Mutation of Arabidopsis SPLICEOSOMAL TIMEKEEPER LOCUS1 Causes Circadian Clock Defects

The circadian clock plays a crucial role in coordinating plant metabolic and physiological functions with predictable environmental variables, such as dusk and dawn, while also modulating responses to biotic and abiotic challenges. Much of the initial characterization of the circadian system has focused on transcriptional initiation, but it is now apparent that considerable regulation is exerted after this key regulatory step. Transcript processing, protein stability, and cofactor availability have all been reported to influence circadian rhythms in a variety of species. We used a genetic screen to identify a mutation within a putative RNA binding protein (SPLICEOSOMAL TIMEKEEPER LOCUS1 [STIPL1]) that induces a long circadian period phenotype under constant conditions. STIPL1 is a homolog of the spliceosomal proteins TFP11 (Homo sapiens) and Ntr1p (Saccharomyces cerevisiae) involved in spliceosome disassembly. Analysis of general and alternative splicing using a high-resolution RT-PCR system revealed that mutation of this protein causes less efficient splicing of most but not all of the introns analyzed. In particular, the altered accumulation of circadian-associated transcripts may contribute to the observed mutant phenotype. Interestingly, mutation of a close homolog of STIPL1, STIP-LIKE2, does not cause a circadian phenotype, which suggests divergence in function between these family members. Our work highlights the importance of posttranscriptional control within the clock mechanism. © 2012 American Society of Plant Biologists. All rights reserved

Can mutation and selection explain virulence in human P. falciparum infections?

BACKGROUND: Parasites incur periodic mutations which must ultimately be eliminated to maintain their genetic integrity. METHODS: It is hypothesised that these mutations are eliminated not by the conventional mechanisms of competition between parasites in different hosts but primarily by competition between parasites within the same infection. RESULTS: This process is enhanced by the production of a large number of parasites within individual infections, and this may significantly contribute to parasitic virulence. CONCLUSIONS: Several features of the most virulent human malaria parasite Plasmodium falciparum can usefully be re-interpreted in this light and lend support to this interpretation. More generally, it constitutes a novel explanation for the evolution of virulence in a wider range of microparasites

Post-operative bilateral adrenal haemorrhage: A case report

AbstractINTRODUCTIONBilateral adrenal haemorrhage is a rare, but serious, illness carrying an estimated 15% mortality.1,2 The majority of cases occur in patients with acute, stressful illness, however the exact mechanism underlying adrenal haemorrhage remains unclear. This medical emergency carries significant diagnostic difficulty4 with non-specific clinical symptoms and variations in electrolyte abnormalities. Timely treatment is important as it prevents both the acute and long-term sequelae of adrenal failure.PRESENTATION OF CASEThis report describes a medical emergency in a surgical patient following emergency surgery for intra-abdominal sepsis. The patient reported non-specific symptoms of confusion, mild pyrexia and vague abdominal pain during the post-operative phase, with subtle electrolyte abnormalities and a low serum cortisol suggestive of adrenal crisis. Timely medical treatment, with intravenous hydrocortisone and intensive monitoring, and appropriate medical follow-up with addition of long-term fludrocortisone resulted in a satisfactory outcome.DISCUSSIONThis report describes a potentially life-threatening complication of intra-abdominal sepsis with adrenal crisis secondary to bilateral adrenal haemorrhage. In particular, this case highlights the diagnostic difficulty in such surgical patients due to vague symptoms and, in this case, the presence of a presentation variant with acute hyponatraemia and normal potassium.CONCLUSIONThis case highlights the importance of awareness of both the symptoms and signs and variation in electrolyte profile when assessing surgical patients post-operatively. In addition, this case highlights the benefit of early recognition and initiation of treatment and the importance of follow-up as long-term medical management is often required to prevent further relapse

Measuring Metacognition in Cancer: Validation of the Metacognitions Questionnaire 30 (MCQ-30)

