All-in-one whole exome sequencing strategy with simultaneous copy number variant,single nucleotide variant and absence-of-heterozygosity analysis in fetuses with structural ultrasound anomalies: A 1-year experience

Objective

We performed a 1-year evaluation of a novel strategy of simultaneously analyzing single nucleotide variants (SNVs), copy number variants (CNVs) and copy-number-neutral Absence-of-Heterozygosity from Whole Exome Sequencing (WES) data for prenatal diagnosis of fetuses with ultrasound (US) anomalies and a non-causative QF-PCR result.

Methods

After invasive diagnostics, whole exome parent-offspring trio-sequencing with exome-wide CNV analysis was performed in pregnancies with fetal US anomalies and a non-causative QF-PCR result (WES-CNV). On request, additional SNV-analysis, restricted to (the) requested gene panel(s) only (with the option of whole exome SNV-analysis afterward) was performed simultaneously (WES-CNV/SNV) or as rapid SNV-re-analysis, following a normal CNV analysis.

Results

In total, 415 prenatal samples were included. Following a non-causative QF-PCR result, WES-CNV analysis was initially requested for 74.3% of the chorionic villus (CV) samples and 45% of the amniotic fluid (AF) samples. In case WES-CNV analysis did not reveal a causative aberration, SNV-re-analysis was requested in 41.7% of the CV samples and 17.5% of the AF samples. All initial analyses could be finished within 2 weeks after sampling. For SNV-re-analysis during pregnancy, turn-around-times (TATs) varied between one and 8 days.

Conclusion

We show a highly efficient all-in-one WES-based strategy, with short TATs, and the option of rapid SNV-re-analysis after a normal CNV result.     

Birthweight of children with isolated congenital heart disease—A sibling analysis study

Objective

Congenital heart disease (CHD) is associated with decreased birthweight (BW) compared to population-based references. The aim of this study was to compare the BW of isolated CHD cases to their siblings, thus controlling for unknown and unmeasured confounders within the family.

Methods

All isolated CHD cases in the Leiden University Medical Center were included (2002–2019). Generalized estimated equation models were constructed to compare BW z scores of CHD neonates with their siblings. Cases were clustered to minor or severe CHD and stratified according to the aortic flow and oxygenation to the brain.

Results

The overall BW z score of siblings was 0.032 (n = 471). The BW z score was significantly lower in CHD cases (n = 291) compared to their siblings (−0.20, p = 0.005). The results were consistent in the subgroup analysis of severe and minor CHD (BW z score difference −0.20 and −0.10), but did not differ significantly (p = 0.63). Stratified analysis regarding flow and oxygenation showed no BW difference between the groups (p = 0.1).

Conclusion

Isolated CHD cases display a significantly lower BW z score compared to their siblings. As the siblings of these CHD cases show a BW distribution similar to the general population, this suggests that shared environmental and maternal influences between siblings do not explain the difference in BW.     

Perinatal outcome after selective fetal reduction in monochorionic twin pregnancies: A comparison of techniques over a 20-year period

Objective

To assess the perinatal outcome after fetal reduction in complicated monochorionic (MC) twin pregnancies by comparing different techniques.

Methods

A retrospective cohort study at a national referral center comparing data between four techniques: interstitial laser coagulation, radiofrequency ablation (RFA), fetoscopic laser coagulation (FLC) and bipolar cord coagulation (BCC). The primary outcome was the mortality of the co-twins. Secondary outcomes were preterm pre-labor rupture of membranes (PPROM), gestational age at delivery and neonatal morbidity.

Results

259 MC twin pregnancies underwent selective fetal reduction: 29 IL, 64 RFA, 85 FLC and 81 BCC. The perinatal mortality rate was 29% and fetal demise of the co-twins occurred in 19%. The lowest mortality rate was seen after BCC (17%, p = 0.012). PPROM occurred in 18% patients without significant differences between techniques. The mean gestational age at delivery in liveborn children was 35 weeks and did not differ between techniques. Severe cerebral injury and neonatal morbidity were reported in 4% and 14%, respectively, without significant differences between techniques.

Conclusions

Selective fetal reductions in MC twins are precarious procedures with an increased risk of perinatal mortality of the co-twins. Our results show the lowest mortality rates after BCC. However, high PPROM rates were seen irrespective of the technique.     

