title: Internal versus external control of calcium nutrition in kiwifruit

authors: Montanaro, Giuseppe

subjects: Actinidia deliciosa

abstract: Higher calcium (Ca) concentration in several fleshy fruit including kiwifruit is a pre-requisite for lower incidence of Ca-related diseases and improved fruit nutritional value. This review examines the internal and external factors operating along the soil-to-fruit pathway that are involved in the uptake and partitioning of Ca in kiwifruit vines. After a brief description of fruit growth and the dynamic of nutrient accumulation during fruit development, the review considers the role of soil Ca concentration and availability, root elongation, mass flow in the apoplast, fruit transpiration, competition between fruit and highly transpiring leaves, weather variables and soil moisture. How fruit morphological and anatomical traits, including skin anatomy, xylem development and hydraulic resistance, influence physiological processes such as transpiration and impact on Ca accumulation is also discussed. The review highlights that approximately 80% of the total Ca content of fruit is accumulated during the early weeks after fruit-set, suggesting that failure of good fruit Ca nutrition at that time may lead to poor fruit Ca content at harvest. Therefore, based on the analysis of the internal and external factors that influence Ca accumulation, recommendations are made for orchard practices that maximize Ca accumulation in the kiwifruit berry, including optimal pollination, nutrient and irrigation management, and manipulation of canopy architecture.

text: Internal versus external control of calcium nutrition in kiwifruit Higher calcium (Ca) concentration in several fleshy fruit including kiwifruit is a pre-requisite for lower incidence of Ca-related diseases and improved fruit nutritional value. This review examines the internal and external factors operating along the soil-to-fruit pathway that are involved in the uptake and partitioning of Ca in kiwifruit vines. After a brief description of fruit growth and the dynamic of nutrient accumulation during fruit development, the review considers the role of soil Ca concentration and availability, root elongation, mass flow in the apoplast, fruit transpiration, competition between fruit and highly transpiring leaves, weather variables and soil moisture. How fruit morphological and anatomical traits, including skin anatomy, xylem development and hydraulic resistance, influence physiological processes such as transpiration and impact on Ca accumulation is also discussed. The review highlights that approximately 80% of the total Ca content of fruit is accumulated during the early weeks after fruit-set, suggesting that failure of good fruit Ca nutrition at that time may lead to poor fruit Ca content at harvest. Therefore, based on the analysis of the internal and external factors that influence Ca accumulation, recommendations are made for orchard practices that maximize Ca accumulation in the kiwifruit berry, including optimal pollination, nutrient and irrigation management, and manipulation of canopy architecture.

year: 2014-10-08

title: An Analysis of the Impact of Reinforcement on Response Variability on Multiple Behavioural Dimensions

