Oestrogen and Progesterone Receptors and COX‐2 Expression in Endometrial Biopsy Samples During Maternal Recognition of Pregnancy in Llamas (Lama glama)

Endometrial expression of oestrogen receptor‐α (ERα), progesterone receptor (PR) and cyclooxigenase‐2 (COX‐2) was evaluated in non‐pregnant and pregnant llamas during the period when luteolysis/maternal recognition of pregnancy is expected to occur. Females (n = 28) were divided into two groups: non‐pregnant llamas were induced to ovulate with a Buserelin injection, and endometrial biopsies were obtained on day 8 (n = 5) or 12 (n = 5) post‐induction of ovulation. Animals of the pregnant group (n = 18) were mated with a fertile male. Pregnancy was confirmed by the visualization of the embryo collected by transcervical flushing in 5 of 9 animals on day 8 post‐mating and by progesterone profile on day 12 post‐mating in 4 of 9 animals, when endometrial biopsies were obtained. An immunohistochemical technique was used to evaluate receptors population and COX‐2 expression. Pregnant llamas showed a higher percentage of positive cells and stronger intensity for ERα than for non‐pregnant llamas in stroma on day 8 and in the luminal epithelium on day 12 post‐induction of ovulation, while a deep decrease in endometrial PR population was reported in pregnant llamas on that day in luminal and glandular epithelia and stroma. In the luminal epithelium, COX‐2 expression was lower in pregnant than in non‐pregnant animals. Briefly, the increase of ERα in pregnant llamas gives further support to the hypothesis that oestrogens are involved in the mechanism of maternal recognition of pregnancy. Endometrial PR decrease in pregnant llamas might be a necessary event to allow the expression of proteins involved in conceptus attachment, a mechanism widely accepted in other species. Moreover, embryo seems to attenuate maternal PGF_2α secretion during early pregnancy by decreasing the endometrial expression of COX‐2 in the luminal epithelium of pregnant llamas.     

Prediction of soil surface salinity in arid region of central Iran using auxiliary variables and genetic programming

Spatial information on soil salinity is increasingly needed for decision making and management practices in arid environments. In this article, we attempted to investigate soil salinity variation via a digital soil mapping approach and genetic programming in an arid region, Chah-Afzal, located in central Iran. A grid sampling strategy with 2-km distance was used. In total, 180 soil surface samples were collected and then analyzed. A symbolic regression was then adopted to correlate electrical conductivity (EC_e) with a suite of auxiliary data including predicted maps of apparent electrical conductivity (vertical: EC_av and horizontal: EC_ah), Landsat spectral data and terrain attributes derived from a digital elevation model. The accuracy of the genetic programming model was evaluated using root mean square error (RMSE), mean error (ME), and coefficient of determination (R²) based on an independent validation data set (20% of database or thirty soil samples). In general, results showed that EC_ah had the strongest influence on the prediction of soil salinity followed by salinity index wetness index, Landsat Band 3, multi-resolution valley bottom flatness index, elevation, and normalized difference vegetation index. Furthermore, results indicated that the genetic programming model predicted EC_e over the study area accurately (R² = 0.87, ME = ?1.04 and RMSE = 16.36 dSm^?1). Overall, it is suggested that similar applications of this technique could be used for mapping soil salinity in other arid regions of Iran.     

Modeling soil carbon transported by water erosion processes

Long‐term monitoring is needed for direct assessment of soil organic carbon (SOC), soil, and nutrient loss by water erosion on a watershed scale. However, labor and capital requirements preclude implementation of such monitoring at many locations representing principal soils and ecoregions. These considerations warrant the development of diagnostic models to assess erosional SOC loss from more readily obtained data. The same factors affect transport of SOC and mineral soil fraction, suggesting that given the gain or loss of soil minerals, it may be possible to estimate the SOC flux from the data on erosion and deposition. One possible approach to parameterization is the use of the revised universal soil loss equation (RUSLE) to predict soil loss and this multiplied by the per cent of SOC in the near‐surface soil and an enrichment factor to obtain SOC loss. The data obtained from two watersheds in Ohio indicate that a power law relationship between soil loss and SOC loss may be more appropriate. When measured SOC loss from individual events over a 12‐year period was plotted against measured soil loss the data were logarithmically linear (R²=0·75) with a slope (or exponent in the power law) slightly less than would be expected for a RUSLE type model. The stable aggregate size distribution in runoff from a plot scale may be used to estimate the fate of size pools of SOC by comparing size distributions in the runoff plot scale and river watershed scales. Based upon this comparison, a minimum of 73 per cent of material from runoff plots is deposited on the landscape and the most stable carbon pool is lost from watershed soils to aquatic ecosystems and atmospheric carbon dioxide. Implicit in these models is the supposition that water stable soil aggregates and primary particles can be viewed as a tracer for SOC. Copyright © 2000 John Wiley & Sons, Ltd.     

Adrenergic, cholinergic, and nonadrenergic-noncholinergic intrinsic innervation of the jejunum in horses.

