Prediction of likelihood of conception in dairy cows using milk mid-infrared spectra collected before the first insemination and machine learning algorithms.

Accurate and ex-ante prediction of cows' likelihood of conception (LC) based on milk composition information could improve reproduction management on dairy farms. Milk composition is already routinely measured by mid-infrared (MIR) spectra, which are known to change with advancing stages of pregnancy. For lactating cows, MIR spectra may also be used for predicting the LC. Our objectives were to classify the LC at first insemination using milk MIR spectra data collected from calving to first insemination and to identify the spectral regions that contribute the most to the prediction of LC at first insemination. After quality control, 4,866 MIR spectra, milk production, and reproduction records from 3,451 Holstein cows were used. The classification accuracy and area under the curve (AUC) of 6 models comprising different predictors and 3 machine learning methods were estimated and compared. The results showed that partial least square discriminant analysis (PLS-DA) and random forest had higher prediction accuracies than logistic regression. The classification accuracy of good and poor LC cows and AUC in herd-by-herd validation of the best model were 76.35 ± 10.60% and 0.77 ± 0.11, respectively. All wavenumbers with values of variable importance in the projection higher than 1.00 in PLS-DA belonged to 3 spectral regions, namely from 1,003 to 1,189, 1,794 to 2,260, and 2,300 to 2,660 cm-1. In conclusion, the model can predict LC in dairy cows from a high productive TMR system before insemination with a relatively good accuracy, allowing farmers to intervene in advance or adjust the insemination schedule for cows with a poor predicted LC.

Reliability and usefulness of upper gastro intestinal contrast studies to assess pouch size in patients with weight loss failure after Roux-en-Y gastric bypass.

Background: Weight loss failure or weight regain occurs in up to 25% of patients with a Roux-en-Y gastric bypass (RYGB). Post-operative anatomical changes, like pouch or stoma dilatation, might contribute. Aim of this study is to assess reliability and usefulness of upper gastro intestinal (UGI) contrast studies to detect pouch dilatation.Methods: Retrospective case-control study of patients with weight loss failure between 2010 and 2015 (failure group, n = 101) and a control group (n = 101) with adequate weight loss. Pouch dilatation was systematically reassessed. Clinical parameters were extracted from the electronic patient records.Results: Systematic reassessment showed 23/101 (23%) pouch dilatation in the failure group, compared to 11/101 (11%) in the control group (p = .024). Revision surgery was performed in 43/101 patients in the failure group. After this surgery, only 8% of patients with pouch dilatation achieved adequate weight loss, whereas 39% of patients without pouch dilatation achieved adequate weight loss (p = .07). There was no difference in return to adequate weight loss between patients treated surgically and conservatively (30% vs 28%).Conclusion: Systematic reassessment of UGI contrast studies showed 23% pouch dilatation in patients with weight loss failure after RYGB. However, low interobserver agreement and discrepancy in success rate of revision surgery greatly questions the reliability and usefulness of this diagnostic modality.

Diffusion kurtosis imaging probes cortical alterations and white matter pathology following cuprizone induced demyelination and spontaneous remyelination.