authors: Kong, Xiuyan

subjects: Reinforcing behavioural variability

abstract: A series of four experiments were carried out to examine whether increases in variability in responding on some dimensions of a behaviour as a result of reinforcement generalised to other dimensions of the same behaviour. In Experiment 1, adult participants drew 300 rectangles on a computer screens; variability in the Area, Shape and Location dimensions of the rectangles drawn was measured. One group of participants received reinforcement when they drew rectangles varying on all three dimensions (VAR) using a threshold contingency to determine reinforcement while another group received reinforcement regardless whether they varied on any of the dimensions of the rectangles drawn (YOKE). Results showed that the variability of each dimension, as measured by the U-value, was higher for the VAR group than for the YOKE group. In Experiment 2, three groups of adult participants received reinforcement when they varied on two of the three dimensions of the rectangles drawn. Results showed that reinforcing variability in the Shape and Location dimensions and in the Area and Location dimensions resulted in higher variability in these dimensions compared to the dimension where variability was not directly reinforced, as measured by U-values. However, for the group who received reinforcement when varying in the Area and Shape dimensions, the variability across the three dimensions did not differ. Generalisation of reinforced variability was examined by comparing the variability in dimensions that were not subject to reinforcement for varying from Experiment 1 and Experiment 2. For the Shape and Location dimensions, results showed that the variability was higher when the two dimensions occurred with other dimensions that were subject for reinforcement for varying compared to when they occurred with other dimensions that were not required to vary. However, no significant difference was found for the Area dimension. Therefore, there appeared to be generalisation of reinforced variability for only two of these three groups of participants, suggesting the dimensions were not orthogonal. The non-orthogonality of the three dimensions of the rectangles was suggested as a possible confounding variable so that it not be concluded that generalisation of reinforced variability across dimensions had been obtained. Experiment 3 used a task with more independent dimensions (Shape, Colour and Pattern) to control for the non-orthogonality issue found in Experiment 2. Adult participants created objects by selecting elements from three dimensions on the computer screen. One group of participants received reinforcement when they varied on the use of elements on all three dimensions using a threshold contingency while the other group received reinforcement independent of the elements chosen. Results showed that the variability in using the elements for all three dimensions was similar between the two groups; whether the group received reinforcement when the dimensions varied did not make a difference. Inspection of the elements selected on each trial revealed that participants from both groups, in general, responded in stereotypic patterns; however, the stereotypy in the responses was not picked up by the measure of U-value. In Experiment 4, a new task asking participants to colour t-shirts on the computer screen was created to examine the effect of reinforcement on the variability in colours used. Adult and adolescent participants were instructed to colour t-shirts on the computer screen in three phases. In Phase 1, no feedback was provided; in Phase 2, positive feedback was provided when participants used a colour they had not used before (including those used in Phase 1); and in Phase 3, no feedback was provided. Results showed that, after reinforcement for using novel colours, participants who used only a small number of colours initially used more colours; however, the increase was not found for participants who initially used a moderate or high number of colours. U-value as the measure of variability was examined by using two sets of simulated data. It was found that highly stereotypic response patterns can result in extremely high U-values. Also, the number of options/categories used affects the values of U, which makes comparisons between groups difficult. Overall, results from these experiments support the notion that the level of variability in responses can be controlled by reinforcement. It is possible that learned variability can generalise over unreinforced dimensions. However, the examination of generalisation of reinforced variability across dimensions is not conclusive when the dimensions are interdependent. The results and simulation showed that U-value as a measure of variability needs to be used with caution because it does not capture potential stereotypy in responses and the values of U can be ambiguous.

text: An Analysis of the Impact of Reinforcement on Response Variability on Multiple Behavioural Dimensions A series of four experiments were carried out to examine whether increases in variability in responding on some dimensions of a behaviour as a result of reinforcement generalised to other dimensions of the same behaviour. In Experiment 1, adult participants drew 300 rectangles on a computer screens; variability in the Area, Shape and Location dimensions of the rectangles drawn was measured. One group of participants received reinforcement when they drew rectangles varying on all three dimensions (VAR) using a threshold contingency to determine reinforcement while another group received reinforcement regardless whether they varied on any of the dimensions of the rectangles drawn (YOKE). Results showed that the variability of each dimension, as measured by the U-value, was higher for the VAR group than for the YOKE group. In Experiment 2, three groups of adult participants received reinforcement when they varied on two of the three dimensions of the rectangles drawn. Results showed that reinforcing variability in the Shape and Location dimensions and in the Area and Location dimensions resulted in higher variability in these dimensions compared to the dimension where variability was not directly reinforced, as measured by U-values. However, for the group who received reinforcement when varying in the Area and Shape dimensions, the variability across the three dimensions did not differ. Generalisation of reinforced variability was examined by comparing the variability in dimensions that were not subject to reinforcement for varying from Experiment 1 and Experiment 2. For the Shape and Location dimensions, results showed that the variability was higher when the two dimensions occurred with other dimensions that were subject for reinforcement for varying compared to when they occurred with other dimensions that were not required to vary. However, no significant difference was found for the Area dimension. Therefore, there appeared to be generalisation of reinforced variability for only two of these three groups of participants, suggesting the dimensions were not orthogonal. The non-orthogonality of the three dimensions of the rectangles was suggested as a possible confounding variable so that it not be concluded that generalisation of reinforced variability across dimensions had been obtained. Experiment 3 used a task with more independent dimensions (Shape, Colour and Pattern) to control for the non-orthogonality issue found in Experiment 2. Adult participants created objects by selecting elements from three dimensions on the computer screen. One group of participants received reinforcement when they varied on the use of elements on all three dimensions using a threshold contingency while the other group received reinforcement independent of the elements chosen. Results showed that the variability in using the elements for all three dimensions was similar between the two groups; whether the group received reinforcement when the dimensions varied did not make a difference. Inspection of the elements selected on each trial revealed that participants from both groups, in general, responded in stereotypic patterns; however, the stereotypy in the responses was not picked up by the measure of U-value. In Experiment 4, a new task asking participants to colour t-shirts on the computer screen was created to examine the effect of reinforcement on the variability in colours used. Adult and adolescent participants were instructed to colour t-shirts on the computer screen in three phases. In Phase 1, no feedback was provided; in Phase 2, positive feedback was provided when participants used a colour they had not used before (including those used in Phase 1); and in Phase 3, no feedback was provided. Results showed that, after reinforcement for using novel colours, participants who used only a small number of colours initially used more colours; however, the increase was not found for participants who initially used a moderate or high number of colours. U-value as the measure of variability was examined by using two sets of simulated data. It was found that highly stereotypic response patterns can result in extremely high U-values. Also, the number of options/categories used affects the values of U, which makes comparisons between groups difficult. Overall, results from these experiments support the notion that the level of variability in responses can be controlled by reinforcement. It is possible that learned variability can generalise over unreinforced dimensions. However, the examination of generalisation of reinforced variability across dimensions is not conclusive when the dimensions are interdependent. The results and simulation showed that U-value as a measure of variability needs to be used with caution because it does not capture potential stereotypy in responses and the values of U can be ambiguous.

