University of Aberdeen

About: University of Aberdeen is a education organization based out in Aberdeen, United Kingdom. It is known for research contribution in the topics: Population & Randomized controlled trial. The organization has 21174 authors who have published 49962 publications receiving 2105479 citations. The organization is also known as: Aberdeen University.

Linking drought‐resistance mechanisms to drought avoidance in upland rice using a QTL approach: progress and new opportunities to integrate stomatal and mesophyll responses

Abstract: The advent of saturated molecular maps promised rapid progress towards the improvement of crops for genetically complex traits like drought resistance via analysis of quantitative trait loci (QTL). Progress with the identification of QTLs for drought resistance-related traits in rice is summarized here with the emphasis on a mapping population of a cross between drought-resistant varieties Azucena and Bala. Data which have used root morphological traits and indicators of drought avoidance in field-grown plants are reviewed, highlighting problems and uncertainties with the QTL approach. The contribution of root-growth QTLs to drought avoidance appears small in the experiments so far conducted, and the limitations of screening methodologies and the involvement of shoot-related mechanisms of drought resistance are studied. When compared to Azucena, Bala has been observed to have highly sensitive stomata, does not roll its leaves readily, has a greater ability to adjust osmotically, slows growth more rapidly when droughted and has a lower water-use efficiency. It is also a semi-dwarf variety and hence has a different canopy structure. There is a need to clarify the contribution of the shoot to drought resistance from the level of the biochemistry of photosynthesis through stomatal behaviour and leaf anatomy to canopy architecture. Recent advances in studying the physical and biochemical processes related to water use and drought stress offer the opportunity to advance a more holistic understanding of drought resistance. These include the potential use of infrared thermal imaging to study energy balance, integrated and online stable isotope analysis to dissect processes involved in carbon dioxide fixation and water evaporation, and leaf fluorescence to monitor photosynthesis and photochemical quenching. Justification and a strategy for this integrated approach is described, which has relevance to the study of drought resistance in most crops.

Personalised care planning for adults with chronic or long-term health conditions