Although MRI is the gold standard for the diagnosis and monitoring of multiple sclerosis (MS), current conventional MRI techniques often fail to detect cortical alterations and provide little information about gliosis, axonal damage and myelin status of lesioned areas. Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) provide sensitive and complementary measures of the neural tissue microstructure. Additionally, specific white matter tract integrity (WMTI) metrics modelling the diffusion in white matter were recently derived. In the current study we used the well-characterized cuprizone mouse model of central nervous system demyelination to assess the temporal evolution of diffusion tensor (DT), diffusion kurtosis tensor (DK) and WMTI-derived metrics following acute inflammatory demyelination and spontaneous remyelination. While DT-derived metrics were unable to detect cuprizone induced cortical alterations, the mean kurtosis (MK) and radial kurtosis (RK) were found decreased under cuprizone administration, as compared to age-matched controls, in both the motor and somatosensory cortices. The MK remained decreased in the motor cortices at the end of the recovery period, reflecting long lasting impairment of myelination. In white matter, DT, DK and WMTI-derived metrics enabled the detection of cuprizone induced changes differentially according to the stage and the severity of the lesion. More specifically, the MK, the RK and the axonal water fraction (AWF) were the most sensitive for the detection of cuprizone induced changes in the genu of the corpus callosum, a region less affected by cuprizone administration. Additionally, microgliosis was associated with an increase of MK and RK during the acute inflammatory demyelination phase. In regions undergoing severe demyelination, namely the body and splenium of the corpus callosum, DT-derived metrics, notably the mean diffusion (MD) and radial diffusion (RD), were among the best discriminators between cuprizone and control groups, hence highlighting their ability to detect both acute and long lasting changes. Interestingly, WMTI-derived metrics showed the aptitude to distinguish between the different stages of the disease. Both the intra-axonal diffusivity (Da) and the AWF were found to be decreased in the cuprizone treated group, Da specifically decreased during the acute inflammatory demyelinating phase whereas the AWF decrease was associated to the spontaneous remyelination and the recovery period. Altogether our results demonstrate that DKI is sensitive to alterations of cortical areas and provides, along with WMTI metrics, information that is complementary to DT-derived metrics for the characterization of demyelination in both white and grey matter and subsequent inflammatory processes associated with a demyelinating event.

Differential hippocampal gene expression is associated with climate-related natural variation in memory and the hippocampus in food-caching chickadees.

There is significant and often heritable variation in cognition and its underlying neural mechanisms, yet specific genetic contributions to such variation are not well characterized. Black-capped chickadees present a good model to investigate the genetic basis of cognition because they exhibit tremendous climate-related variation in memory, hippocampal morphology and neurogenesis rates throughout the North American continent, and these cognitive traits appear to have a heritable basis. We examined the hippocampal transcriptome profiles of laboratory-reared chickadees from the two most divergent populations to test whether differential gene expression in the hippocampus is associated with population differences in spatial memory, hippocampal morphology and adult hippocampal neurogenesis rates. Using high-resolution mRNA sequencing coupled to a de novo transcriptome assembly, we generated 23 295 consensus sequences, which predicted 16 206 protein sequences with 13 982 showing high similarity to known protein sequences or conserved hypothetical proteins in other species. Of these, we identified differential expression in nearly 380 genes, with 47 genes specifically linked to neurogenesis, apoptosis, synaptic function, and learning and memory processes. Many of the other differentially expressed genes, however, may be associated with other functions. Our study presents the first avian hippocampal transcriptome, and it is the first study identifying differential gene expression associated with natural variation in cognition and the hippocampus. Our results provide additional support to the hypothesis that population differences in memory, hippocampal morphology and neurogenesis in chickadees have likely resulted from natural selection that appears to act on memory and its underlying neural mechanisms.

Frequency division multiplexing readout of a transition edge sensor bolometer array with microstrip-type electrical bias lines.

We demonstrate multiplexed readout of 43 transition edge sensor (TES) bolometers operating at 90 mK using a frequency division multiplexing (FDM) readout chain with bias frequencies ranging from 1 to 3.5 MHz and a typical frequency spacing of 32 kHz. We improve the previously reported performance of our FDM system by two important steps. First, we replace the coplanar wires with microstrip wires, which minimize the cross talk from mutual inductance. From the measured electrical cross talk (ECT) map, the ECT of all pixels is carrier leakage dominated. Only five pixels show an ECT level higher than 1%. Second, we reduce the thermal response speed of the TES detectors by a factor of 20 by increasing the heat capacity of the TES, which allows us to bias all TES detectors below 50% in transition without oscillations. We compare the current-voltage curves and noise spectra of the TESs measured in single-pixel mode and multiplexing mode. We also compare the noise equivalent power (NEP) and the saturation power of the bolometers in both modes, where 38 pixels show less than 10% difference in NEP and 5% difference in saturation power when measured in the two different modes. The measured noise spectrum is in good agreement with the simulated noise based on measured parameters from an impedance measurement, confirming that our TES is dominated by phonon noise.

