Maternal smoking during pregnancy is linked to reduced birth weight but the gestation at onset of this relationship is not certain. We present a systematic review of the literature describing ...associations between maternal smoking during pregnancy and ultrasound measurements of fetal size, together with an accompanying meta-analysis.
Studies were selected from electronic databases (OVID, EMBASE and Google Scholar) that examined associations between maternal smoking or smoke exposure and antenatal fetal ultrasound measurements. Outcome measures were first, second or third trimester fetal measurements.
There were 284 abstracts identified, 16 papers were included in the review and the meta-analysis included data from eight populations. Maternal smoking was associated with reduced second trimester head size (mean reduction 0.09 standard deviation (SD) 95% CI 0.01, 0.16) and femur length (0.06 0.01, 0.10) and reduced third trimester head size (0.18 SD 0.13, 0.23), femur length (0.27 SD 0.21, 0.32) and estimated fetal weight (0.18 SD 0.11, 0.24). Higher maternal cigarette consumption was associated with a lower z score for head size in the second (mean difference 0.09 SD 0, 0.19) and third (0.15 SD 0.03, 0.26) trimesters compared to lower consumption. Fetal measurements were not reduced for those whose mothers quit before or after becoming pregnant compared to mothers who had never smoked.
Maternal smoking during pregnancy is associated with reduced fetal measurements after the first trimester, particularly reduced head size and femur length. These effects may be attenuated if mothers quit or reduce cigarette consumption during pregnancy.
The increase of publicly available bioactivity data in recent years has fueled and catalyzed research in chemogenomics, data mining, and modeling approaches. As a direct result, over the past few ...years a multitude of different methods have been reported and evaluated, such as target fishing, nearest neighbor similarity-based methods, and Quantitative Structure Activity Relationship (QSAR)-based protocols. However, such studies are typically conducted on different datasets, using different validation strategies, and different metrics. In this study, different methods were compared using one single standardized dataset obtained from ChEMBL, which is made available to the public, using standardized metrics (BEDROC and Matthews Correlation Coefficient). Specifically, the performance of Naïve Bayes, Random Forests, Support Vector Machines, Logistic Regression, and Deep Neural Networks was assessed using QSAR and proteochemometric (PCM) methods. All methods were validated using both a random split validation and a temporal validation, with the latter being a more realistic benchmark of expected prospective execution. Deep Neural Networks are the top performing classifiers, highlighting the added value of Deep Neural Networks over other more conventional methods. Moreover, the best method (‘DNN_PCM’) performed significantly better at almost one standard deviation higher than the mean performance. Furthermore, Multi-task and PCM implementations were shown to improve performance over single task Deep Neural Networks. Conversely, target prediction performed almost two standard deviations under the mean performance. Random Forests, Support Vector Machines, and Logistic Regression performed around mean performance. Finally, using an ensemble of DNNs, alongside additional tuning, enhanced the relative performance by another 27% (compared with unoptimized ‘DNN_PCM’). Here, a standardized set to test and evaluate different machine learning algorithms in the context of multi-task learning is offered by providing the data and the protocols.
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This article reviews the creative ways in which the sixth Secretary-General of the United Nations, Boutros Boutros-Ghali, used the UN Secretariat to achieve his goals, as well as the obstacles he ...faced in doing so. Using new sources - including confidential UN memos, elite interviews, and private archives - the paper suggests that, in the context of peacekeeping, the former Secretary-General engaged in parallel processes of 'politicization' and 'depoliticization': on the one hand he minimised, avoided and concealed the substantive dimensions of certain decisions, units and issues with the aim of marginalising those departments and officials that he saw as too close to the United States, while on the other he empowered those bureaucratic units which he felt he could more easily control. Specifically, by bestowing upon the Department of Political Affairs (DPA) a sweeping mandate while painting the role of the Department of Peacekeeping Operations (DPKO) as merely 'operational', Boutros-Ghali used 'technicization' as a means to strengthen the Secretary-General's office.