Abstract: © 2015 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd. Background: Personalised care planning is a collaborative process used in chronic condition management in which patients and clinicians identify and discuss problems caused by or related to the patient's condition, and develop a plan for tackling these. In essence it is a conversation, or series of conversations, in which they jointly agree goals and actions for managing the patient's condition. Objectives: To assess the effects of personalised care planning for adults with long-term health conditions compared to usual care (i.e. forms of care in which active involvement of patients in treatment and management decisions is not explicitly attempted or achieved). Search methods: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, PsycINFO, ProQuest, clinicaltrials.gov and WHO International Clinical Trials Registry Platform to July 2013. Selection criteria: We included randomised controlled trials and cluster-randomised trials involving adults with long-term conditions where the intervention included collaborative (between individual patients and clinicians) goal setting and action planning. We excluded studies where there was little or no opportunity for the patient to have meaningful influence on goal selection, choice of treatment or support package, or both. Data collection and analysis: Two of three review authors independently screened citations for inclusion, extracted data, and assessed risk of bias. The primary outcomes were effects on physical health, psychological health, subjective health status, and capabilities for self management. Secondary outcomes included effects on health-related behaviours, resource use and costs, and type of intervention. A patient advisory group of people with experience of living with long-term conditions advised on various aspects of the review, including the protocol, selection of outcome measures and emerging findings. Main results: We included 19 studies involving a total of 10,856 participants. Twelve of these studies focused on diabetes, three on mental health, one on heart failure, one on end-stage renal disease, one on asthma, and one on various chronic conditions. All 19 studies included components that were intended to support behaviour change among patients, involving either face-to-face or telephone support. All but three of the personalised care planning interventions took place in primary care or community settings; the remaining three were located in hospital clinics. There was some concern about risk of bias for each of the included studies in respect of one or more criteria, usually due to inadequate or unclear descriptions of research methods. Physical health Nine studies measured glycated haemoglobin (HbA1c), giving a combined mean difference (MD) between intervention and control of -0.24% (95% confidence interval (CI) -0.35 to -0.14), a small positive effect in favour of personalised care planning compared to usual care (moderate quality evidence). Six studies measured systolic blood pressure, a combined mean difference of -2.64 mm/Hg (95% CI -4.47 to -0.82) favouring personalised care (moderate quality evidence). The pooled results from four studies showed no significant effect on diastolic blood pressure, MD -0.71 mm/Hg (95% CI -2.26 to 0.84). We found no evidence of an effect on cholesterol (LDL-C), standardised mean difference (SMD) 0.01 (95% CI -0.09 to 0.11) (five studies) or body mass index, MD -0.11 (95% CI -0.35 to 0.13) (four studies). A single study of people with asthma reported that personalised care planning led to improvements in lung function and asthma control. Psychological health Six studies measured depression. We were able to pool results from five of these, giving an SMD of -0.36 (95% CI -0.52 to -0.20), a small effect in favour of personalised care (moderate quality evidence). The remaining study found greater improvement in the control group than the intervention group. Four other studies used a variety of psychological measures that were conceptually different so could not be pooled. Of these, three found greater improvement for the personalised care group than the usual care group and one was too small to detect differences in outcomes. Subjective health status Ten studies used various patient-reported measures of health status (or health-related quality of life), including both generic health status measures and condition-specific ones. We were able to pool data from three studies that used the SF-36 or SF-12, but found no effect on the physical component summary score SMD 0.16 (95% CI -0.05 to 0.38) or the mental component summary score SMD 0.07 (95% CI -0.15 to 0.28) (moderate quality evidence). Of the three other studies that measured generic health status, two found improvements related to personalised care and one did not. Four studies measured condition-specific health status. The combined results showed no difference between the intervention and control groups, SMD -0.01 (95% CI -0.11 to 0.10) (moderate quality evidence). Self-management capabilities Nine studies looked at the effect of personalised care on self-management capabilities using a variety of outcome measures, but they focused primarily on self efficacy. We were able to pool results from five studies that measured self efficacy, giving a small positive result in favour of personalised care planning: SMD 0.25 (95% CI 0.07 to 0.43) (moderate quality evidence). A further five studies measured other attributes that contribute to self-management capabilities. The results from these were mixed: two studies found evidence of an effect on patient activation, one found an effect on empowerment, and one found improvements in perceived interpersonal support. Other outcomes Pooled data from five studies on exercise levels showed no effect due to personalised care planning, but there was a positive effect on people's self-reported ability to carry out self-care activities: SMD 0.35 (95% CI 0.17 to 0.52). We found no evidence of adverse effects due to personalised care planning. The effects of personalised care planning were greater when more stages of the care planning cycle were completed, when contacts between patients and health professionals were more frequent, and when the patient's usual clinician was involved in the process. Authors' conclusions: Personalised care planning leads to improvements in certain indicators of physical and psychological health status, and people's capability to self-manage their condition when compared to usual care. The effects are not large, but they appear greater when the intervention is more comprehensive, more intensive, and better integrated into routine care.

Physical activity and resting metabolic rate

Abstract: The direct effects of physical activity interventions on energy expenditure are relatively small when placed in the context of total daily energy demands. Hence, the suggestion has been made that exercise produces energetic benefits in other components of the daily energy budget, thus generating a net effect on energy balance much greater than the direct energy cost of the exercise alone. Resting metabolic rate (RMR) is the largest component of the daily energy budget in most human societies and, therefore, any increases in RMR in response to exercise interventions are potentially of great importance. Animal studies have generally shown that single exercise events and longer-term training produce increases in RMR. This effect is observed in longer-term interventions despite parallel decreases in body mass and fat mass. Flight is an exception, as both single flights and long-term flight training induce reductions in RMR. Studies in animals that measure the effect of voluntary exercise regimens on RMR are less commonly performed and do not show the same response as that to forced exercise. In particular, they indicate that exercise does not induce elevations in RMR. Many studies of human subjects indicate a short-term elevation in RMR in response to single exercise events (generally termed the excess post-exercise O2 consumption; EPOC). This EPOC appears to have two phases, one lasting < 2 h and a smaller much more prolonged effect lasting up to 48 h. Many studies have shown that long-term training increases RMR, but many other studies have failed to find such effects. Data concerning long-term effects of training are potentially confounded by some studies not leaving sufficient time after the last exercise bout for the termination of the long-term EPOC. Long-term effects of training include increases in RMR due to increases in lean muscle mass. Extreme interventions, however, may induce reductions in RMR, in spite of the increased lean tissue mass, similar to the changes observed in animals in response to flight.