Evaluation of the specificity and sensitivity of ferritin as an MRI reporter gene in the mouse brain using lentiviral and adeno-associated viral vectors.

The development of in vivo imaging protocols to reliably track transplanted cells or to report on gene expression is critical for treatment monitoring in (pre)clinical cell and gene therapy protocols. Therefore, we evaluated the potential of lentiviral vectors (LVs) and adeno-associated viral vectors (AAVs) to express the magnetic resonance imaging (MRI) reporter gene ferritin in the rodent brain. First, we compared the induction of background MRI contrast for both vector systems in immune-deficient and immune-competent mice. LV injection resulted in hypointense (that is, dark) changes of T(2)/T(2)(*) (spin-spin relaxation time)-weighted MRI contrast at the injection site, which can be partially explained by an inflammatory response against the vector injection. In contrast to LVs, AAV injection resulted in reduced background contrast. Moreover, AAV-mediated ferritin overexpression resulted in significantly enhanced contrast to background on T(2)(*)-weighted MRI. Although sensitivity associated with the ferritin reporter remains modest, AAVs seem to be the most promising vector system for in vivo MRI reporter gene imaging.

Similarities and differences between measured and predicted concentrations of pesticides in Dutch surface waters.

In order to have a thorough evaluation of the progress and effectiveness of Dutch crop protection policy, both model predictions and measured pesticide concentrations in surface waters are considered. To this purpose, monitoring data obtained by various water boards and other monitoring institutes were processed. Data were aggregated over a two year time period and over space (at 1x1 km-grid). A geographic view is given in the Dutch Pesticides Atlas (www.pesticidesatlas.nl). The model used for the predictions was the Dutch National Environmental Indicator NMI version 2 (www.nmi.alterra.nl) that has input data regarding spray drift data, crop interception, soil and climate and many more. Information on aggregation steps over time and space, grid sizes, information on crop areas was geared to one another for both instruments. Results on measured pesticide concentrations in surface waters and model predictions were compared to each other at the national scale. For this study, 10 different cases were selected covering a large range of pesticides' characteristics and pesticides' use. In 60% of the cases, the results were largely in agreement with each other when expressed as absolute numbers of measurements exceeding the environmental quality standard. This is very accurate and useful for policy purposes. Based on concentrations and on the order of magnitude, no significant agreement between measurements and model predictions was found. Differences were explained by various factors, and an overview of predominant systematic differences between the measurements and the model predictions was presented. Using both measurements and model predictions in supporting environmental policy evaluations is warranted, because of higher Weight-of-Evidence. Combining both can assist in optimizing the knowledge on pesticides behaviour, fate and ecological problems and therefore this is the preferred evaluation method.

Electrical cross talk of a frequency division multiplexing readout for a transition edge sensor bolometer array.

We have characterized and mapped the electrical cross talk (ECT) of a frequency division multiplexing (FDM) system with a transition edge sensor (TES) bolometer array, which is intended for space applications. By adding a small modulation at 120 Hz to the AC bias voltage of one bolometer and measuring the cross talk response in the current noise spectra of the others simultaneously, we have for the first time mapped the ECT level of 61 pixels with a nominal frequency spacing of 32 kHz in a 61 × 61 matrix and a carrier frequency ranging from 1 MHz to 4 MHz. We find that about 94% of the pixels show an ECT level of less than 0.4%. Only the adjacent pixels reach this level, and the ECT for the rest of the pixels is less than 0.1%. We also observe higher ECT levels, up to 10%, between some of the pixels, which have bundled long, parallel coplanar wires connecting TES bolometers to inductor-capacitor filters. In this case, the high mutual inductances dominate. To mitigate this source of ECT, the coplanar wires should be replaced by microstrip wires in the array. Our study suggests that an FDM system can have a relatively low ECT level, e.g., around 0.4% if the frequency spacing is 30 kHz. Our results successfully demonstrate a low electrical cross talk for a space FDM technology.

Frequency shift algorithm: Application to a frequency-domain multiplexing readout of x-ray transition-edge sensor microcalorimeters.

