Determinants of parental decisions to abort for chromosome abnormalities

Parental decisions concerning the continuation of pregnancy following prenatal detection of abnormal chromosomes were evaluated for 80 patients whose diagnosis and prenatal counselling were performed in our centre. Twenty-two anomalies were diagnosed by chorionic villus sampling (CVS) and 58 by amniocentesis. The severity of the chromosome anomaly and associated ultrasound findings in the first vs. second trimester were correlated with patients' decisions. No difference was found in the likelihood of parental decisions to interrupt or continue a pregnancy between CVS and amniocentesis for either the‘severe’ or the‘questionable’ group of chromosome anomalies. Ninety-three per cent of patients with severe prognosis and 27 per cent with questionable prognosis opted for pregnancy termination (p <0·0001). The association of ultrasound anomalies and termination was highly significant (p< 0·001). The severity of the chromosome anomaly, and, to a lesser extent, the visualization of anomalies on ultrasound were the major determinants of parental decisions to terminate the pregnancy. The diagnosis of an anomaly in the first trimester was no more likely ito lead to a termination of pregnancy than in the second trimester.     

Evaluation of simplifying assumptions on pesticide degradation in soil

There is evidence that degradation of pesticides in simple laboratory systems may differ from that in the field, but it is not clear which of the simplifications inherent in laboratory studies present serious shortcomings. Laboratory experiments evaluated several simplifying assumptions for a clay loam soil and contrasting pesticides. Degradation of cyanazine [2-(4-chloro-6-ethylamino-1,3,5-triazin-2-ylamino)-2-methylpropiononitrile] and bentazone [3-isopropyl-1H-2,1,3-benzothiadiazin-4(3H)-one 2,2-dioxide] at fluctuating temperature and moisture was predicted reasonably well based on parameters derived from degradation under constant conditions. There was a tendency for slower degradation of cyanazine and bentazone in soil aggregates of 3 to 5 mm in diameter (DT50 at 15 degrees C and 40% maximum water holding capacity of 25.1 and 58.2 d, where DT50 is the time for 50% decline of the initial pesticide concentration) than in soil sieved to <3 mm (DT50 of 19.1 and 37.6 d), but the differences were not significant for most datasets. Degradation of cyanazine, isoproturon [3-(4-isopropylphenyl)-1,1-dimethylurea], and chlorotoluron [3-(3-chloro-p-tolyl)-1,1-dimethylurea] was measured in soil amended with different amounts of lignin. The effect of lignin on degradation was small despite considerable differences in sorption. The DT50 values of cyanazine, isoproturon, and chlorotoluron were 16.2, 18.6, and 33.0 d, respectively, in soil without lignin and 19.0, 23.4, and 34.6 d, respectively, in soil amended with 2% lignin. Degradation of bentazone and cyanazine in repacked soil columns was similar under static and flow conditions with 50.1 and 47.2% of applied bentazone and 74.7 and 73.6% of applied cyanazine, respectively, degraded within 20 d of application. Thus, the assumptions underpinning laboratory to field extrapolation tested here were considered to hold for our experimental system. Additional work is required before general conclusions can be drawn.     

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.     

Correction to: Radical scavenging and antiproliferative effect of novel phenolic derivatives isolated from Nerium indicum against human breast cancer cell line (MCF-7)—an in silico and in vitro approach

Environmental Science and Pollution Research - The correct presentation of the Author names are shown in this paper.     

A hierarchical Bayesian model for forecasting state-level corn yield

Historically, the National Agricultural Statistics Service crop forecasts and estimates have been determined by a group of commodity experts called the Agricultural Statistics Board (ASB). The corn yield forecasts for the “speculative region,” ten states that account for approximately 85 % of corn production, are based on two sets of monthly surveys, a farmer interview survey and a field measurement survey. The members of the ASB subjectively determine a forecast on the basis of a discussion of the survey data and auxiliary information about weather, average planting dates, and crop maturity. The ASB uses an iterative procedure, where initial state estimates are adjusted so that the weighted sum of the final state estimates is equal to a previously-determined estimate for the speculative region. Deficiencies of the highly subjective ASB process are lack of reproducibility and a measure of uncertainty. This paper describes the use of Bayesian methods to model the ASB process in a way that leads to objective forecasts and estimates of the corn yield. First, we use small area estimation techniques to obtain state-level forecasts. Second, we describe a way to adjust the state forecasts so that the weighted sum of the state forecasts is equal to a previously-determined regional forecast. We use several diagnostic techniques to assess the goodness of fit of various models and their competitors. We use Markov chain Monte Carlo methods to fit the models to both historic and current data from the two monthly surveys. Our results show that our methodology can provide reasonable and objective forecasts of corn yields for states in the speculative region.     

Refinery evaluation of optical imaging to locate fugitive emissions

Fugitive emissions account for approximately 50% of total hydrocarbon emissions from process plants. Federal and state regulations aiming at controlling these emissions require refineries and petrochemical plants in the United States to implement a Leak Detection and Repair Program (LDAR). The current regulatory work practice, U.S. Environment Protection Agency Method 21, requires designated components to be monitored individually at regular intervals. The annual costs of these LDAR programs in a typical refinery can exceed US$1,000,000. Previous studies have shown that a majority of controllable fugitive emissions come from a very small fraction of components. The Smart LDAR program aims to find cost-effective methods to monitor and reduce emissions from these large leakers. Optical gas imaging has been identified as one such technology that can help achieve this objective. This paper discusses a refinery evaluation of an instrument based on backscatter absorption gas imaging technology. This portable camera allows an operator to scan components more quickly and image gas leaks in real time. During the evaluation, the instrument was able to identify leaking components that were the source of 97% of the total mass emissions from leaks detected. More than 27,000 components were monitored. This was achieved in far less time than it would have taken using Method 21. In addition, the instrument was able to find leaks from components that are not required to be monitored by the current LDAR regulations. The technology principles and the parameters that affect instrument performance are also discussed in the paper.     

Modeling the impact of direct phototransformation on predicted environmental concentrations (PECs) of propranolol hydrochloride in UK and US rivers

There is currently uncertainty on the persistence of active pharmaceutical ingredients (APIs) and on their depletion mechanisms in natural surface waters such as rivers, and hence predictions of their fate are often poor. In this study, a beta-adrenergic receptor, propranolol hydrochloride, was selected as a model API to explore the relative significance of direct phototransformation as a potential removal process of hydrophilic APIs in rivers. Phototransformation kinetics of propranolol was measured under simulated solar irradiation in the laboratory, which were then converted to the kinetics applicable in UK and US rivers. The effects of light intensity, light penetration, river size and flow were examined. The extrapolated phototransformation half-lives were applied in the river catchment models of GREAT-ER and PhATE. Results demonstrated that direct phototransformation significantly reduced the predicted environmental concentrations of propranolol in the water phase. Predicted reductions of mean concentrations in the River Aire (UK) were 27% in summer and 3% in winter; and for the US rivers simulated, reductions were 28-68% in summer and 11-41% in winter. The highest reductions were predicted for long rivers with low turbidity and low flow conditions.     

用Autospec-Ultima NT气相色谱-高分辨质谱分析二噁英及相关的持久性有机污染物

"二噁英"是指一类化学结构和生物特征均有某些相似之处的化合物.这些有毒化合物有几百种,可分为相关的三大类:氯代二苯并-对-二噁英(CDDs),氯代二苯并呋喃(CDFs)和某些多氯代联苯(PCBs).CDDs和CDFs并非与生具有,而是由于人类活动不注意而生成的.天然过程也会产生CDDs和CDFs.