The application of graph theory and percolation analysis for assessing change in the spatial configuration of pond networks

Pond networks support high levels of biodiversity when compared to other freshwater ecosystems such as rivers, lakes and streams. The persistence of species in these small, sometimes ephemeral, aquatic habitats depends on the dispersal of individuals among ponds in the landscape. However, the number of ponds across the landscape is at a historical low as urbanisation and intensified agricultural practices have led to a substantial loss of ponds (nodes in the pond network) over more than a century. Here, we examine the extent and drivers of pond loss in a heavily urbanised landscape (Birmingham, UK) over 105 years and determine how pond loss influences key structural properties of the pond network using graph theoretic approaches. Specifically, we calculated minimum spanning trees (MST) and performed percolation analyses to determine changes in both the spatial configuration and resilience of the pond network through time. Pond numbers declined by 82% between ca1904 and 2009, such that pond density decreased from 7.1 km-2 to 1.3 km-2. The MST analyses revealed increased distance between ponds in the network (i.e. edge length increased) by up to 49% over the 105-year period, indicating that ponds in the modern landscape (2009) were considerably more isolated, with fewer neighbours. This study demonstrates that graph theory has an excellent potential to inform the management of pond networks in order to support ecological communities that are less vulnerable to environmental change

Partitioning the environmental drivers of immunocompetence

By determining susceptibility to disease, environment-driven variation in immune responses can affect the health, productivity and fitness of vertebrates. Yet how the different components of the total environment control this immune variation is remarkably poorly understood. Here, through combining field observation, experimentation and modelling, we are able to quantitatively partition the key environmental drivers of constitutive immune allocation in a model wild vertebrate (three-spined stickleback, Gasterosteus aculeatus). We demonstrate that, in natural populations, thermal conditions and diet alone are sufficient (and necessary) to explain a dominant (seasonal) axis of variation in immune allocation. This dominant axis contributes to both infection resistance and tolerance and, in turn, to the vital rates of infectious agents and the progression of the disease they cause. Our results illuminate the environmental regulation of vertebrate immunity (given the evolutionary conservation of the molecular pathways involved) and they identify mechanisms through which immunocompetence and host-parasite dynamics might be impacted by changing environments. In particular, we predict a dominant sensitivity of immunocompetence and host-pathogen dynamics to host diet shifts

Electroencephalography (EEG) for neurological prognostication after cardiac arrest and targeted temperature management; rationale and study design.

BACKGROUND: Electroencephalography (EEG) is widely used to assess neurological prognosis in patients who are comatose after cardiac arrest, but its value is limited by varying definitions of pathological patterns and by inter-rater variability. The American Clinical Neurophysiology Society (ACNS) has recently proposed a standardized EEG-terminology for critical care to address these limitations. METHODS/DESIGN: In the TTM-trial, 399 post cardiac arrest patients who remained comatose after rewarming underwent a routine EEG. The presence of clinical seizures, use of sedatives and antiepileptic drugs during the EEG-registration were prospectively documented. DISCUSSION: A well-defined terminology for interpreting post cardiac arrest EEGs is critical for the use of EEG as a prognostic tool. TRIAL REGISTRATION: The TTM-trial is registered at ClinicalTrials.gov (NCT01020916)

Influence of bone density on implant stability parameters and implant success: a retrospective clinical study

<p>Abstract</p> <p>Background</p> <p>The aim of the present clinical study was to determine the local bone density in dental implant recipient sites using computerized tomography (CT) and to investigate the influence of local bone density on implant stability parameters and implant success.</p> <p>Methods</p> <p>A total of 300 implants were placed in 111 patients between 2003 and 2005. The bone density in each implant recipient site was determined using CT. Insertion torque and resonance frequency analysis were used as implant stability parameters. The peak insertion torque values were recorded with OsseoCare machine. The resonance frequency analysis measurements were performed with Osstell instrument immediately after implant placement, 6, and 12 months later.</p> <p>Results</p> <p>Of 300 implants placed, 20 were lost, meaning a survival rate of %. 93.3 after three years (average 3.7 ± 0.7 years). The mean bone density, insertion torque and RFA recordings of all 300 implants were 620 ± 251 HU, 36.1 ± 8 Ncm, and 65.7 ± 9 ISQ at implant placement respectively; which indicated statistically significant correlations between bone density and insertion torque values (p < 0.001), bone density and ISQ values (p < 0.001), and insertion torque and ISQ values (p < 0.001). The mean bone density, insertion torque and RFA values were 645 ± 240 HU, 37.2 ± 7 Ncm, and 67.1 ± 7 ISQ for 280 successful implants at implant placement, while corresponding values were 267 ± 47 HU, 21.8 ± 4 Ncm, and 46.5 ± 4 ISQ for 20 failed implants; which indicated statistically significant differences for each parameter (p < 0.001).</p> <p>Conclusion</p> <p>CT is a useful tool to determine the bone density in the implant recipient sites, and the local bone density has a prevailing influence on primary implant stability, which is an important determinant for implant success.</p