In the frequency-domain multiplexing (FDM) scheme, transition-edge sensors (TESs) are individually coupled to superconducting LC filters and AC biased at MHz frequencies through a common readout line. To make efficient use of the available readout bandwidth and to minimize the effect of non-linearities, the LC resonators are usually designed to be on a regular grid. The lithographic processes, however, pose a limit on the accuracy of the effective filter resonance frequencies. Off-resonance bias carriers could be used to suppress the impact of intermodulation distortions, which, nonetheless, would significantly affect the effective bias circuit and the detector spectral performance. In this paper, we present a frequency shift algorithm (FSA) to allow off-resonance readout of TESs, while preserving the on-resonance bias circuit and spectral performance, demonstrating its application to the FDM readout of an x-ray TES microcalorimeter array. We discuss the benefits in terms of mitigation of the impact of intermodulation distortions at the cost of increased bias voltage and the scalability of the algorithm to multi-pixel FDM readout. We show that with FSA, in the multi-pixel and frequencies shifted on-grid, the line noises due to intermodulation distortion are placed away from the sensitive region in the TES response and the x-ray performance is consistent with the single-pixel, on-resonance level.

Genomic monitoring to understand the emergence and spread of Usutu virus in the Netherlands, 2016-2018.

Usutu virus (USUV) is a mosquito-borne flavivirus circulating in Western Europe that causes die-offs of mainly common blackbirds (Turdus merula). In the Netherlands, USUV was first detected in 2016, when it was identified as the likely cause of an outbreak in birds. In this study, dead blackbirds were collected, screened for the presence of USUV and submitted to Nanopore-based sequencing. Genomic sequences of 112 USUV were obtained and phylogenetic analysis showed that most viruses identified belonged to the USUV Africa 3 lineage, and molecular clock analysis evaluated their most recent common ancestor to 10 to 4 years before first detection of USUV in the Netherlands. USUV Europe 3 lineage, commonly found in Germany, was less frequently detected. This analyses further suggest some extent of circulation of USUV between the Netherlands, Germany and Belgium, as well as likely overwintering of USUV in the Netherlands.

Influence of pH-dependent sorption and transformation on simulated pesticide leaching.

The leaching of a substance is influenced by its physico-chemical characteristics as well as environmental conditions. In spatially distributed modelling the influence of soil properties on the half-life and the sorption constant of the substance might become important and can be taken into account. The GeoPEARL model includes options to account for sorption and transformation being dependent on soil characteristics. Using some of these options in calculations for a herbicide with both sorption and transformation dependent on the pH of the soil, the calculated leaching from an application in spring appeared to be higher than anticipated from calculations according to the so-called paired parameter approach, in which the leaching is assessed for pairs of sorption and transformation parameters at regular pH intervals. The reason for the higher leaching was that the most critical leaching conditions were not covered by the selected pH values. A 'paired approach' might however be useful as a first tier assessment of the leaching potential. The maximum leaching is expected with the highest DegT(50)/K(om) ratio, which might be obtained from plotting this ratio against the characteristic soil property. The leaching potential of the parent was more important for the leaching of the metabolite than the leaching potential of the metabolite itself. This should be accounted for in the evaluation procedure.

LiGAPS-Beef, a mechanistic model to explore potential and feed-limited beef production 2: sensitivity analysis and evaluation of sub-models.

