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Background: Neonatal manifestation of life-threatening hyperammonemic encephalopathy in urea cycle disorders (UCD) is often misdiagnosed as neonatal sepsis, resulting in significantly delayed start of specific treatment and poor outcome. The major aim of this study was to identify specific initial symptoms or signs to clinically distinguish hyperammonemic encephalopathy in neonates from neonatal sepsis in order to identify affected individuals with UCD and to start metabolic therapy without delay. Furthermore, we evaluated the impact of diagnostic delay, peak plasma ammonium (NH4+) concentration, mode of emergency treatment and transfer to a tertiary referral center on the outcome.
Methods: Detailed information of 17 patients (born between 1994 and 2012) with confirmed diagnosis of UCD and neonatal hyperammonemic encephalopathy were collected from the original medical records.
Results: The initially suspected diagnosis was neonatal sepsis in all patients, but was not confirmed in any of them. Unlike neonatal sepsis and not previously reported blood pressure increased above the 95th percentile in 13 (81%) of UCD patients before emergency treatment was started. Respiratory alkalosis was found in 11 (65%) of UCD patients, and in 14 (81%) plasma NH4+concentrations further increased despite initiation of metabolic therapy.
Conclusion: Detection of high blood pressure could be a valuable parameter for distinguishing neonatal sepsis from neonatal manifestation of UCD. Since high blood pressure is not typical for neonatal sepsis, other reasons such as encephalopathy and especially hyperammonemic encephalopathy (caused by e.g. UCD) should be searched for immediately. However, our result that the majority of newborns with UCD initially present with high blood pressure has to be evaluated in larger patient cohorts.
As part of the CLACE-6 campaign we performed size-resolved CCN measurements for a~supersaturation range of S = 0.079 % to 0.66% at the high-alpine research station Jungfraujoch, Switzerland, in March~2007. The derived effective hygroscopicity parameter κ describing the influence of particle composition on CCN activity was on average 0.23–0.30 for Aitken (50–100 nm) and 0.32–0.43 for accumulation mode particles (100–200 nm). The campaign average value of κ = 0.3 is similar to the average value of κ for other continental locations. When air masses came from southeasterly directions crossing the Po Valley in Italy, particles were much more hygroscopic (κ ≈ 0.42) due to large sulfate mass fractions. The κ values obtained at S = 0.079 % exhibited a good negative correlation with the organic mass fractions derived from PM1 aerosol mass spectrometer (AMS) measurements. Applying a simple mixing rule the organic and inorganic mass fractions observed by the AMS could be used to reproduce the temporal fluctuations of the hygroscopicity of accumulation mode particles quite well.
We show how during a cloud event the aerosol particles were activated as cloud droplets and then removed from the air by precipitation leaving behind only a small amount of accumulation mode particles consisting mainly of weakly CCN-active particles, most likely externally mixed unprocessed soot particles.
During the campaign we had the opportunity to directly compare two DMT CCN counters for a certain time. The total CCN concentration (NCCN,tot) obtained by the two instruments at equal supersaturations agreed well for both possible operating modes: detecting NCCN,tot directly by sampling the polydisperse aerosol with the CCNC, or indirectly by combining size-resolved measurements of the activated fraction with parallel measurements of the particle size distribution (e.g., by SMPS). However, some supersaturation setpoints differed between the two CCNCs by as much as 20% after applying the instrument calibrations, which resulted in differences of the corresponding NCCN,tot of up to 50%. This emphasizes that it is extremely important to carefully calibrate the supersaturation of the instrument, especially at low S.
In this study we show how size-resolved measurements of aerosol particles and cloud condensation nuclei (CCN) can be used to characterize the supersaturation of water vapor in a cloud. The method was developed and applied for the investigation of a cloud event during the ACRIDICON-Zugspitze campaign (17 September to 4 October 2012) at the high-alpine research station Schneefernerhaus (German Alps, 2650 m a.s.l.). Number size distributions of total and interstitial aerosol particles were measured with a scanning mobility particle sizer (SMPS), and size-resolved CCN efficiency spectra were recorded with a CCN counter system operated at different supersaturation levels.
During the evolution of a cloud, aerosol particles are exposed to different supersaturation levels. We outline and compare different estimates for the lower and upper bounds (Slow, Shigh) and the average value (Savg) of peak supersaturation encountered by the particles in the cloud. For the investigated cloud event, we derived Slow ≈ 0.19–0.25%, Shigh ≈ 0.90–1.64% and Savg ≈ 0.38–0.84%. Estimates of Slow, Shigh and Savg based on aerosol size distribution data require specific knowledge or assumptions of aerosol hygroscopicity, which are not required for the derivation of Slow and Savg from the size-resolved CCN efficiency spectra.
In this study we show how size-resolved measurements of aerosol particles and cloud condensation nuclei (CCN) can be used to characterize the supersaturation of water vapor in a cloud. The method was developed and applied during the ACRIDICON-Zugspitze campaign (17 September to 4 October 2012) at the high-Alpine research station Schneefernerhaus (German Alps, 2650 m a.s.l.). Number size distributions of total and interstitial aerosol particles were measured with a scanning mobility particle sizer (SMPS), and size-resolved CCN efficiency spectra were recorded with a CCN counter system operated at different supersaturation levels.
During the evolution of a cloud, aerosol particles are exposed to different supersaturation levels. We outline and compare different estimates for the lower and upper bounds (Slow, Shigh) and the average value (Savg) of peak supersaturation encountered by the particles in the cloud. A major advantage of the derivation of Slow and Savg from size-resolved CCN efficiency spectra is that it does not require the specific knowledge or assumptions about aerosol hygroscopicity that are needed to derive estimates of Slow, Shigh, and Savg from aerosol size distribution data. For the investigated cloud event, we derived Slow ≈ 0.07–0.25%, Shigh ≈ 0.86–1.31% and Savg ≈ 0.42–0.68%.