Loss of bone density and bone strength following premenopausal risk-reducing bilateral salpingo-oophorectomy: a prospective controlled study (WHAM Study).

Prophylactic oophorectomy is recommended for women at high risk for ovarian cancer, but the associated impact on bone health is of clinical concern. This prospective, controlled study demonstrated substantial loss of bone density and bone strength following surgical menopause. Postoperative hormone therapy alleviated, but not fully prevented, spinal bone loss. INTRODUCTION: This prospective study investigated bone health in women following premenopausal oophorectomy. METHODS: Dual-energy x-ray absorptiometry (DXA), peripheral quantitative computed tomography (pQCT), and pQCT-based finite element analysis (pQCT-FEA) were used to assess bone health between systemic hormone therapy (HT) users and non-users after premenopausal risk-reducing bilateral salpingo-oophorectomy (RRBSO) compared with premenopausal controls over 24-month follow-up. RESULTS: Mean age was 42.4 ± 2.6 years (n = 30) for the surgery group and 40.2 ± 6.3 years for controls (n = 42), and baseline bone measures were similar between groups. Compromised bone variables were observed at 24 months after RRBSO, among which areal bone mineral density (aBMD) at the lumbar spine, tibial volumetric cortical density (Crt vBMD), and tibial bending stiffness (kbend) had decreased by 4.7%, 1.0%, and 12.1%, respectively (all p < 0.01). In non-HT users, significant losses in lumbar spine (5.8%), total hip (5.2%), femoral neck (6.0%) aBMD, tibial Crt vBMD (2.3%), and kbend (14.8%) were observed at 24 months (all p < 0.01). HT prevented losses in kbend, tibial Crt vBMD, and aBMD, except for modest 2.3% loss at the lumbar spine (p = 0.01). CONCLUSION: This prospective, controlled study of bone health following RRBSO or premenopausal oophorectomy demonstrated substantial loss of bone density and bone strength following RRBSO. HT prevented loss of bone density and bone stiffness, although there was still a modest decrease in lumbar spine aBMD in HT users. These findings may inform decision-making about RRBSO and clinical management following premenopausal oophorectomy.

Peripheral quantitative computed tomography (pQCT)-based finite element analysis provides enhanced diagnostic performance in identifying non-vertebral fracture patients compared with dual-energy X-ray absorptiometry.

Due to limitations of the predominant clinical method for diagnosing osteoporosis, an engineering model based on a dedicated CT scanner for bone density and structure was applied in fracture patients and controls. Improved diagnostic performance was observed, which supports its potential use in future research and clinical practice. INTRODUCTION: Dual-energy X-ray absorptiometry (DXA), the predominant clinical method for diagnosing osteoporosis, has limitations in identifying individuals with increased fracture risk. Peripheral quantitative computed tomography (pQCT) provides additional information and can be used to generate finite element (FE) models from which bone strength properties can be estimated. We investigated the ability of pQCT-FE properties to distinguish peripheral low-trauma fracture patients from healthy controls, by comparison with DXA and standard pQCT. METHODS: One hundred and eight fracture patients (77 females aged 67.7 ± 7.9 years, 31 males aged 69.7 ± 8.9 years) were recruited from a hospital fracture liaison service. One hundred and twenty healthy community controls (85 females aged 69.8 ± 8.5 years, 35 males aged 68.9 ± 7.2 years) were recruited. RESULTS: Significant differences between groups were observed in pQCT-FE properties, especially at the 4% tibia site. Fracture odds increased most per standard deviation decrease in pQCT-FE at this location [shear stiffness estimate, kshear, in females, OR = 10.34, 95% CI (1.91, 43.98); bending stiffness estimate, kbend, in males, OR = 8.32, 95% CI (4.15, 33.84)]. Area under the receiver operating characteristics curve (AUROC) was observed to be highest with pQCT-FE properties at 4% the tibia site. In females, this was 0.83 for the pQCT-FE variable kshear, compared with 0.72 for DXA total hip bone density (TH aBMD) and 0.76 for pQCT tibia trabecular density (Trb vBMD); in males, this was 0.81 for the pQCT-FE variable kbend at the 4% tibia site, compared with 0.62 for TH aBMD and 0.71 for Trb vBMD. There were significant differences in AUROC between DXA and pQCT-FE variables in both females (p = 0.02) and males (p = 0.03), while no difference was observed in AUROC between primary pQCT and pQCT-FE variables. CONCLUSIONS: pQCT-FE modeling can provide enhanced diagnostic performance compared with DXA and, given its moderate cost, may be useful in clinical settings.