The model LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems - Beef cattle) has been developed to assess potential and feed-limited growth and production of beef cattle in different areas of the world and to identify the processes responsible for the yield gap. Sensitivity analysis and evaluation of model results with experimental data are important steps after model development. The first aim of this paper, therefore, is to identify which parameters affect the output of LiGAPS-Beef most by conducting sensitivity analyses. The second aim is to evaluate the accuracy of the thermoregulation sub-model and the feed intake and digestion sub-model with experimental data. Sensitivity analysis was conducted using a one-at-a-time approach. The upper critical temperature (UCT) simulated with the thermoregulation sub-model was most affected by the body core temperature and parameters affecting latent heat release from the skin. The lower critical temperature (LCT) and UCT were considerably affected by weather variables, especially ambient temperature and wind speed. Sensitivity analysis for the feed intake and digestion sub-model showed that the digested protein per kg feed intake was affected to a larger extent than the metabolisable energy (ME) content. Sensitivity analysis for LiGAPS-Beef was conducted for ¾ Brahman×» Shorthorn cattle in Australia and Hereford cattle in Uruguay. Body core temperature, conversion of digestible energy to ME, net energy requirements for maintenance, and several parameters associated with heat release affected feed efficiency at the herd level most. Sensitivity analyses have contributed, therefore, to insight which parameters are to be investigated in more detail when applying LiGAPS-Beef. Model evaluation was conducted by comparing model simulations with independent data from experiments. Measured heat production in experiments corresponded fairly well to the heat production simulated with the thermoregulation sub-model. Measured ME contents from two data sets corresponded well to the ME contents simulated with the feed intake and digestion sub-model. The relative mean absolute errors were 9.3% and 6.4% of the measured ME contents for the two data sets. In conclusion, model evaluation indicates the thermoregulation sub-model can deal with a wide range of weather conditions, and the feed intake and digestion sub-model with a variety of feeds, which corresponds to the aim of LiGAPS-Beef to simulate cattle in different beef production systems across the world.

LiGAPS-Beef, a mechanistic model to explore potential and feed-limited beef production 1: model description and illustration.

The expected increase in the global demand for livestock products calls for insight in the scope to increase actual production levels across the world. This insight can be obtained by using theoretical concepts of production ecology. These concepts distinguish three production levels for livestock: potential (i.e. theoretical maximum) production, which is defined by genotype and climate only; feed-limited production, which is limited by feed quantity and quality; and actual production. The difference between the potential or limited production and the actual production is the yield gap. The objective of this paper, the first in a series of three, is to present a mechanistic, dynamic model simulating potential and feed-limited production for beef cattle, which can be used to assess yield gaps. A novelty of this model, named LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems - Beef cattle), is the identification of the defining factors (genotype and climate) and limiting factors (feed quality and available feed quantity) for cattle growth by integrating sub-models on thermoregulation, feed intake and digestion, and energy and protein utilisation. Growth of beef cattle is simulated at the animal and herd level. The model is designed to be applicable to different beef production systems across the world. Main model inputs are breed-specific parameters, daily weather data, information about housing, and data on feed quality and quantity. Main model outputs are live weight gain, feed intake and feed efficiency (FE) at the animal and herd level. Here, the model is presented, and its use is illustrated for Charolais and Brahman × Shorthorn cattle in France and Australia. Potential and feed-limited production were assessed successfully, and we show that FE of herds is highest for breeds most adapted to the local climate conditions. LiGAPS-Beef also identified the factors that define and limit growth and production of cattle. Hence, we argue the model has scope to be used as a tool for the assessment and analysis of yield gaps in beef production systems.

LiGAPS-Beef, a mechanistic model to explore potential and feed-limited beef production 3: model evaluation.

LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems - Beef cattle) is a generic, mechanistic model designed to quantify potential and feed-limited growth, which provides insight in the biophysical scope to increase beef production (i.e. yield gap). Furthermore, it enables identification of the bio-physical factors that define and limit growth, which provides insight in management strategies to mitigate yield gaps. The aim of this paper, third in a series of three, is to evaluate the performance of LiGAPS-Beef with independent experimental data. After model calibration, independent data were used from six experiments in Australia, one in Uruguay and one in the Netherlands. Experiments represented three cattle breeds, and a wide range of climates, feeding strategies and cattle growth rates. The mean difference between simulated and measured average daily gains (ADGs) was 137 g/day across all experiments, which equals 20.1% of the measured ADGs. The root mean square error was 170 g/day, which equals 25.0% of the measured ADGs. LiGAPS-Beef successfully simulated the factors that defined and limited growth during the experiments on a daily basis (genotype, heat stress, digestion capacity, energy deficiency and protein deficiency). The simulated factors complied well to the reported occurrence of heat stress, energy deficiency and protein deficiency at specific periods during the experiments. We conclude that the level of accuracy of LiGAPS-Beef is acceptable, and provides a good basis for acquiring insight in the potential and feed-limited production of cattle in different beef production systems across the world. Furthermore, its capacity to identify factors that define or limit growth and production provides scope to use the model for yield gap analysis.