year: 2016

title: Real world initiation of newly funded empagliflozin and dulaglutide under special authority for patients with type 2 diabetes in New Zealand

authors: Chepulis, Lynne Merran

subjects: GLP1RA

abstract: Background: Type 2 diabetes (T2D) is sub-optimally managed for many in Aotearoa New Zealand, and disproportionately affects Māori and Pacific peoples. In February 2021, SGLT2i/GLP1RA agents were funded for use for the first time with prioritisation for Māori, Pacific and those with cardiovascular and/or renal disease or risk (CVRD). This study evaluates the impact of health system factors on initiation of SGLT2i/GLP1RA therapy. 

Methods: Primary care data was collected for patients with T2D aged 18–75 years from four primary care organisations (302 general practices) in the Auckland / Waikato region of New Zealand (Feb 2021 – July 2022). Initiation of SGLT2i/GLP1RA therapy was reviewed by patient (age, gender, ethnicity, CVRD status) and health system variables (funding, provider type, staffing, patient numbers, rurality, after-hours access). Logistic regression was used to estimate the odds ratio of a patient being dispensed SGLT2i/GLP1RA. 

Results: Of 57,743 patients with T2D, 22,331 were eligible for funded SGLT2i/GLP1RA access and 10,272 of those (46.0%) were prescribed. Initiation of therapy was highest in Māori (50.8%) and Pacific (48.8%) patients (vs. 36·2–40·7% of other ethnic groups; P < 0.001), but was comparable in those with and without CVRD (47·1% vs. 48·9%; P = 0.2). Prescribing was highest in practices with higher doctor/patient numbers, low-cost fees, Māori health providers and clinics without after-hours access.

Conclusion: Prioritised access for SGLT2i/GLP1RA appears to be associated with a reduced health equity gap for Māori and Pacific patients with T2D in NZ, but work is required to improve prescribing for patients with CVRD.

text: Real world initiation of newly funded empagliflozin and dulaglutide under special authority for patients with type 2 diabetes in New Zealand Background: Type 2 diabetes (T2D) is sub-optimally managed for many in Aotearoa New Zealand, and disproportionately affects Māori and Pacific peoples. In February 2021, SGLT2i/GLP1RA agents were funded for use for the first time with prioritisation for Māori, Pacific and those with cardiovascular and/or renal disease or risk (CVRD). This study evaluates the impact of health system factors on initiation of SGLT2i/GLP1RA therapy. 

Methods: Primary care data was collected for patients with T2D aged 18–75 years from four primary care organisations (302 general practices) in the Auckland / Waikato region of New Zealand (Feb 2021 – July 2022). Initiation of SGLT2i/GLP1RA therapy was reviewed by patient (age, gender, ethnicity, CVRD status) and health system variables (funding, provider type, staffing, patient numbers, rurality, after-hours access). Logistic regression was used to estimate the odds ratio of a patient being dispensed SGLT2i/GLP1RA. 

Results: Of 57,743 patients with T2D, 22,331 were eligible for funded SGLT2i/GLP1RA access and 10,272 of those (46.0%) were prescribed. Initiation of therapy was highest in Māori (50.8%) and Pacific (48.8%) patients (vs. 36·2–40·7% of other ethnic groups; P < 0.001), but was comparable in those with and without CVRD (47·1% vs. 48·9%; P = 0.2). Prescribing was highest in practices with higher doctor/patient numbers, low-cost fees, Māori health providers and clinics without after-hours access.

Conclusion: Prioritised access for SGLT2i/GLP1RA appears to be associated with a reduced health equity gap for Māori and Pacific patients with T2D in NZ, but work is required to improve prescribing for patients with CVRD.

year: 2025