The novel fungal CYP51 inhibitor VT-1598 displays classic dose-dependent antifungal activity in murine models of invasive aspergillosis.

Aspergillus spp. infections remain a global concern, with ∼30% attributable mortality of invasive aspergillosis (IA). VT-1598 is a novel fungal CYP51 inhibitor designed for exquisite selectivity versus human CYP enzymes to achieve a maximal therapeutic index and therefore maximal antifungal efficacy. Previously, its broad-spectrum in vitro antifungal activity was reported. We report here the pharmacokinetics (PK) and pharmacodynamics (PD) of VT-1598 in neutropenic mouse models of IA. The plasma area-under-the-curve (AUC) of VT-1598 increased nearly linearly between 5 and 40 mg/kg after 5 days of QD administration (155 and 1033 µg*h/ml, respectively), with a further increase with 40 mg/kg BID dosing (1354 µg*h/ml). When A. fumigatus isolates with in vitro susceptibilities of 0.25 and 1.0 µg/ml were used in a disseminated IA model, VT-1598 treatment produced no decrease in kidney fungal burden at QD 10 mg/kg, intermediate decreases at QD 20 mg/kg and maximum or near maximum decreases at 40 mg/kg QD and BID. The PK/PD relationships of AUCfree/MIC for 1-log killing for the two strains were 5.1 and 1.6 h, respectively, similar to values reported for approved CYP51 inhibitors. In a survival study where animals were observed for 12 days after the last treatment, survival was 100% at the doses tested (20 and 40 mg/kg QD), and fungal burden remained suppressed even though drug wash-out was complete. Similar dose-dependent reductions in lung fungal burden were observed in a pulmonary model of IA. These data strongly support further exploration of VT-1598 for the treatment of this lethal mold infection.

Presentations to the emergency department with non-medical use of benzodiazepines and Z-drugs: profiling and relation to sales data.

BACKGROUND: Non-medical use of benzodiazepines and Z-drugs is common; however, there is limited information available on the extent of harm related to this in Europe, as well as the relationship between misuse and availability. AIM: To describe presentations to the emergency department in Europe related to the recreational use of benzodiazepines and Z-drugs and compare regional differences in these presentations with legal drug sales of benzodiazepines and Z-drugs within each country. METHODS: Emergency department presentations with recreational misuse of benzodiazepines and Z-drugs were obtained from the Euro-DEN dataset for the period from October 2013 to September 2015; data extracted included demographics, clinical features, reported coused drugs, and outcome data. Sales figures obtained by QuintilesIMS™ (Atlanta, Georgia) were used to compare regional differences in the proportion of benzodiazepines and Z-drugs in the emergency department presentations and legal drug sales across Europe. RESULTS: Over the 2 years, there were 2119 presentations to the Euro-DEN project associated with recreational use of benzodiazepines and/or Z-drugs (19.3% of all Euro-DEN presentations). Presentations with 25 different benzodiazepines and Z-drugs were registered in all countries, most (1809/2340 registered benzodiazepines and Z-drugs, 77.3%) of which were prescription drugs. In 24.9%, the benzodiazepine was not specified. Where the benzodiazepine/Z-drug was known, the most frequently used benzodiazepines and Z-drugs were respectively clonazepam (29.5% of presentations), diazepam (19.9%), alprazolam (11.7%), and zopiclone (9.4%). The proportions of types of benzodiazepines/Z-drugs related to ED-presentations varied between countries. There was a moderate (Spain, UK, Switzerland) to high (France, Ireland, Norway) positive correlation between ED presentations and sales data (Spearman Row's correlation 0.66-0.80, p < 0.005), with higher correlation in countries with higher ED presentation rates. CONCLUSION: Presentations to the emergency department associated with the non-medical use of benzodiazepines and/or Z-drugs are common, with variation in the benzodiazepines and/or Z-drugs between countries. There was a moderate to high correlation with sales data, with higher correlation in countries with higher ED presentation rates. However, this is not the only explanation for the variation in non-medical use and in the harm associated with the non-medical use of benzodiazepines/Z-drugs.

