Mccurdysteen9898

Local excision (LE) after chemoradiotherapy is a new option in low rectal cancer, but morbidity has never been compared prospectively with total mesorectal excision (TME). Early and late morbidity were compared in patients treated either by LE or TME after neoadjuvant chemoradiotherapy for rectal cancer.

This was a post-hoc analysis from a randomized trial. Patients with clinical T2/T3 low rectal cancer with good response to the chemoradiotherapy and having either LE, LE with eventual completion TME, or TME were considered. Early (1 month) and late (2 years) morbidities were compared between the three groups.

There were no deaths following surgery in any of the three groups. Early surgical morbidity (20 per cent LE versus 36 per cent TME versus 43 per cent completion TME, P = 0.025) and late surgical morbidity (4 per cent versus 33 per cent versus 57 per cent, P < 0.001) were significantly lower in the LE group than in the TME or the completion TME group. of LE, was associated with the lowest rate ofte responders.Transcriptomic and epigenetic alterations during early embryo development have been proven to play essential roles in regulating the cell fate. Nowadays, advances in single-cell transcriptomics and epigenomics profiling techniques provide large volumes of data for understanding the molecular regulatory mechanisms in early embryos and facilitate the investigation of assisted reproductive technology as well as preimplantation genetic testing. However, the lack of integrated data collection and unified analytic procedures greatly limits their usage in scientific research and clinical application. Hence, it is necessary to establish a database integrating the regulatory information of human and mouse early embryos with unified analytic procedures. Here, we introduce DevOmics (http//devomics.cn/), which contains normalized gene expression, DNA methylation, histone modifications (H3K4me3, H3K9me3, H3K27me3, H3K27ac), chromatin accessibility and 3D chromatin architecture profiles of human and mouse early embryos spanning six developmental stages (zygote, 2cell, 4cell, 8cell, morula and blastocyst (ICM, TE)). The current version of DevOmics provides Search and Advanced Search for retrieving genes a researcher is interested in, Analysis Tools including the differentially expressed genes (DEGs) analysis for acquiring DEGs between different types of samples, allelic explorer for displaying allele-specific gene expression as well as epigenetic modifications and correlation analysis for showing the dynamic changes in different layers of data across developmental stages, as well as Genome Browser and Ortholog for visualization. DevOmics offers a user-friendly website for biologists and clinicians to decipher molecular regulatory mechanisms of human and mouse early embryos.Coronavirus disease 2019 pandemic is the most damaging pandemic in recent human history. Rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and variant strains is paramount for recovery from this pandemic. Conventional SARS-CoV-2 tests interrogate only limited regions of the whole SARS-CoV-2 genome, which are subjected to low specificity and miss the opportunity of detecting variant strains. In this work, we developed the first SARS-CoV-2 tiling array that captures the entire SARS-CoV-2 genome at single nucleotide resolution and offers the opportunity to detect point mutations. A thorough bioinformatics protocol of two base calling methods has been developed to accompany this array. To demonstrate the effectiveness of the tiling array, we genotyped all genomic positions of eight SARS-CoV-2 samples. Using high-throughput sequencing as the benchmark, we show that the tiling array had a genome-wide accuracy of at least 99.5%. From the tiling array analysis results, we identified the D614G mutation in the spike protein in four of the eight samples, suggesting the widespread distribution of this variant at the early stage of the outbreak in the United States. Two additional nonsynonymous mutations were identified in one sample in the nucleocapsid protein (P13L and S197L), which may complicate future vaccine development. With around $5 per array, supreme accuracy, and an ultrafast bioinformatics protocol, the SARS-CoV-2 tiling array makes an invaluable toolkit for combating current and future pandemics. Our SARS-CoV-2 tilting array is currently utilized by Molecular Vision, a CLIA-certified lab for SARS-CoV-2 diagnosis.

frail older adults may be more vulnerable to stressors, resulting in steeper declines in cognitive function. Whether the frailty-cognition link differs by cognitive domain remains unclear; however, it could lend insight into underlying mechanisms.

we tested whether domain-specific cognitive trajectories (clock-drawing test, (CDT), immediate and delayed recall, orientation to date, time, president and vice-president naming) measured annually (2011-2016) differ by baseline frailty (physical frailty phenotype) in the National Health and Aging Trends Study (n = 7,439), a nationally representative sample of older adult U.S. Medicare beneficiaries, using mixed effects models to describe repeated measures of each cognitive outcome. To determine if the association between frailty and subsequent cognitive change differed by education, we tested for interaction using the Wald test.

we observed steeper declines for frail compared to non-frail participants in each domain-specific outcome, except for immediate recalassociations for executive function. These findings suggest that aetiologies are multifactorial, though primarily vascular related; further research into its association with dementia sub-types and related pathologies is critical.

