Erythroid-specific antibodies enhance detection of fetal nucleated erythrocytes in maternal blood

Fetal nucleated erythrocytes (NRBC) in maternal blood are a non-invasive source of fetal DNA for prenatal genetic screening. We compared the effectiveness of three monoclonal antibodies for the separation of fetal cells from maternal blood by flow sorting. Mononuclear blood cells from 49 healthy pregnant women were incubated with antibody to CD 71, CD 36, and/or glycophorin A (GPA), employed singly or in combination with each other. These monoclonal antibodies recognize surface antigens on haematopoietic precursor cells. Successful isolation of fetal cells was defined as detection of Y chromosomal sequences in maternal blood from women carrying male fetuses, with absence of Y sequences when female fetuses were carried. Thus, gender prediction accuracy was used as a measure of fetal cell separation. Using anti-CD 71 to isolate fetal cells, gender prediction was 57 per cent correct; with anti-CD 36, it was 88 per cent correct. Anti-GPA, an erythrocyte-specific antigen, used alone or in combination with anti-CD 71 or 36, improved gender prediction to 100 per cent. We conclude that antibody to GPA improves the retrieval of fetal NRBC from maternal blood, permitting genetic analysis by the polymerase chain reaction.     

Flow sorting of fetal erythroblasts using intracytoplasmic anti-fetal haemoglobin: Preliminary observations on maternal samples

Monoclonal antibody to fetal haemoglobin (a₂γy₂) has been proposed as a fetal-specific reagent. We developed an intracellular staining protocol that combines fluorescein isothiocyanate or phycoerythrin conjugated anti-γ with the DNA binding dye Hoechst 33342 to identify and flow sort fetal erythroblasts from maternal blood. Our preliminary observations on anti-γ-positive cells sorted from four different pregnant women are described here, using fluorescence in situ hybridization (FISH) with chromosome-specific probes to identify fetal cells. Our data demonstrate that far fewer candidate fetal cells are sorted with this protocol than by current cell surface staining methods that employ the monoclonal antibody CD71. This results in increased fetal cell sorting purities. With this protocol, standard FISH techniques require modification due to the rigorous fixation with 4 per cent paraformaldehyde. Our initial data indicate the promise of this approach.     

Detection of fetal HLA-DQα sequences in maternal blood: A gender-independent technique of fetal cell identification

The objective of this study was to detect fetal HLA-DQα gene sequences in maternal blood. HLA-DQα genotypes of 70 pregnant women and their partners were determined for type A1. We specifically sought couples where the father, but not the mother, had genotype A1. In 12 women, maternal blood samples were flow-sorted. Candidate fetal cells were isolated and amplified by using PCR primers specific for a paternal HLA-DQα A1 allele. Fetal HLA-DQα A1 genotype was predicted from sorted cells; amniocytes or cheek swabs were used for confirmation. Six of twelve sorted samples had amplification products indicating the presence of the HLA-DQα A1 allele; 6/12 did not. Prediction of the fetal genotype was 100 per cent correct, as determined by subsequent amplification of amniocytes or cheek swabs. We conclude that paternally inherited uniquely fetal HLA-DQα gene sequences can be identified in maternal blood. This system permits the identification of fetal cells independent of fetal gender, and has the potential for non-invasive prenatal diagnosis of paternally inherited conditions.     

Continuous subcutaneous insulin infusion (CSII) in pregnant diabetic patients

The efficacy of the insulin infusion pump (CSII) in pregnancy was examined in 12 diabetic patients and compared with intermittent insulin therapy (IIT). In patients poorly controlled on IIT constant and rapid equilibrium was achieved with CSII (mean of glucose levels: CSII versus IIT=84 versus 137 mg/dl; S.D. = 36 versus 63 mg/dl; mean amplitude of glycemic excursion (MAGE)=65 versus 112 mg/dl. In patients well controlled on IIT, CSII led to a reduction in the variation of glucose excursions (S.D.= 29 versus 36 mg/dl; MAGE=48 versus 76 mg/dl). CSII generally produced a reduction of 20–37 per cent of daily insulin dose (in three cases there was an increase of dose with the achievement of glycemic control). Furthermore in CSII treated-patients amniotic glucose, insulin and C-peptide concentrations werefound tobeinthenormalrange(22.1±10.1 mg/dl; 5.2±2.7μ/ml; 1.25±0.71 ng/ml, respectively). All infants were horn at or near-term, had no macrosomia or neonatal problems. It is concluded that CSII is a highly efficient way to achieve normal glucose levels in pregnancy, not only in type I, hut also in type II or gestational diabetes.     