Objective The Metacognitions Questionnaire 30 assesses metacognitive beliefs and processes which are central to the metacognitive model of emotional disorder. As recent studies have begun to explore the utility of this model for understanding emotional distress after cancer diagnosis, it is important also to assess the validity of the Metacognitions Questionnaire 30 for use in cancer populations. Methods 229 patients with primary breast or prostate cancer completed the Metacognitions Questionnaire 30 and the Hospital Anxiety and Depression Scale pre-treatment and again 12 months later. The structure and validity of the Metacognitions Questionnaire 30 were assessed using factor analyses and structural equation modelling. Results Confirmatory and exploratory factor analyses provided evidence supporting the validity of the previously published 5-factor structure of the Metacognitions Questionnaire 30. Specifically, both pre-treatment and 12 months later, this solution provided the best fit to the data and all items loaded on their expected factors. Structural equation modelling indicated that two dimensions of metacognition (positive and negative beliefs about worry) were significantly associated with anxiety and depression as predicted, providing further evidence of validity. Conclusions These findings provide initial evidence that the Metacognitions Questionnaire 30 is a valid measure for use in cancer populations

To What Extent Can UAV Photogrammetry Replicate UAV LiDAR to Determine Forest Structure? A Test in Two Contrasting Tropical Forests

Tropical forests are complex multi-layered systems, with the height and three-dimensional (3D) structure of trees influencing the carbon and biodiversity they contain. Fine-resolution 3D data on forest structure can be collected reliably with Light Detection and Ranging (LiDAR) sensors mounted on aircraft or Unoccupied Aerial Vehicles (UAVs), however, they remain expensive to collect and process. Structure-from-Motion (SfM) Digital Aerial Photogrammetry (SfM-DAP), which relies on photographs taken of the same area from multiple angles, is a lower-cost alternative to LiDAR for generating 3D data on forest structure. Here, we evaluate how SfM-DAP compares to LiDAR data acquired concurrently using a fixed-wing UAV, over two contrasting tropical forests in Gabon and Peru. We show that SfM-DAP data cannot be used in isolation to measure key aspects of forest structure, including canopy height (%Bias: 40%–50%), fractional cover, and gap fraction, due to difficulties measuring ground elevation, even under low tree cover. However, we find even in complex forests, SfM-DAP is an effective means of measuring top-of-canopy structure, including surface heterogeneity, and is capable of producing similar measurements of vertical structure as LiDAR. Thus, in areas where ground height is known, SfM-DAP is an effective method for measuring important aspects of forest structure, including canopy height, and gaps, however, without ground data, SfM-DAP is of more limited utility. Our results support the growing evidence base pointing to photogrammetry as a viable complement, or alternative, to LiDAR, capable of providing much needed information to support the mapping and monitoring of biomass and biodiversity

Adoption of precision livestock farming technologies has the potential to mitigate greenhouse gas emissions from beef production

To meet the objectives of the Paris Agreement, which aims to limit the increase in global temperature to 1.5°C, significant greenhouse gas (GHG) emission reductions will be needed across all sectors. This includes agriculture which accounts for a significant proportion of global GHG emissions. There is therefore a pressing need for the uptake of new technologies on farms to reduce GHG emissions and move towards current policy targets. Recently, precision livestock farming (PLF) technologies have been highlighted as a promising GHG mitigation strategy to indirectly reduce GHG emissions through increasing production efficiencies. Using Scotland as a case study, average data from the Scottish Cattle Tracing System (CTS) was used to create two baseline beef production scenarios (one grazing and one housed system) and emission estimates were calculated using the Agrecalc carbon footprinting tool. The effects of adopting various PLF technologies on whole farm and product emissions were then modelled. Scenarios included adoption of automatic weigh platforms, accelerometer based sensors for oestrus detection (fertility sensors) and accelerometer-based sensors for early disease detection (health sensors). Model assumptions were based on validated technologies, direct experience from farms and expert opinion. Adoption of all three PLF technologies reduced total emissions (kgCO2e) and product emissions (kg CO2e/kg deadweight) in both the grazing and housed systems. In general, adoption of PLF technologies had a larger impact in the housed system than in the grazing system. For example, while health sensors reduced total emissions by 6.1% in the housed system, their impact was slightly lower in the grazing system at 4.4%. The largest reduction in total emissions was seen following the adoption of an automatic weight platform which reduced the age at slaughter by 3  months in the grazing system (6.8%) and sensors for health monitoring in the housed system (6.1%). Health sensors also resulted in the largest reduction in product emissions for both the housed (12.0%) and grazing systems (10.5%). These findings suggest PLF could be an effective GHG mitigation strategy for beef systems in Scotland. Although this study utilised data from beef farms in Scotland, comparable emission reductions are likely attainable in other European countries with similar farming systems

