Early serum procalcitonin, interleukin-6, and 24-hour lactate clearance: useful indicators of septic infections in severely traumatized patients

BACKGROUND: Elevated lactate and interleukin-6 (IL-6) levels were shown to correlate with mortality and multiple organ dysfunction in severely traumatized patients. The purpose of this study was to test whether an association exists between 24-hour lactate clearance, IL-6 and procalcitonin (PCT) levels, and the development of infectious complications in trauma patients. METHODS: A total of 1757 consecutive trauma patients with an Injury Severity Score (ISS) > 16 admitted over a 10-year period were retrospectively analyzed over a 21-day period. Exclusion criteria included death within 72 h of admission (24.5%), late admission > 12 h after injury (16%), and age < 16 years (0.5%). Data are stated as the median (range). RESULTS: Altogether, 1032 trauma patients (76.2% male) with an average age of 38 years, a median ISS of 29 (16-75), and an Acute Physiology, Age, and Chronic Health Evaluation (APACHE) II score of 14 (0-40) were evaluated. The in-hospital mortality (>3 days) was 10%. Patients with insufficient 24-hour lactate clearance had a high rate of overall mortality and infections. Elevated early serum procalcitonin on days 1 to 5 after trauma was strongly associated with the subsequent development of sepsis (p < 0.01) but not with nonseptic infections. The kinetics of IL-6 were similar to those of PCT but did differentiate between infected and noninfected patients after day 5. CONCLUSIONS: This study demonstrates that elevated early procalcitonin and IL-6 levels and inadequate 24-hour lactate clearance help identify trauma patients who develop septic and nonseptic infectious complications. Definition of specific cutoff values and early monitoring of these parameters may help direct early surgical and antibiotic therapy and reduce infectious mortality.

Community mean traits as additional indicators to monitor effects of land-use intensity on grassland plant diversity

Semi-natural grasslands, biodiversity hotspots in Central-Europe, suffer from the cessation of traditional land-use. Amount and intensity of these changes challenge current monitoring frameworks typically based on classic indicators such as selected target species or diversity indices. Indicators based on plant functional traits provide an interesting extension since they reflect ecological strategies at individual and ecological processes at community levels. They typically show convergent responses to gradients of land-use intensity over scales and regions, are more directly related to environmental drivers than diversity components themselves and enable detecting directional changes in whole community dynamics. However, probably due to their labor- and cost intensive assessment in the field, they have been rarely applied as indicators so far. Here we suggest overcoming these limitations by calculating indicators with plant traits derived from online accessible databases. Aiming to provide a minimal trait set to monitor effects of land-use intensification on plant diversity we investigated relationships between 12 community mean traits, 2 diversity indices and 6 predictors of land-use intensity within grassland communities of 3 different regions in Germany (part of the German ‘Biodiversity Exploratory’ research network). By standardization of traits and diversity measures, use of null models and linear mixed models we confirmed (i) strong links between functional community composition and plant diversity, (ii) that traits are closely related to land-use intensity, and (iii) that functional indicators are equally, or even more sensitive to land-use intensity than traditional diversity indices. The deduced trait set consisted of 5 traits, i.e., specific leaf area (SLA), leaf dry matter content (LDMC), seed release height, leaf distribution, and onset of flowering. These database derived traits enable the early detection of changes in community structure indicative for future diversity loss. As an addition to current monitoring measures they allow to better link environmental drivers to processes controlling community dynamics.