The novel fungal CYP51 inhibitor VT-1598 is efficacious alone and in combination with liposomal amphotericin B in a murine model of cryptococcal meningitis.

Objectives: Annual global deaths from cryptococcal meningitis (CM) are estimated at 180 000 and mortality is as high as 30%, even with optimal therapy. VT-1598 is a novel fungal CYP51 inhibitor with potent intrinsic antifungal activity against Cryptococcus. We report here VT-1598's in vivo antifungal activity in a murine model of CM. Methods: Single-dose plasma and brain pharmacokinetics in mice and MIC for Cryptococcus neoformans H99 were determined prior to efficacy studies. Short-course monotherapy and combination doses were explored with the endpoint of brain fungal burden. A survival study was also conducted using monotherapy treatment with fungal burden measured after a 6 day drug washout. Results: Oral doses of VT-1598 had good plasma and brain exposure and resulted in significant (P < 0.0001) and dose-dependent reductions in brain fungal burden, reaching a 6 log10 reduction. Unlike either positive drug control (fluconazole or liposomal amphotericin B), both mid and high doses of VT-1598 reduced fungal burden to below levels measured at the start of treatment. When VT-1598 was dosed in the survival study, no VT-1598-treated animal succumbed to the infection. Whereas fluconazole showed a 2.5 log10 increase in fungal burden after the 6 day washout, the VT-1598 mid- and high-dose animals showed almost no regrowth (<0.5 log10). In a separate fungal burden study using suboptimal doses of VT-1598 and liposomal amphotericin B to probe for combination effects, each combination had a positive effect relative to corresponding monotherapies. Conclusions: These pre-clinical in vivo data strongly support clinical investigation of VT-1598 as a novel therapy for this lethal infection.

Efficient parameter sensitivity computation for spatially extended reaction networks.

Reaction-diffusion models are widely used to study spatially extended chemical reaction systems. In order to understand how the dynamics of a reaction-diffusion model are affected by changes in its input parameters, efficient methods for computing parametric sensitivities are required. In this work, we focus on the stochastic models of spatially extended chemical reaction systems that involve partitioning the computational domain into voxels. Parametric sensitivities are often calculated using Monte Carlo techniques that are typically computationally expensive; however, variance reduction techniques can decrease the number of Monte Carlo simulations required. By exploiting the characteristic dynamics of spatially extended reaction networks, we are able to adapt existing finite difference schemes to robustly estimate parametric sensitivities in a spatially extended network. We show that algorithmic performance depends on the dynamics of the given network and the choice of summary statistics. We then describe a hybrid technique that dynamically chooses the most appropriate simulation method for the network of interest. Our method is tested for functionality and accuracy in a range of different scenarios.

Impact of insulin initiation on glycaemic variability and glucose profiles in a primary healthcare Type 2 diabetes cohort: analysis of continuous glucose monitoring data from the INITIATION study.

AIM: To use continuous glucose monitoring to examine the effects of insulin initiation with glargine, with or without glulisine, on glycaemic variability and glycaemia in a cohort of people with Type 2 diabetes receiving maximum oral hypoglycaemic agents in primary healthcare. METHODS: We conducted a post hoc analysis of continuous glucose monitoring data from 89 participants at baseline and at 24 weeks after insulin commencement. Indicators of glycaemic variability (standard deviation, J-index and mean amplitude of glycaemic excursion) and glycaemia (HbA1c , mean glucose, area under the glucose-time curve) were assessed. Multi-level regression analysis was used to identify the predictors of change. RESULTS: Complete glycaemic variability data were available for 78 participants. Of these participants, 41% were women, their mean (sd) age was 59.2 (10.4) years, the median (interquartile range) diabetes duration was 10.4 (6.5, 13.3) years and the median (interquartile range) baseline HbA1c was 82.5 (71.6, 96.7) mmol/mol [9.7 (8.7, 11.0)%]. At baseline, BMI correlated negatively with standard deviation (r = -0.30) and mean amplitude of glycaemic excursion (r = -0.26), but not with J-index; HbA1c correlated with J-index (r = 0.61) but not with mean amplitude of glycaemic excursion and standard deviation. After insulin initiation the mean (sd) glucose level decreased [from 12.0 (3.0) to 8.5 (1.6) mmol/l; P < 0.001], as did the median (interquartile range) J-index [from 66.9 (47.7, 95.1) to 36.9 (27.6, 49.8) mmol/l; P < 0.001]. Baseline HbA1c correlated with a greater J-index reduction (r = -0.45; P < 0.001). The mean amplitude of glycaemic excursion and standard deviation values were unchanged. The baseline temporal profile, showing elevated postprandial morning glucose levels, was unchanged after insulin initiation, despite an overall reduction in glycaemia. CONCLUSION: Insulin initiation reduced hyperglycaemia but did not alter glycaemic variability in adults with Type 2 diabetes receiving maximum oral hypoglycaemic agents. The most significant postprandial excursions were seen in the morning, which identifies prebreakfast as the most effective target for short-acting insulin therapy.