OBJECTIVE: To determine the major neurotransmitters that regulate contractile activity in the jejunum of horses. SAMPLE POPULATION: Jejunal specimens from 65 horses without gastrointestinal tract lesions. PROCEDURE: Jejunal smooth muscle strips, oriented in the plane of the circular or longitudinal muscular layer, were suspended isometrically in muscle baths. Neurotransmitter release was induced by electrical field stimulation (EFS) delivered at 30 and 70 V intensities and at various frequencies on muscle strips maintained at low or high muscle tone. To detect residual nonadrenergic-noncholinergic neurotransmission, the response of muscle to EFS in the presence of adrenergic and cholinergic blockade was compared with the response in the presence of tetrodotoxin. RESULTS: Atropine (ATR) decreased the contractile response of muscle strips to EFS under most conditions. However, ATR increased the contractile response of high-tone circular muscle. Adrenergic blockade generally increased the muscle responses to 30 V EFS and in high-tone longitudinal muscle but decreased contractile responses in high-tone circular muscle. Tetrodotoxin significantly altered the responses to EFS, compared with adrenergic and cholinergic receptor blockade. CONCLUSIONS: Acetylcholine and norepinephrine appear to be important neurotransmitters regulating smooth muscle contractility in the equine jejunum. They induce contraction and relaxation, respectively, in most muscle preparations, although they may cause opposite effects under certain conditions. In addition, nonadrenergic-noncholinergic excitatory and inhibitory influences were detected. CLINICAL RELEVANCE: Acetylcholine or norepinephrine release within the myenteric plexus of horses may alter gastrointestinal motility.     

Quasi-biennial corn yield cycles in Iowa

Quasi-biennial cycles are often reported in climate studies. The interannual El Niño Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) are two phenomena containing quasi-periodicities of approximately 2.5 and 2.2 years. It is known that ENSO affects corn yield through weather patterns, NAO affects surface temperature and cloudiness, and surface temperature, rainfall, and radiation affect corn yield. However, a quasi-biennial pattern in corn yield and the combined effect of several climate signals on long-term U.S. corn yield are not known. Here we show statistically significant 2–3 year periods in long-term corn yield from one of the world's most important corn producing regions. High (low) yields are due in part to high (low) surface radiation and low (high) temperature early in the corn growing season coupled with sufficient (insufficient) rainfall later in the growing season. A statistical model we developed using three climate indices accounts for 54% of the interannual variation in Iowa corn yield. The most significant periodicities found in the model's spectrum are similar to the quasi-biennial periodicities in observed corn yield. We classify Iowa corn yield from several regional datasets (1960–2006) for ‘low yield’ and ‘high yield’ conditions as predicted by the model. The difference between observed corn yields for ‘high’ and ‘low’ yielding years was 19% (p = 0.0001). The results demonstrate a quasi-biennial pattern in long-term Iowa corn yield related to large-scale climate variability. This knowledge could lead to models that help guide springtime agricultural management decisions that improve profitability and reduce nitrate flux to groundwater, streams, rivers, and coastal oceans.     

Intravenous continuous infusion of lidocaine for treatment of equine ileus

OBJECTIVE: To determine if intravenous lidocaine is useful and safe as a treatment for equine ileus. Study DESIGN: Prospective double-blinded placebo-controlled trial. STUDY POPULATION: Horses (n = 32) with a diagnosis of postoperative ileus (POI) or enteritis and that had refluxed >20 L or had been refluxing for >24 hours. METHODS: Refluxing horses were administered lidocaine (1.3 mg/kg intravenously [IV] as a bolus followed by a 0.05 mg/kg/min infusion) or saline (0.9% NaCl) solution placebo for 24 hours. Variables evaluated included volume and duration of reflux, time to 1st fecal passage, signs of pain, analgesic use, heart rate and arrhythmias, respiratory rate, temperature, days of hospitalization, outcome (survival to discharge), and complications. RESULTS: Of the lidocaine-treated horses, 65% (11/17) stopped refluxing within 30 hours (mean+/-SD, 15.2+/-2.4 hours) whereas 27% (4/15) of the saline-treated horses stopped within 30 hours. Fecal passage was significantly correlated with response to treatment; horses that responded to lidocaine passed feces within 16 hours of starting the infusion. Compared with placebo treatment, lidocaine treatment resulted in shorter hospitalization time for survivors, equivalent survival to discharge, no clinically significant changes in physical or laboratory variables, and no difference in the rate of incisional infections, jugular thrombosis, laminitis, or diarrhea. Muscle fasciculations occurred in 3 lidocaine-treated horses (18%). CONCLUSION: IV lidocaine significantly improved the clinical course in refluxing horses with minimal side effects. CLINICAL RELEVANCE: At the infusion rate studied, IV lidocaine is safe and should be considered for the treatment of equine ileus.     

Mapping forest dynamics under climate change: A matrix model

Global climate change may be affecting forests around the world. However, the impact of climate change on forest population dynamics, especially at the landscape or regional level, has hardly been addressed before. A new methodology was proposed to enable matrix transition models to account for climate impact on forest population dynamics. The first climate-sensitive matrix (CSMatrix) model was developed for the Alaska boreal forest based on observations from over 15 years of forest inventory. The spatially explicit model was used to map climate-induced forest population dynamics across the region. The model predicted that the basal area increment in the region under natural succession would be hindered by global warming, more so for dry upland areas than for moist wetlands. It was suggested that temperature-induced drought stress could more than offset a predicted increase of future precipitation in the region to lower overall forest productivity. At the same time, stand diversity would increase across the region through transient species redistribution. Accounting for climate conditions made the CSMatrix model more accurate than conventional matrix models.