Cardiovascular effects of arsenic: clinical and epidemiological findings

Several population studies relate exposure to high levels of arsenic with an increased incidence of ischemic heart disease and cardiovascular mortality. An association has been shown between exposure to high levels of arsenic and cardiovascular risk factors such as hypertension and diabetes mellitus, and vascular damage such as subclinical carotid atherosclerosis. The mechanisms underlying these phenomena are currently being studied and appear to indicate an alteration of vascular function. However, the effects of low levels of exposure to arsenic and their potential detrimental cardiovascular effect are less explored. The article provides an overview of the pathophysiologic mechanisms linking low-level arsenic exposure to the occurrence of cardiovascular disease and its complications, and some potential preventive strategies to implement.     

Genetic considerations in the prenatal diagnosis of overgrowth syndromes

Large (>90%) for gestational age (LGA) fetuses are usually identified incidentally. Detection of the LGA fetus should first prompt the provider to rule out incorrect dates and maternal diabetes. Once this is done, consideration should be given to certain overgrowth syndromes, especially if anomalies are present. The overgrowth syndromes have significant clinical and molecular overlap, and are associated with developmental delay, tumors, and other anomalies. Although genetic causes of overgrowth are considered postnatally, they are infrequently diagnosed prenatally. Here, we review prenatal sonographic findings in fetal overgrowth syndromes, including Pallister-Killian, Beckwith-Wiedemann, Sotos, Perlman, and Simpson-Golabi-Behmel. We also discuss prenatal diagnosis options and recurrence risks. Copyright © 2009 John Wiley & Sons, Ltd.     

Automotive shredder residue (ASR) characterization for a valuable management

Car fluff is the waste produced after end-of-life-vehicles (ELVs) shredding and metal recovery. It is made of plastics, rubber, glass, textiles and residual metals and it accounts for almost one-third of a vehicle mass. Due to the approaching of Directive 2000/53/EC recycling targets, 85% recycling rate and 95% recovery rate in 2015, the implementation of automotive shredder residue (ASR) sorting and recycling technologies appears strategic. The present work deals with the characterization of the shredder residue coming from an industrial plant, representative of the Italian situation, as for annual fluxes and technologies involved. The aim of this study is to characterize ASR in order to study and develop a cost effective and environmentally sustainable recycling system. Results show that almost half of the residue is made of fines and the remaining part is mainly composed of polymers. Fine fraction is the most contaminated by mineral oils and heavy metals. This fraction produces also up to 40% ashes and its LHV is lower than the plastic-rich one. Foam rubber represents around half of the polymers share in car fluff. Moreover, some chemical–physical parameters exceed the limits of some parameters fixed by law to be considered refuse derived fuel (RDF). As a consequence, ASR needs to be pre-treated in order to follow the energy recovery route.     

Assessing ICT risk through a Monte Carlo method

To assess and manage the risk due to an information and communication system before its deployment, data of interest can be produced by a Monte Carlo method. This paper presents Haruspex, a software tool that applies a Monte Carlo method to simulate intelligent and adaptive threat agents that reach predefined goals through plan with several attacks. The samples that Haruspex collects are used to compute statistics on the agent’s impacts and their plans as well as to select cost-effective countermeasures. We describe the rationale and the implementation of Haruspex, the inputs it requires and the simulation of how the agents select and implement their plans. After discussing the validation and the performance of the first version of Haruspex, we present a case study and the first set of experimental results.