Adoption of precision livestock farming technologies has the potential to mitigate greenhouse gas emissions from beef production

To meet the objectives of the Paris Agreement, which aims to limit the increase in global temperature to 1.5°C, significant greenhouse gas (GHG) emission reductions will be needed across all sectors. This includes agriculture which accounts for a significant proportion of global GHG emissions. There is therefore a pressing need for the uptake of new technologies on farms to reduce GHG emissions and move towards current policy targets. Recently, precision livestock farming (PLF) technologies have been highlighted as a promising GHG mitigation strategy to indirectly reduce GHG emissions through increasing production efficiencies. Using Scotland as a case study, average data from the Scottish Cattle Tracing System (CTS) was used to create two baseline beef production scenarios (one grazing and one housed system) and emission estimates were calculated using the Agrecalc carbon footprinting tool. The effects of adopting various PLF technologies on whole farm and product emissions were then modelled. Scenarios included adoption of automatic weigh platforms, accelerometer based sensors for oestrus detection (fertility sensors) and accelerometer-based sensors for early disease detection (health sensors). Model assumptions were based on validated technologies, direct experience from farms and expert opinion. Adoption of all three PLF technologies reduced total emissions (kgCO2e) and product emissions (kg CO2e/kg deadweight) in both the grazing and housed systems. In general, adoption of PLF technologies had a larger impact in the housed system than in the grazing system. For example, while health sensors reduced total emissions by 6.1% in the housed system, their impact was slightly lower in the grazing system at 4.4%. The largest reduction in total emissions was seen following the adoption of an automatic weight platform which reduced the age at slaughter by 3  months in the grazing system (6.8%) and sensors for health monitoring in the housed system (6.1%). Health sensors also resulted in the largest reduction in product emissions for both the housed (12.0%) and grazing systems (10.5%). These findings suggest PLF could be an effective GHG mitigation strategy for beef systems in Scotland. Although this study utilised data from beef farms in Scotland, comparable emission reductions are likely attainable in other European countries with similar farming systems

The impacts of precision livestock farming tools on the greenhouse gas emissions of an average Scottish dairy farm

Precision livestock farming (PLF) tools are increasingly used in daily herd management to improve health, welfare, and overall production. While not intended to reduce greenhouse gas (GHG) emissions on farm, PLF tools can do so indirectly by improving overall efficiency, thereby reducing the emissions per unit of product. This work modelled the potential effects of commercially available PLF tools on whole enterprise and product emissions of two average Scottish dairy farm systems (an 8,000  L and 10,000  L herd) using the Agrecalc carbon foot printing tool. Scenarios modelled included an improvement infertility and an improvement in fertility and yield from the introduction of an accelerometer-based sensor, and an improvement in health from introduction of an accelerometer-based sensor, with and without the use of management interventions. Use of a sensor intended to improve fertility had the large streduction in total emissions (kg CO2e) of −1.42% for a 10,000  L farm, with management changes applied. The largest reduction in emissions from milk production (kg CO2e) of −2.31% was observed via fertility technology application in an 8,000  L farm, without management changes. The largest reduction in kg CO2e per kg fat and protein corrected milk of −6.72% was observed from an improvement in fertility and yield in a 10,000  L herd, with management changes. This study has highlighted the realistic opportunities available to dairy farmers in low and high input dairy systems to reduce their emissions through adoption of animal mounted PLF technologies