Four-decade responses of soil trace elements to an aggrading old-field forest: B, Mn, Zn, Cu, and Fe.

In the ancient and acidic Ultisol soils of the Southern Piedmont, USA, we studied changes in trace element biogeochemistry over four decades, a period during which formerly cultivated cotton fields were planted with pine seedlings that grew into mature forest stands. In 16 permanent plots, we estimated 40-year accumulations of trace elements in forest biomass and O horizons (between 1957 and 1997), and changes in bioavailable soil fractions indexed by extractions of 0.05 mol/L HCl and 0.2 mol/L acid ammonium oxalate (AAO). Element accumulations in 40-year tree biomass plus O horizons totaled 0.9, 2.9, 4.8, 49.6, and 501.3 kg/ha for Cu, B, Zn, Mn, and Fe, respectively. In response to this forest development, samples of the upper 0.6-m of mineral soil archived in 1962 and 1997 followed one of three patterns. (1) Extractable B and Mn were significantly depleted, by -4.1 and -57.7 kg/ha with AAO, depletions comparable to accumulations in biomass plus O horizons, 2.9 and 49.6 kg/ha, respectively. Tree uptake of B and Mn from mineral soil greatly outpaced resupplies from atmospheric deposition, mineral weathering, and deep-root uptake. (2) Extractable Zn and Cu changed little during forest growth, indicating that nutrient resupplies kept pace with accumulations by the aggrading forest. (3) Oxalate-extractable Fe increased substantially during forest growth, by 275.8 kg/ha, about 10-fold more than accumulations in tree biomass (28.7 kg/ha). The large increases in AAO-extractable Fe in surficial 0.35-m mineral soils were accompanied by substantial accretions of Fe in the forest's O horizon, by 473 kg/ha, amounts that dwarfed inputs via litterfall and canopy throughfall, indicating that forest Fe cycling is qualitatively different from that of other macro- and micronutrients. Bioturbation of surficial forest soil layers cannot account for these fractions and transformations of Fe, and we hypothesize that the secondary forest's large inputs of organic additions over four decades has fundamentally altered soil Fe oxides, potentially altering the bioavailability and retention of macro- and micronutrients, contaminants, and organic matter itself. The wide range of responses among the ecosystem's trace elements illustrates the great dynamics of the soil system over time scales of decades.

Huntingtin is required for normal excitatory synapse development in cortical and striatal circuits.

Huntington's disease (HD) is a neurodegenerative disease caused by the expansion of a poly-glutamine (poly-Q) stretch in the huntingtin (Htt) protein. Gain-of-function effects of mutant Htt have been extensively investigated as the major driver of neurodegeneration in HD. However, loss-of-function effects of poly-Q mutations recently emerged as potential drivers of disease pathophysiology. Early synaptic problems in the excitatory cortical and striatal connections have been reported in HD, but the role of Htt protein in synaptic connectivity was unknown. Therefore, we investigated the role of Htt in synaptic connectivity in vivo by conditionally silencing Htt in the developing mouse cortex. When cortical Htt function was silenced, cortical and striatal excitatory synapses formed and matured at an accelerated pace through postnatal day 21 (P21). This exuberant synaptic connectivity was lost over time in the cortex, resulting in the deterioration of synapses by 5 weeks. Synaptic decline in the cortex was accompanied with layer- and region-specific reactive gliosis without cell loss. To determine whether the disease-causing poly-Q mutation in Htt affects synapse development, we next investigated the synaptic connectivity in a full-length knock-in mouse model of HD, the zQ175 mouse. Similar to the cortical conditional knock-outs, we found excessive excitatory synapse formation and maturation in the cortices of P21 zQ175, which was lost by 5 weeks. Together, our findings reveal that cortical Htt is required for the correct establishment of cortical and striatal excitatory circuits, and this function of Htt is lost when the mutant Htt is present.

An evaluation of remifentanil-sevoflurane response surface models in patients emerging from anesthesia: model improvement using effect-site sevoflurane concentrations.

