4-Methyl­morpholinium bromide

The six-membered ring in the title salt, C5H12NO+·Br−, has a chair conformation. In the crystal, the cations are linked to the anions by N—H⋯Br hydrogen bonds

Age as a risk factor for acute mountain sickness upon rapid ascent to 3,700 m among young adult Chinese men.

BackgroundThe aim of this study was to explore the relationship between age and acute mountain sickness (AMS) when subjects are exposed suddenly to high altitude.MethodsA total of 856 young adult men were recruited. Before and after acute altitude exposure, the Athens Insomnia Scale score (AISS) was used to evaluate the subjective sleep quality of subjects. AMS was assessed using the Lake Louise scoring system. Heart rate (HR) and arterial oxygen saturation (SaO2) were measured.ResultsResults showed that, at 500 m, AISS and insomnia prevalence were higher in older individuals. After acute exposure to altitude, the HR, AISS, and insomnia prevalence increased sharply, and the increase in older individuals was more marked. The opposite trend was observed for SaO2. At 3,700 m, the prevalence of AMS increased with age, as did severe AMS, and AMS symptoms (except gastrointestinal symptoms). Multivariate logistic regression analysis showed that age was a risk factor for AMS (adjusted odds ratio [OR] 1.07, 95% confidence interval [CI] 1.01-1.13, P<0.05), as well as AISS (adjusted OR 1.39, 95% CI 1.28-1.51, P<0.001).ConclusionThe present study is the first to demonstrate that older age is an independent risk factor for AMS upon rapid ascent to high altitude among young adult Chinese men, and pre-existing poor subjective sleep quality may be a contributor to increased AMS prevalence in older subjects

PeP: a Point enhanced Painting method for unified point cloud tasks

Point encoder is of vital importance for point cloud recognition. As the very beginning step of whole model pipeline, adding features from diverse sources and providing stronger feature encoding mechanism would provide better input for downstream modules. In our work, we proposed a novel PeP module to tackle above issue. PeP contains two main parts, a refined point painting method and a LM-based point encoder. Experiments results on the nuScenes and KITTI datasets validate the superior performance of our PeP. The advantages leads to strong performance on both semantic segmentation and object detection, in both lidar and multi-modal settings. Notably, our PeP module is model agnostic and plug-and-play. Our code will be publicly available soon

Risk factors for high-altitude headache upon acute high-altitude exposure at 3700 m in young Chinese men: a cohort study.

BackgroundThis prospective and observational study aimed to identify demographic, physiological and psychological risk factors associated with high-altitude headache (HAH) upon acute high-altitude exposure.MethodsEight hundred fifty subjects ascended by plane to 3700 m above Chengdu (500 m) over a period of two hours. Structured Case Report Form (CRF) questionnaires were used to record demographic information, physiological examinations, psychological scale, and symptoms including headache and insomnia a week before ascending and within 24 hours after arrival at 3700 m. Binary logistic regression models were used to analyze the risk factors for HAH.ResultsThe incidence of HAH was 73.3%. Age (p =0.011), physical labor intensity (PLI) (p =0.044), primary headache history (p <0.001), insomnia (p <0.001), arterial oxygen saturation (SaO2) (p =0.001), heart rate (HR) (p =0.002), the Self-Rating Anxiety Scale (SAS) (p <0.001), and the Epworth Sleepiness Scale (ESS) (p <0.001) were significantly different between HAH and non-HAH groups. Logistic regression models identified primary headache history, insomnia, low SaO2, high HR and SAS as independent risk factors for HAH.ConclusionsInsomnia, primary headache history, low SaO2, high HR, and high SAS score are the risk factors for HAH. Our findings will provide novel avenues for the study, prevention and treatment of HAH

Cerebral hemodynamic characteristics of acute mountain sickness upon acute high-altitude exposure at 3,700 m in young Chinese men.