Towards high quality real-time whole genome sequencing during outbreaks using Usutu virus as example.

Recently, protocols for amplicon based whole genome sequencing using Nanopore technology have been described for Ebola virus, Zika virus, yellow fever virus and West Nile virus. However, there is some debate regarding reliability of sequencing using this technology, which is important for applications beyond diagnosis such as linking lineages to outbreaks, tracking transmission pathways and pockets of circulation, or mapping specific markers. To our knowledge, no in depth analyses of the required read coverage to compensate for the error profile in Nanopore sequencing have been described. Here, we describe the validation of a protocol for whole genome sequencing of USUV using Nanopore sequencing by direct comparison to Illumina sequencing. To that point we selected brain tissue samples with high viral loads, typical for birds which died from USUV infection. We conclude that the low-cost MinION Nanopore sequencing platform can be used for characterization and tracking of Usutu virus outbreaks.

Measuring brain hemodynamic changes in a songbird: responses to hypercapnia measured with functional MRI and near-infrared spectroscopy.

Songbirds have been evolved into models of choice for the study of the cerebral underpinnings of vocal communication. Nevertheless, there is still a need for in vivo methods allowing the real-time monitoring of brain activity. Functional Magnetic Resonance Imaging (fMRI) has been applied in anesthetized intact songbirds. It relies on blood oxygen level-dependent (BOLD) contrast revealing hemodynamic changes. Non-invasive near-infrared spectroscopy (NIRS) is based on the weak absorption of near-infrared light by biological tissues. Time-resolved femtosecond white laser NIRS is a new probing method using real-time spectral measurements which give access to the local variation of absorbing chromophores such as hemoglobins. In this study, we test the efficiency of our time-resolved NIRS device in monitoring physiological hemodynamic brain responses in a songbird, the zebra finch (Taeniopygia guttata), using a hypercapnia event (7% inhaled CO(2)). The results are compared to those obtained using BOLD fMRI. The NIRS measurements clearly demonstrate that during hypercapnia the blood oxygen saturation level increases (increase in local concentration of oxyhemoglobin, decrease in deoxyhemoglobin concentration and total hemoglobin concentration). Our results provide the first correlation in songbirds of the variations in total hemoglobin and oxygen saturation level obtained from NIRS with local BOLD signal variations.

Pesticides in groundwater and drinking water wells: overview of the situation in the Netherlands.

In the Netherlands, many of the fresh groundwater resources are vulnerable to pollution. Owing to high population densities and intensive farming practices, pesticide residues are found in groundwater at many places. Hence a number of drinking water abstraction wells contain pesticides residues, causing considerable costs for purification. The Water Framework Directive (WFD) requires countries to assess the chemical status of groundwater bodies and set up monitoring plans for groundwater quality, including pesticides. 771 groundwater samples were taken from monitoring wells in 2006 and analysed for a broad list of pesticides in order to fulfil these requirements. Pesticide were detected in 27% of samples, while in 11% the WFD limit of 0.1 microg/l was exceeded. In this paper, these and earlier measurements are evaluated further, considering also measurements in drinking water wells, information about the origin of measured pesticides and calculated trends in use and emissions. The measurements in the monitoring wells showed that where pesticides are used, 15-55% (minimal and maximal estimation) of the wells in shallow groundwater (1 to 20 m below soil surface) contain pesticides residues at concentrations above 0.1 microg/l. When the metabolites BAM and AMPA are excluded (as not relevant in human toxicological terms), the estimation range is 7-37%. These patterns observed in shallow groundwater are reflected by the occurrence of pesticides in vulnerable abstraction wells that are used for the production of drinking water. The WFD requires the determination of both status and trends. The design of current monitoring network is evaluated from this perspective. Several recommendations are made for more adequate and efficient monitoring.

