitosan and monetite (CaHPO₄) dissolved in hydrochloric acid; (ii) chitosan, monetite (CaHPO₄), and genipin dissolved in hydrochloric acid; or (iii) PCL polymer dissolved in tetrahydrofuran (THF). Porous SCBB materials were infiltrated with one of the three solutions using vacuum-assisted infiltration. Chitosan and CaHPO₄ were immobilized in the SCBB structure by reprecipitation following a pH increase in an ammonia atmosphere. Genipin was used in one sample group to immobilize chitosan via crosslinking. PCL was immobilized by evaporating the THF carrier solvent. Mechanical compression testing showed an improvement in ultimate stress for the SCBB with chitosan/CaHPO₄ infiltrates, whereas PCL samples showed an increase in modulus. All SCBB samples were found to demonstrate favorable in vitro biocompatibility when subjected to L929 mouse fibroblast cells but required a vigorous washing regime to eradicate toxic ammonia residue. In conclusion, infiltration of SCBB with a polymeric or organic/mineral composite matrix positively modifies SCBB mechanical properties in favor of bone grafting applications.

text: Vacuum-assisted infiltration of chitosan or polycaprolactone as a structural reinforcement for sintered cancellous bovine bone graft Sintered cancellous bovine bone (SCBB) offers numerous advantages as a bone graft substitute material; however, its mechanical properties require improvement. In this study, SCBB was infiltrated with ε-polycaprolactone (PCL) or chitosan/monetite to improve mechanical properties while retaining valuable SCBB structure. Organic infiltrating solutions consisted of (i) chitosan and monetite (CaHPO₄) dissolved in hydrochloric acid; (ii) chitosan, monetite (CaHPO₄), and genipin dissolved in hydrochloric acid; or (iii) PCL polymer dissolved in tetrahydrofuran (THF). Porous SCBB materials were infiltrated with one of the three solutions using vacuum-assisted infiltration. Chitosan and CaHPO₄ were immobilized in the SCBB structure by reprecipitation following a pH increase in an ammonia atmosphere. Genipin was used in one sample group to immobilize chitosan via crosslinking. PCL was immobilized by evaporating the THF carrier solvent. Mechanical compression testing showed an improvement in ultimate stress for the SCBB with chitosan/CaHPO₄ infiltrates, whereas PCL samples showed an increase in modulus. All SCBB samples were found to demonstrate favorable in vitro biocompatibility when subjected to L929 mouse fibroblast cells but required a vigorous washing regime to eradicate toxic ammonia residue. In conclusion, infiltration of SCBB with a polymeric or organic/mineral composite matrix positively modifies SCBB mechanical properties in favor of bone grafting applications.

year: 2012

title: Mining data streams using option trees (revised edition, 2004)

authors: Holmes, Geoffrey

subjects: Machine learning

abstract: The data stream model for data mining places harsh restrictions on a learning algorithm. A model must be induced following the briefest interrogation of the data, must use only available memory and must update itself over time within these constraints. Additionally, the model must be able to be used for data mining at any point in time.
This paper describes a data stream classi_cation algorithm using an ensemble of option trees. The ensemble of trees is induced by boosting and iteratively combined into a single interpretable model. The algorithm is evaluated using benchmark datasets for accuracy against state-of-the-art algorithms that make use of the entire dataset.

text: Mining data streams using option trees (revised edition, 2004) The data stream model for data mining places harsh restrictions on a learning algorithm. A model must be induced following the briefest interrogation of the data, must use only available memory and must update itself over time within these constraints. Additionally, the model must be able to be used for data mining at any point in time.
This paper describes a data stream classi_cation algorithm using an ensemble of option trees. The ensemble of trees is induced by boosting and iteratively combined into a single interpretable model. The algorithm is evaluated using benchmark datasets for accuracy against state-of-the-art algorithms that make use of the entire dataset.

year: 2004-01-01

title: Ethnic disparities in breast cancer survival in New Zealand: which factors contribute?

