Background: In meningiomas, CDKN2A/B deletions are associated with poor outcomes but are rare in most cohorts (1-5%). Large molecular datasets are therefore required to explore these deletions and their relationship to other prognostic CDKN2A alterations. Methods: We utilized multidimensional molecular data of 560 meningiomas from 5 independent cohorts to comprehensively interrogate the spectrum of CDKN2A alterations through DNA methylation, copy number variation, transcriptomics, and proteomics using an integrated molecular approach. Results: Meningiomas with either CDKN2A/B deletions (partial or homozygous loss) or an intact CDKN2A gene locus but elevated mRNA expression (CDKN2Ahigh) both had poor clinical outcomes. Increased CDKN2A mRNA expression was a poor prognostic factor independent of CDKN2A deletion. CDKN2A expression and p16 protein increased with tumor grade and more aggressive molecular and methylation groups. CDKN2Ahigh meningiomas and meningiomas with CDKN2A deletions were enriched for similar cell cycling pathways dysregulated at different checkpoints. p16 immunohistochemistry was unreliable in differentiating between meningiomas with and without CDKN2A deletions, but increased positivity was associated with increased mRNA expression. CDKN2Ahigh meningiomas were associated with gene hypermethylation, Rb-deficiency, and lack of response to CDK inhibition. Conclusions: These findings support the role of CDKN2A mRNA expression as a biomarker of clinically aggressive meningiomas with potential therapeutic implications.

Influenza virus infections can lead to a number of secondary complications, including sepsis. We applied linear regression models to mortality and hospital admission data coded for septicaemia from 1998 to 2019 in Hong Kong, and estimated that septicaemia was associated with an annual average excess mortality rate of 0.23 (95% CI 0.04–0.40) per 100 000 persons per year and an excess septicaemia hospitalisation rate of 1.73 (95% CI 0.94–2.50) per 100 000 persons per year. The highest excess morbidity and mortality was found in older adults and young children, and during influenza A(H3N2) epidemics.

Stratospheric airships are lighter-than-air vehicles that work at an altitude of 20km in the lower calm portion of the stratosphere. They can be used as real-time surveillance platforms for environment monitoring and civil communication. Solar energy is the ideal power choice for long-endurance stratospheric airships. Attitude control is important for airships so that they can point at a target for observation or adjust the attitude to improve the output performance of solar panels. Stratospheric airships have a large volume and semi-flexible structure. The typical actuators used are aerodynamic surfaces, vectored thrust and ballonets. However, not all these actuators can work well under special working conditions, such as low density and low speed. In this study, moving-mass control is introduced to stratospheric airships because its control efficiency is independent of airspeed and atmospheric density. A nonlinear feedback controller based on generalised inverse with a nonlinear mapping module is designed to implement moving-mass control. Such a new station keeping scheme with moving masses is proposed for airships with different working situations.

Manure is a primary source of methane (CH4) emissions into the atmosphere. A large proportion of CH4 from manure is emitted during storage, but this varies with storage methods. In this research, we tested whether covering a manure heap with plastic reduces CH4 emission during a short-term composting process. A static chamber method was used to detect the CH4 emission rate and the change of the physicochemical properties of cattle manure which was stored either uncovered (treatment UNCOVERED) or covered with plastic (treatment COVERED) for 30-day periods during the four seasons? The dry matter content of the COVERED treatment was significantly less than the UNCOVERED treatment (P < 0.01), and the C/N ratio of the COVERED treatment significantly greater than the UNCOVERED treatment (P > 0.05) under high temperature. In the UNCOVERED treatment, average daily methane (CH4) emissions were in the order summer > spring > autumn > winter. CH4 emissions were positively correlated with the temperature (R2 = 0.52, P < 0.01). Compared to the UNCOVERED treatment, the daily average CH4 emission rates from COVERED treatment manure were less in the first 19 days of spring, 13 days of summer, 10 days of autumn and 30 days of winter. In summary, covering the manure pile with plastic reduces the evaporation of water during storage; and in winter, long-term covering with plastic film reduces the CH4 emissions during the storage of manure.