INTRODUCTION: We previously reported models that characterized the synergistic interaction between remifentanil and sevoflurane in blunting responses to verbal and painful stimuli. This preliminary study evaluated the ability of these models to predict a return of responsiveness during emergence from anesthesia and a response to tibial pressure when patients required analgesics in the recovery room. We hypothesized that model predictions would be consistent with observed responses. We also hypothesized that under non-steady-state conditions, accounting for the lag time between sevoflurane effect-site concentration (Ce) and end-tidal (ET) concentration would improve predictions. METHODS: Twenty patients received a sevoflurane, remifentanil, and fentanyl anesthetic. Two model predictions of responsiveness were recorded at emergence: an ET-based and a Ce-based prediction. Similarly, 2 predictions of a response to noxious stimuli were recorded when patients first required analgesics in the recovery room. Model predictions were compared with observations with graphical and temporal analyses. RESULTS: While patients were anesthetized, model predictions indicated a high likelihood that patients would be unresponsive (> or = 99%). However, after termination of the anesthetic, models exhibited a wide range of predictions at emergence (1%-97%). Although wide, the Ce-based predictions of responsiveness were better distributed over a percentage ranking of observations than the ET-based predictions. For the ET-based model, 45% of the patients awoke within 2 min of the 50% model predicted probability of unresponsiveness and 65% awoke within 4 min. For the Ce-based model, 45% of the patients awoke within 1 min of the 50% model predicted probability of unresponsiveness and 85% awoke within 3.2 min. Predictions of a response to a painful stimulus in the recovery room were similar for the Ce- and ET-based models. DISCUSSION: Results confirmed, in part, our study hypothesis; accounting for the lag time between Ce and ET sevoflurane concentrations improved model predictions of responsiveness but had no effect on predicting a response to a noxious stimulus in the recovery room. These models may be useful in predicting events of clinical interest but large-scale evaluations with numerous patients are needed to better characterize model performance.

Quantification of biological aging in young adults.

Antiaging therapies show promise in model organism research. Translation to humans is needed to address the challenges of an aging global population. Interventions to slow human aging will need to be applied to still-young individuals. However, most human aging research examines older adults, many with chronic disease. As a result, little is known about aging in young humans. We studied aging in 954 young humans, the Dunedin Study birth cohort, tracking multiple biomarkers across three time points spanning their third and fourth decades of life. We developed and validated two methods by which aging can be measured in young adults, one cross-sectional and one longitudinal. Our longitudinal measure allows quantification of the pace of coordinated physiological deterioration across multiple organ systems (e.g., pulmonary, periodontal, cardiovascular, renal, hepatic, and immune function). We applied these methods to assess biological aging in young humans who had not yet developed age-related diseases. Young individuals of the same chronological age varied in their "biological aging" (declining integrity of multiple organ systems). Already, before midlife, individuals who were aging more rapidly were less physically able, showed cognitive decline and brain aging, self-reported worse health, and looked older. Measured biological aging in young adults can be used to identify causes of aging and evaluate rejuvenation therapies.

The evolving capabilities of rhodopsin-based genetically encoded voltage indicators.

Protein engineering over the past four years has made rhodopsin-based genetically encoded voltage indicators a leading candidate to achieve the task of reporting action potentials from a population of genetically targeted neurons in vivo. Rational design and large-scale screening efforts have steadily improved the dynamic range and kinetics of the rhodopsin voltage-sensing domain, and coupling these rhodopsins to bright fluorescent proteins has supported bright fluorescence readout of the large and rapid rhodopsin voltage response. The rhodopsin-fluorescent protein fusions have the highest achieved signal-to-noise ratios for detecting action potentials in neuronal cultures to date, and have successfully reported single spike events in vivo. Given the rapid pace of current development, the genetically encoded voltage indicator class is nearing the goal of robust spike imaging during live-animal behavioral experiments.