An adaptive multi-level simulation algorithm for stochastic biological systems.

Discrete-state, continuous-time Markov models are widely used in the modeling of biochemical reaction networks. Their complexity often precludes analytic solution, and we rely on stochastic simulation algorithms (SSA) to estimate system statistics. The Gillespie algorithm is exact, but computationally costly as it simulates every single reaction. As such, approximate stochastic simulation algorithms such as the tau-leap algorithm are often used. Potentially computationally more efficient, the system statistics generated suffer from significant bias unless tau is relatively small, in which case the computational time can be comparable to that of the Gillespie algorithm. The multi-level method [Anderson and Higham, "Multi-level Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics," SIAM Multiscale Model. Simul. 10(1), 146-179 (2012)] tackles this problem. A base estimator is computed using many (cheap) sample paths at low accuracy. The bias inherent in this estimator is then reduced using a number of corrections. Each correction term is estimated using a collection of paired sample paths where one path of each pair is generated at a higher accuracy compared to the other (and so more expensive). By sharing random variables between these paired paths, the variance of each correction estimator can be reduced. This renders the multi-level method very efficient as only a relatively small number of paired paths are required to calculate each correction term. In the original multi-level method, each sample path is simulated using the tau-leap algorithm with a fixed value of τ. This approach can result in poor performance when the reaction activity of a system changes substantially over the timescale of interest. By introducing a novel adaptive time-stepping approach where τ is chosen according to the stochastic behaviour of each sample path, we extend the applicability of the multi-level method to such cases. We demonstrate the efficiency of our method using a number of examples.

Deriving appropriate boundary conditions, and accelerating position-jump simulations, of diffusion using non-local jumping.

In this paper we explore lattice-based position-jump models of diffusion, and the implications of introducing non-local jumping; particles can jump to a range of nearby boxes rather than only to their nearest neighbours. We begin by deriving conditions for equivalence with traditional local jumping models in the continuum limit. We then generalize a previously postulated implementation of the Robin boundary condition for a non-local process of arbitrary maximum jump length, and present a novel implementation of flux boundary conditions, again generalized for a non-local process of arbitrary maximum jump length. In both these cases we validate our results using stochastic simulation. We then proceed to consider two variations on the basic diffusion model: a hybrid local/non-local scheme suitable for models involving sharp concentration gradients, and the implementation of biased jumping. In all cases we show that non-local jumping can deliver substantial time savings for stochastic simulations.

Contemporary pollen-mediated gene immigration reflects the historical isolation of a rare, animal-pollinated shrub in a fragmented landscape.

Fragmentation is generally considered to have negative impacts on widespread outbreeders but impacts on gene flow and diversity in patchy, naturally rare, self-compatible plant species remain unclear. We investigated diversity, gene flow and contemporary pollen-mediated gene immigration in the rare, narrowly distributed endemic shrub Calothamnus quadrifidus ssp. teretifolius. This taxon occurs in an internationally recognized biodiversity hotspot subjected to recent human-induced fragmentation and the condition of the remnants ranges from intact to highly degraded. Using microsatellites, we found that inbreeding, historically low gene flow and significant population differentiation have characterized the genetic system of C. quadrifidus ssp. teretifolius. Inbreeding arises from self-pollination, a small amount of biparental inbreeding and significant correlation of outcross paternity but fecundity was high suggesting populations might have purged their lethals. Paternity analyses show that pollinators can move pollen over degraded and intact habitat but populations in both intact and degraded remnants had few pollen parents per seed parent and low pollen immigration. Genetic diversity did not differ significantly between intact and degraded remnants but there were signs of genetic bottlenecks and reduced diversity in some degraded remnants. Overall, our study suggests human-induced fragmentation has not significantly changed the mating system, or pollen immigration to, remnant populations and therefore genetic connectivity need not be the highest conservation priority. Rather, for rare species adapted to higher levels of inbreeding, conservation efforts may be best directed to managing intact habitats and ecosystem processes.