Glutamine synthetase (GS) and glutamate synthase (GOGAT) play a central role in plant nitrogen (N) metabolism. In order to study the effect of powdery mildew (Blumeria graminis f. sp. tritici, Bgt) on N metabolism, field experiments were carried out to evaluate GS and GOGAT activity, GS expression and grain protein content (GPC) in susceptible (Xi'nong 979) and resistant (Zhengmai 103) wheat cultivars under three treatments. The three treatments were no inoculation (CK), inoculated once with Bgt (MP) and inoculated nine times with Bgt (HP). For Xi'nong 979, the activities of GS and GOGAT in grains as well as GS activity in flag leaves increased at 10–15 days after anthesis (DAA), and decreased significantly at 15 or 20–30 DAA in HP and MP. However, GS activity in grains decreased from 20 DAA, which was later than that of flag leaves (15 DAA). At the same time, GS expression in grains was up-regulated at early stage, with GS1 at 10 DAA and GS2 at 15 DAA, followed by a continuous down-regulation. This result indicated that GS and GOGAT activity as well as GS expression were inhibited by powdery mildew, indicating that N metabolism in grains was inhibited at 20–30 DAA. The current study also found out that the yield of the susceptible cultivar decreased significantly, while its GPC increased obviously in HP. It was shown that the increase of GPC was not due to the enhancement of N metabolism, but due to the passive increase caused by yield reduction.

ABSTRACT IMPACT: Screening the effect of thousands of non-coding genetic variants will help identify variants important in the etiology of diseases OBJECTIVES/GOALS: Massively parallel reporter assays (MPRAs) can experimentally evaluate the impact of genetic variants on gene expression. In this study, our objective was to systematically evaluate the functional activity of 3’-UTR SNPs associated with neurological disorders and use those results to help understand their contributions to disease etiology. METHODS/STUDY POPULATION: To choose variants to evaluate with the MPRA, we first gathered SNPs from the GWAS Catalog that were associated with any neurological disorder trait with p-value < 10-5. For each SNP, we identified the region that was in linkage disequilibrium (r2 > 0.8) and retrieved all the common 3’-UTR SNPs (allele-frequency > 0.05) within that region. We used an MPRA to measure the impact of these 3’-UTR variants in SH-SY5Y neuroblastoma cells and a microglial cell line. These results were then used to train a deep-learning model to predict the impact of variants and identify features that contribute to the predictions. RESULTS/ANTICIPATED RESULTS: Of the 13,515 3’-UTR SNPs tested, 400 and 657 significantly impacted gene expression in SH-SY5Y and microglia, respectively. Of the 84 SNPs significantly impacted in both cells, the direction of impact was the same in 81. The direction of eQTL in GTEx tissues agreed with the assay SNP effect in SH-SY5Y cells but not microglial cells. The deep-learning model predicted sequence activity level correlated with the experimental activity level (Spearman’s corr = 0.45). The deep-learning model identified several predictive motifs similar to motifs of RNA-binding proteins. DISCUSSION/SIGNIFICANCE OF FINDINGS: This study demonstrates that MPRAs can be used to evaluate the effect of non-coding variants, and the results can be used to train a machine learning model and interpret its predictions. Together, these can help identify causal variants and further understand the etiology of diseases.