To test the validity of the Outcome Measure in Rheumatology (OMERACT) semiquantitative score by comparing with a quantitative method in the sonographic (US) assessment of hyaline cartilage at the metacarpal head (MH) in patients with rheumatoid arthritis (RA) and healthy subjects (HS).

The hyaline cartilage from second to fifth MHs of both hands was scanned. Hyaline cartilage was scored semiquantitatively and quantitatively (by measuring cartilage thickness and comparing with reference values). In RA patients, radiographic joint space narrowing (JSN) was scored on the same joints using the Simple Erosion Narrowing Score (SENS).

Four-hundred and eight MHs in 51 RA patients and 320 MHs in 40 HS were evaluated. The OMERACT semiquantitative score was quicker to perform than the quantitative method (6.0 ± 0.5 vs 8.0 ± 1.5 min, p< 0.01). A significant correlation between the US scores (R = 0.68), and between the US scores and the JSN-SENS (R = 0.61 and R = 0.63, for semiquantitative and quantitative method evaluation of cartilage damage in selected cases.

To investigate sacroiliac joint(SIJ) MRI inflammation, structural and degenerative lesion characteristics in patients with axial spondyloarthritis(axSpA) and various control groups.

Patients with axSpA(n = 41) and lumbar disc herniation(n = 25), women with(n = 46) and without(n = 14) post-partum(childbirth within 4-16 months) buttock/pelvic pain, cleaning assistants(n = 26), long-distance runners(n = 23) and healthy men(n = 29) had MRI of the SIJs prospectively performed. MRI lesions were assessed on 9 slices covering the cartilaginous compartment by two experienced readers according to the definitions of the Spondyloarthritis Research Consortium of Canada(SPARCC) SIJ inflammation and structural scores, and were evaluated according to depth and extent. Other morphological characteristics were also analysed.

Total depth scores for bone marrow oedema(BME) and fat lesion(FAT) and total extent score for erosion were statistically significantly highest in axSpA, while scores for sclerosis were numerically highest in women with post-partum pain. Maximum BME depth > 10mm was frequently and exclusively found in axSpA and post-partum women(39% vs 14-17%) while FAT depth > 5mm was predominantly found in axSpA(76% vs 0-10%). Erosions were primarily seen in axSpA, especially when extensive(≥4 or confluent; 17% vs 0%). Capsulitis was absent in non-axSpA groups. Epigenetic inhibitor nmr BME and FAT in the ligamentous compartment were primarily found in axSpA(17/22% vs 0/2% in non-axSpA groups). In non-axSpA, osteophytes(axSpA vs non-axSpA 0% vs 3-17%) and vacuum phenomenon(7% vs 30-66%) were more frequent, and the joint space was wider(mean(SD) 1.5(0.9)mm vs 2.2(0.5)mm).

FAT depth > 5mm, but not BME depth > 10mm, could almost differentiate axSpA patients from all other groups. When excluding post-partum women, BME >5mm and erosion were highly specific for axSpA.

5mm and erosion were highly specific for axSpA.

Increasingly comprehensive characterisation of cancer-associated genetic alterations has paved the way for the development of highly specific therapeutic vaccines. Predicting precisely the binding and presentation of peptides to MHC alleles is an important step towards such therapies. Recent data suggest that presentation of both class I and II epitopes are critical for the induction of a sustained effective immune response. However, the prediction performance for MHC class II has been limited compared to class I.

We present a transformer neural network model which leverages self-supervised pretraining from a large corpus of protein sequences. We also propose a multiple instance learning (MIL) framework to deconvolve mass spectrometry data where multiple potential MHC alleles may have presented each peptide. We show that pretraining boosted the performance for these tasks. Combining pretraining and the novel MIL approach, our model outperforms state-of-the-art models based on peptide and MHC sequence only for both binding and cell surface presentation predictions.

Our source code is available at https//github.com/s6juncheng/BERTMHC under a non-commercial license. A webserver is available at https//bertmhc.privacy.nlehd.de/.

Our source code is available at https//github.com/s6juncheng/BERTMHC under a non-commercial license. A webserver is available at https//bertmhc.privacy.nlehd.de/.

Clustering is a key step in revealing heterogeneities in single-cell data. Most existing single-cell clustering methods output a fixed number of clusters without the hierarchical information. Classical hierarchical clustering provides dendrograms of cells, but cannot scale to large datasets due to high computational complexity. We present HGC, a fast Hierarchical Graph-based Clustering tool to address both problems. It combines the advantages of graph-based clustering and hierarchical clustering. On the shared nearest-neighbor graph of cells, HGC constructs the hierarchical tree with linear time complexity. Experiments showed that HGC enables multiresolution exploration of the biological hierarchy underlying the data, achieves state-of-the-art accuracy on benchmark data, and can scale to large datasets.

The R package of HGC is available at https//bioconductor.org/packages/HGC/.

Supplementary data are available at Bioinformatics online.

Supplementary data are available at Bioinformatics online.