Hospital-wide healthcare-associated carbapenemase-producing Enterobacterales outbreak: risks of electric floor scrubbers in catering facilities and kitchens.

BACKGROUND: Carbapenemase-producing Enterobacterales (CPE) are associated with poor clinical outcomes and can spread rapidly in healthcare settings. Environmental reservoirs are increasingly recognized as playing an important part in some nosocomial outbreaks. AIM: To describe the investigation and control of a CPE outbreak, lasting several years, across two separate hospital sites within one organization. METHODS: Investigation of multiple ward-level CPE cross-transmissions with a number of sporadic cases. Environmental sampling of ward environments, catering facilities and electric floor scrubbers was undertaken. FINDINGS: Eleven patients over a 19-month period were identified as carrying healthcare-associated New Delhi metallo-beta-lactamase (NDM)-producing Enterobacter cloacae, and a further patient carried NDM Escherichia coli. E. cloacae isolates were indistinguishable on pulsed-field gel electrophoresis typing, supporting acquisition with a single point source. Environmental sampling found contamination of the electric floor scrubbers used for cleaning the hospital catering facilities and in the associated toilets. Standard outbreak response measures achieved control of ward outbreaks. Sporadic cases and hospital-wide cross-transmission were controlled after interventions on the central food-handling unit and by decommissioning affected floor scrubbers. Electric floor scrubbers were found to have the potential to disperse Gram-negative bacteria into the surrounding environment under experimental conditions. CONCLUSION: This outbreak report demonstrates that catering facilities and kitchens can be involved in widespread healthcare outbreaks of enteric organisms. This is also the first report of the potential role of electric floor scrubbers in causing significant environmental contamination with CPE which may indicate a role in nosocomial transmission.

Insulin-like growth factor binding protein-3 inhibits monocyte adhesion to retinal endothelial cells in high glucose conditions.

PURPOSE: Insulin-like growth factor binding protein-3 (IGFBP-3) is cytoprotective in the retina. The goal of this study was to investigate whether IGFBP-3 inhibits monocyte-endothelial cell adhesion associated with hyperglycemia. METHODS: Human retinal vascular endothelial cells (RECs) were grown in normal (5 mM), medium (15 mM), or high glucose medium (25 mM) for 72 h. After 48 h, cells were transfected with endothelial-cell-specific, non-IGF binding IGFBP-3 plasmid DNA (IGFBP-3NB) at 1 µg/ml for 24 h. Cells were serum starved for 16 h and treated with tumor necrosis factor-alpha (TNF-α; 10 ng/ml) for 4 h. Cell proteins were extracted and analyzed for intercellular adhesion molecule-1 (ICAM-1) expression with enzyme-linked immunosorbent assay. Additional RECs were plated onto attachment factor-coated slides, grown to 90% confluence in high glucose medium, and transfected with IGFBP-3 NB plasmid DNA or ICAM-1 small interfering RNA before treatment with or without TNF-α (10 ng/ml) for 4 h. Slides were then mounted in a parallel-plate flow chamber and subjected to a continuous flow of U937 human monocytes (10(5)/ml) in culture medium at shear stresses of 2 dynes/cm(2), with continual exposure to TNF-α. RESULTS: In high ambient glucose, overexpression of IGFBP-3 in RECs significantly decreased ICAM-1 expression when compared to the TNF-α-treated samples, whereas TNF-α increased monocyte-endothelial cell adhesion. IGFBP-3 significantly decreased monocyte adhesion to RECs in the high glucose condition. RECs transfected with ICAM-1 siRNA also had a decreased number of monocytes attached compared with the scrambled siRNA control. CONCLUSIONS: Data suggest that IGFBP-3 reduces monocyte-endothelial cell adhesion through decreased ICAM-1 levels in a hyperglycemic environment. This is the first demonstration of the role of IGFBP-3 in inhibiting monocyte-endothelial cell adhesion.

Mutation in codon 713 of the beta amyloid precursor protein gene presenting with schizophrenia.

