Soil Aggregates and Associated Organic Matter under Conventional Tillage, No-Tillage, and Forest Succession after Three Decades

<div><p>Impacts of land use on soil organic C (SOC) are of interest relative to SOC sequestration and soil sustainability. The role of aggregate stability in SOC storage under contrasting land uses has been of particular interest relative to conventional tillage (CT) and no-till (NT) agriculture. This study compares soil structure and SOC fractions at the 30-yr-old Horseshoe Bend Agroecosystem Experiment (HSB). This research is unique in comparing NT and CT with adjacent land concurrently undergoing forest succession (FS) and in sampling to depths (15–28 cm) previously not studied at HSB. A soil moving experiment (SME) was also undertaken to monitor 1-yr changes in SOC and aggregation. After 30 years, enhanced aggregate stability under NT compared to CT was limited to a depth of 5 cm, while enhanced aggregate stability under FS compared to CT occurred to a depth of 28 cm and FS exceeded NT from 5–28 cm. Increases in SOC concentrations generally followed the increases in stability, except that no differences in SOC concentration were observed from 15–28 cm despite greater aggregate stability. Land use differences in SOC were explained equally by differences in particulate organic carbon (POC) and in silt-clay associated fine C. Enhanced structural stability of the SME soil was observed under FS and was linked to an increase of 1 Mg SOC ha⁻¹ in 0–5 cm, of which 90% could be attributed to a POC increase. The crushing of macroaggregates in the SME soil also induced a 10% reduction in SOC over 1 yr that occurred under all three land uses from 5–15 cm. The majority of this loss was in the fine C fraction. NT and FS ecosystems had greater aggregation and carbon storage at the soil surface but only FS increased aggregation below the surface, although in the absence of increased carbon storage.</p></div

Nomogram for predicting TW8 response in null responders, partial responders, relapsers and previously untreated patients treated with Boceprevir + PR.

<p>Instructions: This nomogram is a visual representation of the regression model built to predict TW8 response to boceprevir. It can be used to calculate a patient's predicted probability of becoming undetectable at TW8 if they have initiated boceprevir treatment. To use it, first circle the patients TW4 HCV-RNA on the TW4 HCV-RNA scale. By drawing a straight line upwards to the points scale. This represents the number of points for that patient based upon their TW4 HCV-RNA level. For example, if they have a value of ≤1500, the point score would be 100. Repeat this procedure for each of the variables presented in the nomogram. Once all point scores are determined, sum the total points and circle that value on the Total Points scale after the last variable. Draw a straight line downward from the Total Points scale to determine an individuals predicted probability of a TW8 response.</p

Soil chemical attributes (mean ±1SD) for the Horseshoe Bend Agroecosystem Experiment, Athens, GA.

<p>N = 4 per treatment type. Soils were collected in 2009.</p><p>¹ Salt pH in 0.01 M CaCl₂.</p><p>² Mehlich I extractable P and cations.</p><p>³ Effective cation exchange capacity by sum of cations method.</p

Prediction of Treatment Week Eight Response & Sustained Virologic Response in Patients Treated with Boceprevir Plus Peginterferon Alfa and Ribavirin

<div><p>Aim</p><p>Sustained virologic response (SVR) can be attained with boceprevir plus peginterferon alfa and ribavirin (PR) in up to 68% of patients, and short duration therapy is possible if plasma HCV RNA levels are undetectable at treatment week 8 (TW8 response). We have developed predictive models for SVR, and TW8 response using data from boceprevir clinical trials.</p><p>Methods</p><p>Regression models were built to predict TW8 response and SVR. Separate models were built for TW8 and SVR using baseline variables only, and compared to models with baseline variables plus HCV RNA change after 4 weeks of PR (TW4 delta). Predictive accuracy was assessed by c-statistics, calibration curves, and decision curve analyses. Nomograms were developed to create clinical decision support tools. Models were externally validated using independent data.</p><p>Results</p><p>The models that included TW4 delta produced the best discrimination ability. The predictive factors for TW8 response (n = 856) were TW4 delta, race, platelet count and ALT. The predictive factors for SVR (n = 522) were TW4 delta, HCV-subtype, gender, BMI, RBV dose and platelet count. The discrimination abilities of these models were excellent (C-statistics = 0.88, 0.80 respectively). Baseline models for TW8 response (n = 444) and SVR (n = 197) had weaker discrimination ability (C-statistic = 0.76, 0.69). External validation confirmed the predictive accuracy of the week 4 models.</p><p>Conclusions</p><p>Models incorporating baseline and treatment week 4 data provide excellent prediction of TW8 response and SVR, and support the clinical utility of the lead-in phase of PR. The nomograms are suitable for point-of-care use to inform individual patient and physician decision-making.</p></div

Contributions of four different aggregate size fractions to total soil organic C (SOC) concentrations.

<p>Different letters indicate a significant difference between land uses in a depth class (α = 0.05). Means of the sums of the four fractions are shown (n = 4) from Horseshoe Bend, Athens, GA, USA, October 2007. See also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084988#pone.0084988.s006" target="_blank">Table S6</a>.</p

Nomogram for predicting SVR in null responders, partial responders, relapsers and previously untreated patients treated with Boceprevir + PR.

<p>Nomogram for predicting SVR in null responders, partial responders, relapsers and previously untreated patients treated with Boceprevir + PR.</p

Distribution of water-stable aggregates on a sand-free soil basis (mean ±1 SE) at the Horseshoe Bend Agroecosystem Experiment (n = 4), Athens, GA, USA, October 2007.

<p>Different letters within an aggregate size class and depth class represent a significant difference between land uses (α = 0.05). See also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084988#pone.0084988.s002" target="_blank">Table S2</a>.</p

Total soil organic C (SOC), particulate organic C (POC) and microbial biomass C (MBC) (mean ±1 SD) at two depths at the end of a soil moving experiment (n = 4).

<p>Conventional till soil was initially dried and crushed to pass a 1 mm sieve and then installed under the three different land uses for a period of one year at Horseshoe Bend, Athens, GA, USA, July 2007–August 2008.</p><p>Different letters indicate statistical significance between treatment means within a depth class based on Tukey's HSD with α = 0.05. See also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084988#pone.0084988.s008" target="_blank">Table S8</a>.</p

Aggregate stability (mean ±1 SD) at two depths at the end of a soil moving experiment (n = 4).

<p>Conventional till soil was initially dried and crushed to pass a 1 mm sieve and then installed under three different land uses for a period of one year at Horseshoe Bend, Athens, GA, USA, July 2007–August 2008.</p><p>Different letters indicate statistical significance among treatment means within a depth class based on Tukey's HSD with α = 0.05. See also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084988#pone.0084988.s007" target="_blank">Table S7</a>.</p><p>Mean-weighted diameter.</p

Dry-sieved and wet-sieved aggregates' mean weight diameter (MWD) (mean ± 1 SE) at the Horseshoe Bend Agroecosystem Experiment (n = 4), Athens, GA, USA, October 2007.

<p>The aggregate stability index is calculated by dividing the Wet MWD by the Dry MWD. Different letters indicate statistical significance between land uses within a depth class based on Tukey's HSD with a = 0.05. See also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084988#pone.0084988.s001" target="_blank">Table S1</a></p