Children with lower birth weight are at increased risk of asthma symptoms.
To examine associations of fetal and infant growth with childhood lung function and asthma.
This study was embedded in a ...population-based prospective cohort study of 5,635 children. Growth was estimated by repeated ultrasounds in the second and third trimesters, and measured at birth and at 3, 6, and 12 months. At age 10 years, spirometry was performed and asthma was assessed by parental questionnaire. Restricted and accelerated growth were defined as the growth percentile change between time periods less than -0.67 and more than 0.67 SD scores (SDSs), respectively. We applied multiple regression analyses, including conditional regression analyses, to account for correlations between repeated growth measures.
Overall greater weight in the second and third trimesters, at birth, and at 12 months was associated with higher FEV
and FVC (range of z-score difference, 0.04-0.08, per SDS increase in weight). Greater weight at 3 months was associated with lower FEV
/FVC and forced expiratory flow at 75% of the pulmonary volume (FEF
) (z-score differences 95% confidence interval: -0.09 -0.14 to -0.05 and -0.09 -0.13 to -0.05 per SDS increase in weight, respectively). Restricted fetal weight growth was associated with lower childhood lung-function measures, partly depending on infant weight growth patterns (range of z-score difference, -0.25 to -0.13). Accelerated fetal weight growth was associated with higher FVC and lower FEV
/FVC only if followed by accelerated infant weight growth. Fetal and infant weight growth was not associated with childhood asthma.
Both restricted fetal weight growth, partly depending on infant weight growth, and accelerated fetal and infant weight growth predispose children to lower lung function and a potential risk for respiratory diseases later in life.
Over the last 5 years deep learning has progressed tremendously in both image recognition and natural language processing. Now it is increasingly applied to other data rich fields. In drug discovery, ...recurrent neural networks (RNNs) have been shown to be an effective method to generate novel chemical structures in the form of SMILES. However, ligands generated by current methods have so far provided relatively low diversity and do not fully cover the whole chemical space occupied by known ligands. Here, we propose a new method (DrugEx) to discover de novo drug-like molecules. DrugEx is an RNN model (generator) trained through reinforcement learning which was integrated with a special exploration strategy. As a case study we applied our method to design ligands against the adenosine A
2A
receptor. From ChEMBL data, a machine learning model (predictor) was created to predict whether generated molecules are active or not. Based on this predictor as the reward function, the generator was trained by reinforcement learning without any further data. We then compared the performance of our method with two previously published methods, REINVENT and ORGANIC. We found that candidate molecules our model designed, and predicted to be active, had a larger chemical diversity and better covered the chemical space of known ligands compared to the state-of-the-art.
The timing performance of scintillation detectors is ultimately limited by photon counting statistics. In fact, photon counting statistics form a dominant contribution to the overall timing ...resolution of many state-of-the-art detectors. A common approach to investigate this contribution is to calculate the variance in the registration times of individual scintillation photons within the photosensor. However, in general the single-photon variance is not equal to the intrinsic limit on the timing resolution, since in principle one can make use of the timing information carried by all photons detected. In this work, the Cramér-Rao lower bound on the timing resolution of a scintillation detector, based on the information contained in the full set of registered photons, is calculated. The results appear to be in good agreement with trends observed in the literature. Furthermore, it is shown that the timestamp obtained from any single scintillation photon never yields the optimum timing resolution for realistic scintillation detectors. Yet, it appears that the intrinsic timing resolution limit can be approached closely by making use of the timestamps from a relatively small number of photons emitted during the initial part of the scintillation pulse.
Target deconvolution is a vital initial step in preclinical drug development to determine research focus and strategy. In this respect, computational target prediction is used to identify the most ...probable targets of an orphan ligand or the most similar targets to a protein under investigation. Applications range from the fundamental analysis of the mode-of-action over polypharmacology or adverse effect predictions to drug repositioning. Here, we provide a review on published ligand- and target-based as well as hybrid approaches for computational target prediction, together with current limitations and future directions.