Following reports of mutations of codon 717 in exon 17 of the amyloid precursor protein (APP) gene in early-onset familial Alzheimer's disease, we screened exon 17 for new mutations in presenile dementia. The majority of the 105 patients screened had definite or probable Alzheimer's disease, but we also included atypical cases and some chronic schizophrenics. We identified a single abnormal case--a chronic schizophrenic with cognitive defects. Sequencing revealed a C to T nucleotide substitution which produces an alanine to valine change at codon 713. We were unable to detect the mutation in the remaining members of the original cohort nor in a further 100 chronic schizophrenics and 100 non-demented controls. Nonetheless, the position of the mutation in a critical portion of the APP gene suggests that it may well prove to be pathogenic.

Prevalence of gestational diabetes mellitus, maternal obesity and associated perinatal outcomes over 10 years in an Australian tertiary maternity provider.

BACKGROUND: The International Association of Diabetes in Pregnancy Study Groups (IADPSG) gestational diabetes mellitus (GDM) criteria have been heavily scrutinised with concerns that the consequent GDM prevalence increase has not been associated with improved perinatal outcomes. AIMS: At a tertiary hospital in Melbourne, Australia we aimed to evaluate prevalence trends for GDM, type 2 diabetes (T2DM), maternal obesity and large-for-gestational age (LGA) and assess changes in perinatal outcomes following IADPSG criteria uptake in 2015. METHODS: A retrospective cohort study of singleton births from 20 weeks' gestation was conducted between 1st January 2011 and 31st December 2020. Maternal characteristics and perinatal outcomes were extracted from medical records. RESULTS: 52,795 pregnancies were included. GDM prevalence increased 2.7 times from 8.9% in 2011 to 23.7% in 2020 and increased annually by 8.59% (95%CI 7.77, 9.42). The rate of T2DM increased annually by 11.69% (95%CI 7.72, 16.67). Obesity prevalence increased annually by 3.18% (95%CI 2.58, 3.78). Induction of labour (IOL) prevalence increased annually by 8.35% (95%CI 5.69, 11.06). LGA prevalence remained unchanged. Increasing maternal obesity was the major contributing factor for LGA prevalence. CONCLUSIONS: From 2011 to 2020 GDM, obesity and T2DM prevalence increased significantly, with associated increased IOL, without change in LGA rates. Prospective studies are required to explore interactions between GDM, obesity, LGA and obstetric interventions.

New-onset diabetes after kidney transplantation-changes and challenges.

Despite substantial improvement in short-term results after kidney transplantation, increases in long-term graft survival have been modest. A significant impediment has been the morbidity and mortality attributable to cardiovascular disease (CVD). New-onset diabetes after transplantation (NODAT) is an independent predictor of cardiovascular events. This review examines recent literature surrounding diagnosis, outcomes and management of NODAT. Amongst otherwise heterogeneous studies, a common finding is the relative insensitivity of fasting blood glucose (FBG) as a screening test. Incorporating self-testing of afternoon capillary BG and glycohemoglobin (HbA(1c) ) detects many cases that would otherwise remain undetected without the oral glucose tolerance test (OGTT). Assessing the impact of NODAT on patient and graft survival is complicated by changes to diagnostic criteria, evolution of immunosuppressive regimens and increasing attention to cardiovascular risk management. Although recent studies reinforce a link between NODAT and death with a functioning graft (DWFG), there seems to be little effect on death-censored graft loss. The significance of glycemic control and diabetes resolution for patient outcomes remain notably absent from NODAT literature and treatment is also a neglected area. This review examines new and old therapeutic options, emphasizing the need to assess ß-cell pathology in customizing therapy. Finally, areas warranting further research are considered.

Evaluating the influence of different aspects of habitat fragmentation on mating patterns and pollen dispersal in the bird-pollinated Banksia sphaerocarpa var. caesia.