PURPOSE: We aimed at identifying the cerebral hemodynamic characteristics of acute mountain sickness (AMS). METHODS: Transcranial Doppler (TCD) sonography examinations were performed between 18 and 24 h after arrival at 3,700 m via plane from 500 m (n = 454). A subgroup of 151 subjects received TCD examinations at both altitudes. RESULTS: The velocities of the middle cerebral artery, vertebral artery (VA) and basilar artery (BA) increased while the pulsatility indexes (PIs) and resistance indexes (RIs) decreased significantly (all p < 0.05). Velocities of BA were higher in AMS (AMS+) individuals when compared with non-AMS (AMS-) subjects (systolic velocity: 66 ± 12 vs. 69 ± 15 cm/s, diastolic velocity: 29 ± 7 vs. 31 ± 8 cm/s and mean velocity, 42 ± 9 vs. 44 ± 10 cm/s). AMS was characterized by higher diastolic velocity [V d_VA (26 ± 4 vs. 25 ± 4, p = 0.013)] with lower PI and RI (both p = 0.004) in VA. Furthermore, the asymmetry index (AI) of VAs was significantly lower in the AMS + group [-5.7 % (21.0 %) vs. -2.5 % (17.8 %), p = 0.016]. The AMS score was closely correlated with the hemodynamic parameters of BA and the V d_VA, PI, RI and AI of VA. CONCLUSION: AMS is associated with alterations in cerebral hemodynamics in the posterior circulation rather than the anterior one, and is characterized by higher blood velocity with lower resistance. In addition, the asymmetry of VAs may be involved in AMS

Uni-QSAR: an Auto-ML Tool for Molecular Property Prediction

Recently deep learning based quantitative structure-activity relationship (QSAR) models has shown surpassing performance than traditional methods for property prediction tasks in drug discovery. However, most DL based QSAR models are restricted to limited labeled data to achieve better performance, and also are sensitive to model scale and hyper-parameters. In this paper, we propose Uni-QSAR, a powerful Auto-ML tool for molecule property prediction tasks. Uni-QSAR combines molecular representation learning (MRL) of 1D sequential tokens, 2D topology graphs, and 3D conformers with pretraining models to leverage rich representation from large-scale unlabeled data. Without any manual fine-tuning or model selection, Uni-QSAR outperforms SOTA in 21/22 tasks of the Therapeutic Data Commons (TDC) benchmark under designed parallel workflow, with an average performance improvement of 6.09\%. Furthermore, we demonstrate the practical usefulness of Uni-QSAR in drug discovery domains

REMAS: a new regression model to identify alternative splicing events from exon array data

<p>Abstract</p> <p>Background</p> <p>Alternative splicing (AS) is an important regulatory mechanism for gene expression and protein diversity in eukaryotes. Previous studies have demonstrated that it can be causative for, or specific to splicing-related diseases. Understanding the regulation of AS will be helpful for diagnostic efforts and drug discoveries on those splicing-related diseases. As a novel exon-centric microarray platform, exon array enables a comprehensive analysis of AS by investigating the expression of known and predicted exons. Identifying of AS events from exon array has raised much attention, however, new and powerful algorithms for exon array data analysis are still absent till now.</p> <p>Results</p> <p>Here, we considered identifying of AS events in the framework of variable selection and developed a regression method for AS detection (REMAS). Firstly, features of alternatively spliced exons were scaled by reasonably defined variables. Secondly, we designed a hierarchical model which can represent gene structure and transcriptional influence to exons, and the lasso type penalties were introduced in calculation because of huge variable size. Thirdly, an iterative two-step algorithm was developed to select alternatively spliced genes and exons. To avoid negative effects introduced by small sample size, we ranked genes as parameters indicating their AS capabilities in an iterative manner. After that, both simulation and real data evaluation showed that REMAS could efficiently identify potential AS events, some of which had been validated by RT-PCR or supported by literature evidence.</p> <p>Conclusion</p> <p>As a new lasso regression algorithm based on hierarchical model, REMAS has been demonstrated as a reliable and effective method to identify AS events from exon array data.</p