From Therapeutic Drug Monitoring to Model-Informed Precision Dosing for Antibiotic

Therapeutic drug monitoring (TDM) and model-informed precision dosing (MIPD) have evolved as important tools to inform rational dosing of antibiotics in individual patients with infections. In particular, critically ill patients display altered, highly variable pharmacokinetics and often suffer from infections caused by less susceptible bacteria. Consequently, TDM has been used to individualize dosing in this patient group for many years. More recently, there has been increasing research on the use of MIPD software to streamline the TDM process, which can increase the flexibility and precision of dose individualization but also requires adequate model validation and re-evaluation of existing workflows. In parallel, new minimally invasive and noninvasive technologies such as microneedle-based sensors are being developed, which-together with MIPD software-have the potential to revolutionize how patients are dosed with antibiotics. Nonetheless, carefully designed clinical trials to evaluate the benefit of TDM and MIPD approaches are still sparse, but are critically needed to justify the implementation of TDM and MIPD in clinical practice. The present review summarizes the clinical pharmacology of antibiotics, conventional TDM and MIPD approaches, and evidence of the value of TDM/MIPD for aminoglycosides, beta-lactams, glycopeptides, and linezolid, for which precision dosing approaches have been recommended

LiST as a catalyst in program planning: experiences from Burkina Faso, Ghana and Malawi

Background African countries are working to achieve rapid reductions in maternal and child mortality and meet their targets for the Millennium Development Goals (MDGs). Partners in the Catalytic Initiative to Save One Million Lives (CI) are assisting them by providing funding and technical assistance to increase and accelerate coverage for proven interventions. Here we describe how the Lives Saved Tool (LiST) was used as part of an early assessment of the expected impact of CI plans in Malawi, Burkina Faso and Ghana

Albumin-Like Protein is the Major Protein Constituent of Luminal Fluid in the Human Endolymphatic Sac

The endolymphatic sac (ES) is an inner ear organ that is connected to the cochleo-vestibular system through the endolymphatic duct. The luminal fluid of the ES contains a much higher concentration of proteins than any other compartment of the inner ear. This high protein concentration likely contributes to inner ear fluid volume regulation by creating an osmotic gradient between the ES lumen and the interstitial fluid. We characterized the protein profile of the ES luminal fluid of patients (n = 11) with enlarged vestibular aqueducts (EVA) by proteomics. In addition, we investigated differences in the protein profiles between patients with recent hearing deterioration and patients without hearing deterioration. The mean total protein concentration of the luminal fluid was 554.7±94.6 mg/dl. A total of 58 out of 517 spots detected by 2-DE were analyzed by MALDI-TOF MS. The protein profile of the luminal fluid was different from the profile of plasma. Proteins identified from 29 of the spots were also present in the MARC-filtered human plasma; however, the proteins identified from the other 25 spots were not detected in the MARC-filtered human plasma. The most abundant protein in the luminal fluid was albumin-like proteins, but most of them were not detected in MARC-filtered human plasma. The concentration of albumin-like proteins was higher in samples from patients without recent hearing deterioration than in patients with recent hearing deterioration. Consequently, the protein of ES luminal fluid is likely to be originated from both the plasma and the inner ear and considering that inner ear fluid volumes increase abnormally in patients with EVA following recent hearing deterioration, it is tempting to speculate that albumin-like proteins may be involved in the regulation of inner ear fluid volume through creation of an osmotic gradient during pathological conditions such as endolymphatic hydrops

How well does LiST capture mortality by wealth quintile? A comparison of measured versus modelled mortality rates among children under-five in Bangladesh

Background In the absence of planned efforts to target the poor, child survival programs often favour the rich. Further evidence is needed urgently about which interventions and programme approaches are most effective in addressing inequities. The Lives Saved Tool (LiST) is available and can be used to model mortality levels across economic groups based on coverage levels for child survival interventions