Habitat fragmentation can significantly affect mating and pollen dispersal patterns in plant populations, although the differential effects of the various aspects of fragmentation are poorly understood. In this study, we used eight microsatellite loci to investigate the effect of fragmentation on the mating system and pollen dispersal within one large and eight small population remnants of Banksia sphaerocarpa var. caesia, a bird-pollinated shrub in the southern agricultural region of Western Australia. The large population had a much larger neighbourhood size and lower selfing rate, maternal pollen pool differentiation and within-plot mean pollen dispersal distance than the small populations. Outcrossing was consistently high and ranged from 85.7% ± 2.6 to 98.5% ± 0.9, and mating patterns suggested nearest-neighbour pollination. Pollen immigration into small populations ranged from 2.8% ± 1.8 to 16.5% ± 3.2. Using the small populations, we tested for correlations between various fragmentation variables and mating system and pollen dispersal parameters. We found significant negative linear relationships between population isolation and outcrossing rate; population shape and neighbourhood size; and conspecific density and mean pollen dispersal distance. There were significant positive linear relationships between population shape and pollen pool differentiation and between population size and number of different fathers per seed crop. Our results suggest that birds may use a series of fragmented populations as a vegetation corridor while foraging across the landscape and that population connectivity is a critical determinant of pollinator visitation. Our results also suggest that the effect of a linear population shape on the mating system and pollen dispersal is routinely underestimated.

Sampling, storage and laboratory approaches for dissolved organic matter characterisation in freshwaters: Moving from nutrient fraction to molecular-scale characterisation.

Recent research has highlighted the importance of dissolved organic matter (DOM) for ecosystem function and because of this paradigm shift, it has become crucial to not only quantify its contribution to river nutrient loads but also to characterise its composition. There has been a significant research effort utilising optical methods, such as fluorescence and UV-Vis spectrophotometry, in order to start exploring DOM character. However, these methods still lack the granularity to understand the chemical composition at the molecular level, which is vital to properly understanding its functional role in freshwater ecosystems. As a direct result, there has been a shift towards including molecular-scale analyses to investigate the in-stream processing of the material. Alongside this, recent methodological advancements, particularly in mass spectrometry are opening new opportunities for probing one of the most complex environmental mixtures. However, in order to fully exploit these opportunities, it is key that the way that samples are collected, processed and stored is considered carefully such that sample integrity is maintained. There are additional challenges when collecting water samples for analysis at molecular scale, for example the ultra-low concentrations of individual compounds within DOM means that the samples are sensitive to contamination. This paper discusses current sample collection, processing and storage protocols for this C, N and P quantification and characterisation in freshwaters, and proposes a new standardised protocol suitable for both nutrient fraction quantification and molecular scale analyses, based on method development and testing undertaken in our UK Natural Environment Research Council large grant programme, characterising the nature, origins and ecological significance of Dissolved Organic Matter IN freshwater Ecosystems (DOMAINE).

Caffeine may disrupt the impact of real-time drowsiness on cognitive performance: a double-blind, placebo-controlled small-sample study.

Caffeine is widely used to promote alertness and cognitive performance under challenging conditions, such as sleep loss. Non-digestive modes of delivery typically reduce variability of its effect. In a placebo-controlled, 50-h total sleep deprivation (TSD) protocol we administered four 200 mg doses of caffeine-infused chewing-gum during night-time circadian trough and monitored participants' drowsiness during task performance with infra-red oculography. In addition to the expected reduction of sleepiness, caffeine was found to disrupt its degrading impact on performance errors in tasks ranging from standard cognitive tests to simulated driving. Real-time drowsiness data showed that caffeine produced only a modest reduction in sleepiness (compared to our placebo group) but substantial performance gains in vigilance and procedural decisions, that were largely independent of the actual alertness dynamics achieved. The magnitude of this disrupting effect was greater for more complex cognitive tasks.

A theoretical framework for transitioning from patient-level to population-scale epidemiological dynamics: influenza A as a case study.

Multi-scale epidemic forecasting models have been used to inform population-scale predictions with within-host models and/or infection data collected in longitudinal cohort studies. However, most multi-scale models are complex and require significant modelling expertise to run. We formulate an alternative multi-scale modelling framework using a compartmental model with multiple infected stages. In the large-compartment limit, our easy-to-use framework generates identical results compared to previous more complicated approaches. We apply our framework to the case study of influenza A in humans. By using a viral dynamics model to generate synthetic patient-level data, we explore the effects of limited and inaccurate patient data on the accuracy of population-scale forecasts. If infection data are collected daily, we find that a cohort of at least 40 patients is required for a mean population-scale forecasting error below 10%. Forecasting errors may be reduced by including more patients in future cohort studies or by increasing the frequency of observations for each patient. Our work, therefore, provides not only an accessible epidemiological modelling framework but also an insight into the data required for accurate forecasting using multi-scale models.