Hausertownsend6879
Results with large-scale scRNA-seq data indicate that D-TSEE can uncover oscillatory gene expression patterns by using experimentally temporal information.
D-EE is a distributed dimensionality reduction and visualization tool. Its distributed storage and distributed computation technique allow us to efficiently analyze large-scale single-cell data at the cost of constant time speedup. The source code for D-EE algorithm based on C and MPI tailored to a high-performance computing cluster is available at https//github.com/ShaokunAn/D-EE.
D-EE is a distributed dimensionality reduction and visualization tool. Its distributed storage and distributed computation technique allow us to efficiently analyze large-scale single-cell data at the cost of constant time speedup. The source code for D-EE algorithm based on C and MPI tailored to a high-performance computing cluster is available at https//github.com/ShaokunAn/D-EE.
The increasing production of genomic data has led to an intensified need for models that can cope efficiently with the lossless compression of DNA sequences. Important applications include long-term storage and compression-based data analysis. In the literature, only a few recent articles propose the use of neural networks for DNA sequence compression. However, they fall short when compared with specific DNA compression tools, such as GeCo2. This limitation is due to the absence of models specifically designed for DNA sequences. In this work, we combine the power of neural networks with specific DNA models. For this purpose, we created GeCo3, a new genomic sequence compressor that uses neural networks for mixing multiple context and substitution-tolerant context models.
We benchmark GeCo3 as a reference-free DNA compressor in 5 datasets, including a balanced and comprehensive dataset of DNA sequences, the Y-chromosome and human mitogenome, 2 compilations of archaeal and virus genomes, 4 whole genomes, and easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https//github.com/cobilab/geco3.
GeCo3 is a genomic sequence compressor with a neural network mixing approach that provides additional gains over top specific genomic compressors. The proposed mixing method is portable, requiring only the probabilities of the models as inputs, providing easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https//github.com/cobilab/geco3.Singapore's hospitals had prepared operations to receive patients (potentially) infected with SARS-CoV-2, planning various scenarios and levels of surge with a policy of isolating all confirmed cases as inpatients. The National University Hospital, adopted a whole of hospital approach to COVID-19 with three primary goals zero hospital-acquired COVID-19, all patients receive timely necessary care, and maintenance of staff morale. These goals to date have been met. A large influx of COVID-19 cases emerged requiring a significant transformation of clinical and operational processes. Isolation room numbers almost tripled and dedicated COVID-19 cohort wards were established, elective care was postponed and Intensive Care Units were augmented with equipment and manpower. In the wake of the surge establishing a new normal for hospital care requires a considered balance of maintaining vigilance to detect endemic COVID-19, establishing contingency plans to ramp up in case of another surge, while returning to business as usual.
The aim of this study was to investigate the effects of alcohol hangover on emotion regulation.
Forty-five non-smoking, healthy participants aged between 18 and 30years completed a lab-based emotion regulation task assessing cognitive reappraisal and an emotion regulation questionnaire (State-Difficulties in Emotion Regulation Scale [S-DERS]) when hungover (morning following a night of heavy drinking) and under a no-hangover condition in a naturalistic, within-subjects design study.
Participants reported poorer emotion regulation overall (P<0.001, d=0.75), and for the subscales 'Non-Acceptance', 'Modulation' and 'Clarity' (Ps≤0.001, ds≥0.62), but not 'Awareness' on the S-DERS, in the hangover versus the no-hangover condition. Hangover did not impair emotion regulation ability as assessed using the lab-based task (Ps≥0.21, ds≤0.40), but there was a general negative shift in valence ratings (i.e. all images were rated more negatively) in the hangover relative to the no-hangover condition (P<0.001, d=1.16).
These results suggest that emotion regulation in everyday life and emotional reactivity may be adversely affected by alcohol hangover, but some emotion regulation strategies (e.g. deliberate cognitive reappraisal) may be unaffected.
These results suggest that emotion regulation in everyday life and emotional reactivity may be adversely affected by alcohol hangover, but some emotion regulation strategies (e.g. deliberate cognitive reappraisal) may be unaffected.Focal epilepsy in adults is associated with progressive atrophy of the cortex at a rate more than double that of normal ageing. We aimed to determine whether successful epilepsy surgery interrupts progressive cortical thinning. In this longitudinal case-control neuroimaging study, we included subjects with unilateral temporal lobe epilepsy (TLE) before (n = 29) or after (n = 56) anterior temporal lobe resection and healthy volunteers (n = 124) comparable regarding age and sex. We measured cortical thickness on paired structural MRI scans in all participants and compared progressive thinning between groups using linear mixed effects models. Compared to ageing-related cortical thinning in healthy subjects, we found progressive cortical atrophy on vertex-wise analysis in TLE before surgery that was bilateral and localized beyond the ipsilateral temporal lobe. STS inhibitor In these regions, we observed accelerated annualized thinning in left (left TLE 0.0192 ± 0.0014 versus healthy volunteers 0.0032 ± 0.0013 mm/year, P less then 0.