Auditory evoked BOLD responses in awake compared to lightly anaesthetized zebra finches.

Functional magnetic resonance imaging (fMRI) is increasingly used in cognitive neuroscience and has become a valuable tool in the study of auditory processing in zebra finches, a well-established model of learned vocal communication. Due to its sensitivity to head motion, most fMRI studies in animals are performed in anaesthetized conditions, which might significantly impact neural activity evoked by stimuli and cognitive tasks. In this study, we (1) demonstrate the feasibility of fMRI in awake zebra finches and (2) explore how light anaesthesia regimes affect auditory-evoked BOLD responses to biologically relevant songs. After an acclimation procedure, we show that fMRI can be successfully performed during wakefulness, enabling the detection of reproducible BOLD responses to sound. Additionally, two light anaesthesia protocols were tested (isoflurane and a combination of medetomidine and isoflurane), of which isoflurane alone appeared to be the most promising given the high success rate, non-invasive induction, and quick recovery. By comparing auditory evoked BOLD responses in awake versus lightly anaesthetized conditions, we observed overall effects of anaesthetics on cerebrovascular reactivity as reflected in the extent of positive and negative BOLD responses. Further, our results indicate that light anaesthesia has limited effects on selective BOLD responses to natural versus synthetic sounds.

DOSE EVALUATION FOR DIGITAL X-RAY IMAGING OF PREMATURE NEONATES.

X-ray radiography is a commonly used diagnostic method for premature neonates. However, because of higher radiosensitivity and young age, premature neonates are more sensitive to the detrimental effects of ionising radiation. Therefore, it is important to monitor and optimise radiation doses at the neonatal intensive care unit (NICU). The number of x-ray examinations, dose-area product (DAP) and effective doses are evaluated for three Dutch NICUs using digital flat panel detectors. Thorax, thorax-abdomen and abdomen protocols are included in this study. Median number of examinations is equal to 1 for all three hospitals. Median DAP ranges between 0.05 and 1.02 µGy m2 for different examination types and different weight categories. These examinations result in mean effective doses between 4 ± 4 and 30 ± 10 µSv per examination. Substantial differences in protocols and doses can be observed between hospitals. This emphasises the need for up-to-date reference levels formulated specifically for premature neonates.

Deficient alpha-1-antitrypsin phenotypes and persistent airflow limitation in severe asthma.

BACKGROUND: Persistent airflow limitation is common among patients with severe asthma, but its pathogenesis has not been fully clarified. Severe alpha-1-antitrypsin (AAT) deficiency is a risk factor of chronic airflow limitation and emphysema, and partially deficient phenotypes have been associated with an accelerated decline in lung function. We hypothesized that partial deficiency of AAT (non-PiM AAT phenotype) is a risk factor of persistent airflow limitation in asthma. METHODS: In 122 patients with severe asthma (86 females; age (median (range)): 44.0 yr (18-75)) postbronchodilator FEV1 and FEV1/VC were measured and the AAT phenotype was determined. Persistent airflow limitation was defined as postbronchodilator FEV1 or FEV1/VC < 75% pred. with TLC > 75% pred. RESULTS: Six patients (4.9%) had a non-PiM phenotype (1 MF, 3 MS, 1 MZ and 1 SZ). Of the 58 patients with persistent airflow limitation only 1 patient (1.7%) had a non-PiM phenotype vs. 7.8% among the patients without persistent airflow limitation (P = 0.21). Postbronchodilator FEV1/VC (% pred.) was higher in the non-PiM patients than in the PiM patients (P = 0.02), the other lung function parameters were not different. Linear regression analysis showed no association between AAT phenotype and FEV1% predicted (P = 0.26). CONCLUSIONS: AAT heterozygoty does not seem to be an important risk factor of persistent airflow limitation in patients with asthma. Although confirmation by longitudinal follow-up studies with larger sample sizes is needed, these results suggest that routine assessment of the AAT phenotype is not indicated in asthmatic patients even if they exhibit fixed airflow limitation.