authors: Tin Tin, Sandar

subjects: Breast cancer

abstract: Background: New Zealand has major ethnic disparities in breast cancer survival with Maori (indigenous people) and Pacific women (immigrants or descended from immigrants from Pacific Islands) faring much worse than other ethnic groups. This paper identified underlying factors and assessed their relative contribution to this risk differential. 
Methods: This study involved all women who were diagnosed with primary invasive breast cancer in two health regions, covering about 40% of the national population, between January 2000 and June 2014. Maori and Pacific patients were compared with other ethnic groups in terms of demographics, mode of diagnosis, disease factors and treatment factors. Cox regression modelling was performed with stepwise adjustments, and hazards of excess mortality from breast cancer for Maori and Pacific patients were assessed. 
Results: Of the 13,657 patients who were included in this analysis, 1281 (9.4%) were Maori, and 897 (6.6%) were Pacific women. Compared to other ethnic groups, they were younger, more likely to reside in deprived neighbourhoods and to have co-morbidities, and less likely to be diagnosed through screening and with early stage cancer, to be treated in a private care facility, to receive timely cancer treatment, and to receive breast conserving surgery. They had a higher risk of excess mortality from breast cancer (age and year of diagnosis adjusted hazard ratio: 1.76; 95% CI: 1.51-2.04 for Maori and 1.97; 95% CI: 1.67-2.32 for Pacific women), of which 75% and 99% respectively were explained by baseline differences. The most important contributor was late stage at diagnosis. Other contributors included neighbourhood deprivation, mode of diagnosis, type of health care facility where primary cancer treatment was undertaken and type of loco-regional therapy. 
Conclusions: Late diagnosis, deprivation and differential access to and quality of cancer care services were the key contributors to ethnic disparities in breast cancer survival in New Zealand. Our findings underscore the need for a greater equity focus along the breast cancer care pathway, with an emphasis on improving access to early diagnosis for Maori and Pacific women.

text: Ethnic disparities in breast cancer survival in New Zealand: which factors contribute? Background: New Zealand has major ethnic disparities in breast cancer survival with Maori (indigenous people) and Pacific women (immigrants or descended from immigrants from Pacific Islands) faring much worse than other ethnic groups. This paper identified underlying factors and assessed their relative contribution to this risk differential. 
Methods: This study involved all women who were diagnosed with primary invasive breast cancer in two health regions, covering about 40% of the national population, between January 2000 and June 2014. Maori and Pacific patients were compared with other ethnic groups in terms of demographics, mode of diagnosis, disease factors and treatment factors. Cox regression modelling was performed with stepwise adjustments, and hazards of excess mortality from breast cancer for Maori and Pacific patients were assessed. 
Results: Of the 13,657 patients who were included in this analysis, 1281 (9.4%) were Maori, and 897 (6.6%) were Pacific women. Compared to other ethnic groups, they were younger, more likely to reside in deprived neighbourhoods and to have co-morbidities, and less likely to be diagnosed through screening and with early stage cancer, to be treated in a private care facility, to receive timely cancer treatment, and to receive breast conserving surgery. They had a higher risk of excess mortality from breast cancer (age and year of diagnosis adjusted hazard ratio: 1.76; 95% CI: 1.51-2.04 for Maori and 1.97; 95% CI: 1.67-2.32 for Pacific women), of which 75% and 99% respectively were explained by baseline differences. The most important contributor was late stage at diagnosis. Other contributors included neighbourhood deprivation, mode of diagnosis, type of health care facility where primary cancer treatment was undertaken and type of loco-regional therapy. 
Conclusions: Late diagnosis, deprivation and differential access to and quality of cancer care services were the key contributors to ethnic disparities in breast cancer survival in New Zealand. Our findings underscore the need for a greater equity focus along the breast cancer care pathway, with an emphasis on improving access to early diagnosis for Maori and Pacific women.

year: 2018