ABSTRACT IMPACT: Glucocorticoid steroids are commonly used despite known dose-dependent cardiovascular toxicity, yet little is known about a) how patients with other cardiovascular risk factors use glucocorticoids, and b) how risks of glucocorticoid treatment might vary depending on a patient’s baseline cardiovascular risk. OBJECTIVES/GOALS: Up to one-third of RA patients use long-term glucocorticoids (GCs) despite a known, dose-dependent association with increased risk of major adverse cardiovascular events (MACE). We aim to evaluate patterns of GC use among RA patients with other MACE risk factors (i.e. diabetes, smoking), and examine how GC use may potentiate these risk factors. METHODS/STUDY POPULATION: We used claims data from Veterans Health Administration to identify 6,090 RA patients with ≥1 rheumatology clinic visit during 2013-2017. We used logistic regression to evaluate associations between incident MACE between 2013-2018, recent long-term GC use, and 5 MACE risk factors: hypertension, diabetes, hyperlipidemia, smoking, and prior MACE. We included two-way interaction terms between GC use and each risk factor. We used a claims-based algorithm to define MACE as any of acute MI, ischemic stroke, TIA, sudden death, or coronary revascularization, between index date and 12/31/2018. We defined index date as first rheumatology visit after meeting RA diagnostic criteria, and recent long-term GC use as ≥90 days’ supply dispensed over 2 years prior to index date. RESULTS/ANTICIPATED RESULTS: Among 2,884 eligible patients,1,553 (54%) had MACE risk factors, and 97 (3%) had prior MACE (Table 1). Overall, 16% of patients recently used long-term GC, compared to 17% of patients with MACE risk factors, and 22% of patients with prior MACE. Incident MACE occurred in 308 (11%) patients, 24% of whom had recent long-term GC use. Recent long-term GC use was independently associated with increased incident MACE (Table 2). While no interaction term was statistically significant overall, differences in odds of incident MACE were seen across levels of recent GC use for several risk factors, particularly diabetes (OR 2.10, 95% CI [0.93-4.77]), tobacco use (OR 2.88, 95% CI [1.16-7.14]) and prior MACE (OR 2.41, 95% CI [0.73-7.95]). DISCUSSION/SIGNIFICANCE OF FINDINGS: Long-term GC use is common among RA patients with MACE risk factors. In this cohort, 25% of patients with incident MACE had recently used long-term GC. Long-term GC use may potentiate effects of comorbidities like diabetes and smoking, disproportionately increasing MACE risk in certain patients.

Dry wind-tunnel (DWT) flutter test systems model the unsteady distributed aerodynamic force using various electromagnetic exciters. They can be used to test the aeroelastic and aeroservoelastic stability of smart aircraft or high-speed flight vehicles. A new parameterised modelling method at the full system level based on the generalised force equivalence for DWT flutter systems is proposed herein. The full system model includes the structural dynamic model, electromechanical coupling model and fast aerodynamic computation model. An optimisation search method is applied to determine the best locations for measurement and excitation by introducing Fisher’s information matrix. The feasibility and accuracy of the proposed system-level numerical DWT modelling method have been validated for a plate aeroelastic model with four exciters/transducers. The effects of key parameters including the number of exciters, the control time delay, the noise interference and the electrical parameters of the electromagnetic exciter model have also been investigated. The numerical and experimental results indicate that the proposed modelling method achieves good accuracy (with deviations of less than 1.5% from simulations and 4.5% from experimental test results for the flutter speed) and robust performance even in uncertain environments with a 10% noise level.

Research on flight emissions at airports is very important for environmental policymaking. This study analysed the trend of aircraft air pollutant emissions at mainland China airports from 1990 to 2017, mainly focusing on standard landing and take-off (LTO) cycles. Total flight movements increased 29-fold from 1990 to 2017 at Chinese airports. Over the same period, the emissions of NOx, SOx, CO, hydrocarbons (HC), and particulate matter (PM) increased 46, 27, 12, 5, and 4 times, respectively. Emissions at the 216 public airports showed a growth trend. It was estimated that in 2017, Chinese airports emitted 12,875 kilotons of CO2, 59 kilotons of NOx, 3 kilotons of SOx, 38 kilotons of CO, 5 kilotons of HC, and 0.4 kilotons of PM. The largest 30 airports produced 68.2% of the total emissions. Emissions from B737-800, A320, A321, B737-700, A330-300, and A319 aircraft accounted for more than 75% of aircraft LTO emissions at Chinese airports in 2017. Results show that average emissions per passenger have decreased for CO2, CO, HC, SOx, PM, and NOx from 1990 to 2017.