Greenhouse gas emissions along a peat swamp forest degradation gradient in the Peruvian Amazon: soil moisture and palm roots effects

Tropical peatlands in the Peruvian Amazon exhibit high densities of Mauritia flexuosa palms, which are often cut instead of being climbed for collecting their fruits. This is an important type of forest degradation in the region that could lead to changes in the structure and composition of the forest, quality and quantity of inputs to the peat, soil properties, and greenhouse gas (GHG) fluxes. We studied peat and litterfall characteristics along a forest degradation gradient that included an intact site, a moderately degraded site, and a heavily degraded site. To understand underlying factors driving GHG emissions, we examined the response of in vitro soil microbial GHG emissions to soil moisture variation, and we tested the potential of pneumatophores to conduct GHGs in situ. The soil phosphorus and carbon content and carbon-to-nitrogen ratio as well as the litterfall nitrogen content and carbon-to-nitrogen ratio were significantly affected by forest degradation. Soils from the degraded sites consistently produced more carbon dioxide (CO₂) than soils from the intact site during in vitro incubations. The response of CO₂ production to changes in water-filled pore space (WFPS) followed a cubic polynomial relationship with maxima at 60–70% at the three sites. Methane (CH₄) was produced in limited amounts and exclusively under water-saturated conditions. There was no significant response of nitrous oxide (N₂O) emissions to WFPS variation. Lastly, the density of pneumatophore decreased drastically as the result of forest degradation and was positively correlated to in situ CH₄ emissions. We conclude that recurrent M. flexuosa harvesting could result in a significant increase of in situ CO₂ fluxes and a simultaneous decrease in CH₄ emissions via pneumatophores. These changes might alter long-term carbon and GHG balances of the peat, and the role of these ecosystems for climate change mitigation, which stresses the need for their protection.

     

Chloramine demand estimation using surrogate chemical and microbiological parameters

A model is developed to enable estimation of chloramine demand in full scale drinking water supplies based on chemical and microbiological factors that affect chloramine decay rate via nonlinear regression analysis method. The model is based on organic character (specific ultraviolet absorbance (SUVA)) of the water samples and a laboratory measure of the microbiological (F m ) decay of chloramine. The applicability of the model for estimation of chloramine residual (and hence chloramine demand) was tested on several waters from different water treatment plants in Australia through statistical test analysis between the experimental and predicted data. Results showed that the model was able to simulate and estimate chloramine demand at various times in real drinking water systems. To elucidate the loss of chloramine over the wide variation of water quality used in this study, the model incorporates both the fast and slow chloramine decay pathways. The significance of estimated fast and slow decay rate constants as the kinetic parameters of the model for three water sources in Australia was discussed. It was found that with the same water source, the kinetic parameters remain the same. This modelling approach has the potential to be used by water treatment operators as a decision support tool in order to manage chloramine disinfection.     

Economic analysis of adaptive strategies for flood risk management under climate change

Climate change requires reconsideration of flood risk management strategies. Cost-benefit analysis (CBA), an economic decision-support tool, has been widely applied to assess these strategies. This paper aims to describe and discuss probabilistic extensions of CBA to identify welfare-maximising flood risk management strategies under climate change. First, uncertainty about the changes in return periods of hydro-meteorological extremes is introduced by probability-weighted climate scenarios. Second, the analysis is extended by learning about climate change impacts. Learning occurs upon the probabilistic arrival of information. We distinguish between learning from scientific progress, from statistical evidence and from flood disasters. These probabilistic extensions can be used to analyse and compare the economic efficiency and flexibility of flood risk management strategies under climate change. We offer a critical discussion of the scope of such extensions and options for increasing flexibility. We find that uncertainty reduction from scientific progress may reduce initial investments, while other types of learning may increase initial investments. This requires analysing effects of different types of learning. We also find that probabilistic information about climate change impacts and learning is imprecise. We conclude that risk-based CBA with learning improves the flexibility of flood risk management strategies under climate change. However, CBA provides subjective estimates of expected outcomes and reflects different decision-maker preferences than those captured in robustness analyses. We therefore advocate robustness analysis in addition to, or combined with, cost-benefit analysis to support local investment decisions on flood risk reduction and global strategies on allocation of adaptation funds for flood risk management.     

Does your facility have a dust problem: Methods for evaluating dust explosion hazards