Literacy is a critical skill and is quite a concern in the world of education, especially mathematics education in the 21st century. Literacy in mathematics illustrates how a student identifies and ...understands the problems in which mathematics he has learned plays a role in all aspects of life. On the other hand, the 21st-century digital era demands the realm of education to be able to utilize ICT (Information and communication technologies) in the learning process, not least in mathematics. Digital technology, as a tool that is believed to make a significant contribution to the development of education, is also a challenge in its application, especially concerning the development of mathematical knowledge and skills, mathematical literacy. A question that arises is, can the use of digital technology develop mathematical literacy in the process of learning mathematics? If the answer can, then how should such integration be carried out. This article aims to provide an overview of the answers to these questions by giving an overview of the importance of mathematical literacy and digital technology in developing mathematical literacy.
Hypoxic ischemic brain injury secondary to pediatric cardiac arrest (CA) may result in acute symptomatic seizures. A high proportion of seizures may be nonconvulsive, so accurate diagnosis requires ...continuous EEG monitoring. We aimed to determine the safety and feasibility of long-term EEG monitoring, to describe electroencephalographic background and seizure characteristics, and to identify background features predictive of seizures in children undergoing therapeutic hypothermia (TH) after CA.
Nineteen children underwent TH after CA. Continuous EEG monitoring was performed during hypothermia (24 hours), rewarming (12-24 hours), and then an additional 24 hours of normothermia. The tolerability of these prolonged studies and the EEG background classification and seizure characteristics were described in a standardized manner.
No complications of EEG monitoring were reported or observed. Electrographic seizures occurred in 47% (9/19), and 32% (6/19) developed status epilepticus. Seizures were nonconvulsive in 67% (6/9) and electrographically generalized in 78% (7/9). Seizures commenced during the late hypothermic or rewarming periods (8/9). Factors predictive of electrographic seizures were burst suppression or excessively discontinuous EEG background patterns, interictal epileptiform discharges, or an absence of the expected pharmacologically induced beta activity. Background features evolved over time. Patients with slowing and attenuation tended to improve, whereas those with burst suppression tended to worsen.
EEG monitoring in children undergoing therapeutic hypothermia after cardiac arrest is safe and feasible. Electrographic seizures and status epilepticus are common in this setting but are often not detectable by clinical observation alone. The EEG background often evolves over time, with milder abnormalities improving and more severe abnormalities worsening.
Digital silicon photomultiplier (dSiPM) arrays have favorable characteristics for application in monolithic scintillator detectors for time-of-flight positron emission tomography (PET). To fully ...exploit these benefits, a maximum likelihood interaction time estimation (MLITE) method was developed to derive the time of interaction from the multiple time stamps obtained per scintillation event. MLITE was compared to several deterministic methods. Timing measurements were performed with monolithic scintillator detectors based on novel dSiPM arrays and LSO:Ce,0.2%Ca crystals of 16 × 16 × 10 mm(3), 16 × 16 × 20 mm(3), 24 × 24 × 10 mm(3), and 24 × 24 × 20 mm(3). The best coincidence resolving times (CRTs) for pairs of identical detectors were obtained with MLITE and measured 157 ps, 185 ps, 161 ps, and 184 ps full-width-at-half-maximum (FWHM), respectively. For comparison, a small reference detector, consisting of a 3 × 3 × 5 mm(3) LSO:Ce,0.2%Ca crystal coupled to a single pixel of a dSiPM array, was measured to have a CRT as low as 120 ps FWHM. The results of this work indicate that the influence of the optical transport of the scintillation photons on the timing performance of monolithic scintillator detectors can at least partially be corrected for by utilizing the information contained in the spatio-temporal distribution of the collection of time stamps registered per scintillation event.
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