Analysis of polygonal cracking patterns in chloride-bearing terrains on Mars: Indicators of ancient playa settings

The ancient southern highlands on Mars (~3.5 Gyr old) contain > 600 regions that display spectral evidence in the infrared for the presence of chloride-bearing materials. Many of these locations were previously reported to display polygonal cracking patterns. We studied more than 80 of the chloride-bearing terrains using high-resolution (0.25-0.5 m/pixel) images, as well as near-infrared spectral data, to characterize the surface textures and the associated cracking patterns and mineralogies. Our study indicates that ~75% of the studied locations display polygonal cracks that resemble desiccation cracks, while some resemble salt expansion/thrust polygons. Furthermore, we detect, spectrally, the presence of smectites in association with ~30% of the studied fractured terrains. We note that smectites are a special class of swelling clay minerals that can induce formation of large desiccation cracks. As such, we suggest that the cracking patterns are indicative of the presence of smectite phyllosilicates even in the absence of spectral confirmation. Our results suggest that many chloride-bearing terrains have a lacustrine origin and a geologic setting similar to playas on Earth. Such locations would have contained ephemeral lakes that may have undergone repeated cycles of desiccation and recharging by a near-surface fluctuating water table in order to account for the salt-phyllosilicates associations. These results have notable implications for the ancient hydrology of Mars. We propose that the morphologies and sizes of the polygonal cracks can be used as paleoenvironmental, as well as lithological, indicators that could be helpful in planning future missions.

Oxygen and indicators of stress for marine life in multi-model global warming projections

Decadal-to-century scale trends for a range of marine environmental variables in the upper mesopelagic layer (UML, 100–600 m) are investigated using results from seven Earth System Models forced by a high greenhouse gas emission scenario. The models as a class represent the observation-based distribution of oxygen (O2) and carbon dioxide (CO2), albeit major mismatches between observation-based and simulated values remain for individual models. By year 2100 all models project an increase in SST between 2 °C and 3 °C, and a decrease in the pH and in the saturation state of water with respect to calcium carbonate minerals in the UML. A decrease in the total ocean inventory of dissolved oxygen by 2% to 4% is projected by the range of models. Projected O2 changes in the UML show a complex pattern with both increasing and decreasing trends reflecting the subtle balance of different competing factors such as circulation, production, remineralization, and temperature changes. Projected changes in the total volume of hypoxic and suboxic waters remain relatively small in all models. A widespread increase of CO2 in the UML is projected. The median of the CO2 distribution between 100 and 600m shifts from 0.1–0.2 mol m−3 in year 1990 to 0.2–0.4 mol m−3 in year 2100, primarily as a result of the invasion of anthropogenic carbon from the atmosphere. The co-occurrence of changes in a range of environmental variables indicates the need to further investigate their synergistic impacts on marine ecosystems and Earth System feedbacks.

The Weekly Adjustment Indicators Checklist: An Application in the Child Welfare Field

Research on the effectiveness of various home-based interventions implemented in the 1980s and 1990s indicates that results have been equivocal. Because of the unique and complex behavioral challenges presented by each family and the need for individualized treatments and long-term interventions for these families, group research and evaluation designs are often insufficient in assessing effectiveness of home-based interventions. Alternative evaluation strategies are needed. The purpose of this exploratory study was two-fold: (a) to investigate the applicability and acceptability of the Weekly Adjustment Indicators Checklist (WAIC) in monitoring adult and child behaviors and (b) to monitor, on an on-going basis, the progress of a family referred to an urban family preservation and reunification program. The target family on whom data were collected consisted of a 13-year old girl and her foster parent who was her maternal aunt. The findings of this study indicate that the WAIC is applicable in monitoring the progress of children and adults in care and that it has the endorsement of its user, namely, the direct care provider. Other results of the study, limitations of the study, and future research needs are discussed.

Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^

A Wavelet Analysis of Pliopleistocene Climate Indicators: A New View of Periodicity Evolution

Wavelet analysis offers an alternative to Fourier based time-series analysis, and is particularly useful when the amplitudes and periods of dominant cycles are time dependent. We analyse climatic records derived from oxygen isotopic ratios of marine sediment cores with modified Morlet wavelets. We use a normalization of the Morlet wavelets which allows direct correspondence with Fourier analysis. This provides a direct view of the oscillations at various frequencies, and illustrates the nature of the time-dependence of the dominant cycles.