The hazards of dust explosions prevailing in plants are dependent on a large variety of factors that include process parameters, such as pressure, temperature and flow characteristics, as well as equipment properties, such as geometry layout, the presence of moving elements, dust explosion characteristics and mitigating measures. A good dust explosion risk assessment is a thorough method involving the identification of all hazards, their probability of occurrence and the severity of potential consequences. The consequences of dust explosions are described as consequences for personnel and equipment, taking into account consequences of both primary and secondary events.While certain standards cover all the basic elements of explosion prevention and protection, systematic risk assessments and area classifications are obligatory in Europe, as required by EU ATEX and Seveso II directives. In the United States, NFPA 654 requires that the design of the fire and explosion safety provisions shall be based on a process hazard analysis of the facility, process, and the associated fire or explosion hazards. In this paper, we will demonstrate how applying such techniques as SCRAM (short-cut risk analysis method) can help identify potentially hazardous conditions and provide valuable assistance in reducing high-risk areas. The likelihood of a dust explosion is based on the ignition probability and the probability of flammable dust clouds arising. While all possible ignition sources are reviewed, the most important ones include open flames, mechanical sparks, hot surfaces, electric equipment, smoldering combustion (self-ignition) and electrostatic sparks and discharges. The probability of dust clouds arising is closely related to both process and dust dispersion properties.Factors determining the consequences of dust explosions include how frequently personnel are present, the equipment strength, implemented consequence-reducing measures and housekeeping, as risk assessment techniques demonstrate the importance of good housekeeping especially due to the enormous consequences of secondary dust explosions (despite their relatively low probability). The ignitibility and explosibility of the potential dust clouds also play a crucial role in determining the overall risk.Classes describe both the likelihood of dust explosions and their consequences, ranging from low probabilities and limited local damage, to high probability of occurrence and catastrophic damage. Acceptance criteria are determined based on the likelihood and consequence of the events. The risk assessment techniques also allow for choosing adequate risk reducing measures: both preventive and protective. Techniques for mitigating identified explosions risks include the following: bursting disks and quenching tubes, explosion suppression systems, explosion isolating systems, inerting techniques and temperature control. Advanced CFD tools (DESC) can be used to not only assess dust explosion hazards, but also provide valuable insight into protective measures, including suppression and venting.     

Use of SOFEA to predict 1,3-D concentrations in air in high-use regions of California

Methyl bromide, a commonly used soil fumigant, is being phased out per the Montreal Protocol and multiple fumigants are being positioned as replacements. Most effective soil fumigants, including methyl bromide, have the potential for inhalation exposure if the material volatilizes from soil. Chronic exposures for the fumigant 1,3-dichloropropene (1,3-D) are managed in part by the California Department of Pesticide Regulation by limiting the annual amount that can be used within a given township. A stochastic/deterministic numerical system (SOil Fumigant Exposure Assessment system [SOFEA]) was developed using the USEPA air dispersion model ISCST3, field study observations for flux loss, and links to Geographic Information Systems (GIS). SOFEA was used retrospectively to simulate concentrations of 1,3-D in air for direct comparison with monitoring program observations conducted by California Air Resources Board in Fresno County. These results indicated slight overprediction but correct magnitudes for regional air concentrations, especially at the higher percentiles, and provide a performance test. SOFEA was also used, prospectively, to predict air concentrations in potential future-use scenarios. These simulations of chronic air concentrations in two high-use 1,3-D counties of California (Ventura, Merced) consisted of 25 contiguous townships treated either at 1.5 times the current township allocation (40,937 kg) or at the maximum levels of 1,3-D used between 1999 and 2006. Exposure predictions for large regions are necessary to evaluate chronic population-based lifetime exposure and risk to 1,3-D should use patterns change. SOFEA provides a tool to estimate regional air concentrations within high-use areas required for such risk assessments.     

Coupling field observations, soil modeling, and air dispersion algorithms to estimate 1,3-dichloropropene and chloropicrin flux and exposure

Soil fumigants are volatile compounds applied to agricultural land to control nematode populations, weeds, and crop diseases. Field trials used for measuring fumigant loss from soil to the atmosphere encompass only a small proportion of the near semi-infinite parameter combinations of environmental, agronomic, and meteorological conditions. One approach to supplement field observations uses a soil physics model for fumigant emission predictions. A model is first validated against existing field study observations and then used to extrapolate results to a wider range of edaphic and climatic conditions. This work compares field observations of 1,3-dichloropropene and chloropicrin emissions to predictions from the USDA soil model CHAIN_2D. Comparison between model predictions and field observations for a Florida and California study had values between 0.62 to 0.81 and 0.99 to 1.0 for discrete and cumulative emission flux, respectively. CHAIN_2D emission rates were then coupled to several USEPA air dispersion models (ISCST3, CALPUFF6) to extend emission estimates to near field air concentrations. CALPUFF6 predicted slightly higher 1-h maximum air concentrations than ISCST3 for the same source strength (26.2-36.0% for setbacks between 1 and 250 m from the field edge, respectively). A sensitivity analysis for the CHAIN_2D/ISCST3 coupled numerical system is provided, with several soil and irrigation parameters consistently the most sensitive. Changes in the depth of incorporation, tarp material, and initial soil water content illustrate the predicted impact to emission strength and resulting near-field air concentrations with reductions of cumulative emission loss from 8.1 to 71% and average 1-h maximum air concentration reductions between 6.2 and 41% depending on the mitigation strategy chosen. Additionally, a stochastic framework based on the published SOFEA system that couples variability in experiment, model sensitivity, and site specific attributes is outlined should regional air concentration estimates resulting from fumigant use be sought.