PlantRep: a database of plant repetitive elements

Key message We re-annotated repeats of 459 plant genomes and released a new database: PlantRep (http://www.plantrep.cn/). PlantRep sheds lights of repeat evolution and provides fundamental data for deep exploration of genome.

Deep Learning and Device-Assisted Enteroscopy: Automatic Detection of Gastrointestinal Angioectasia

Background and Objectives: Device-assisted enteroscopy (DAE) allows deep exploration of the small bowel and combines diagnostic and therapeutic capacities. Suspected mid-gastrointestinal bleeding is the most frequent indication for DAE, and vascular lesions, particularly angioectasia, are the most common etiology. Nevertheless, the diagnostic yield of DAE for the detection of these lesions is suboptimal. Deep learning algorithms have shown great potential for automatic detection of lesions in endoscopy. We aimed to develop an artificial intelligence (AI) model for the automatic detection of angioectasia DAE images. Materials and Methods: A convolutional neural network (CNN) was developed using DAE images. Each frame was labeled as normal/mucosa or angioectasia. The image dataset was split for the constitution of training and validation datasets. The latter was used for assessing the performance of the CNN. Results: A total of 72 DAE exams were included, and 6740 images were extracted (5345 of normal mucosa and 1395 of angioectasia). The model had a sensitivity of 88.5%, a specificity of 97.1% and an AUC of 0.988. The image processing speed was 6.4 ms/frame. Conclusions: The application of AI to DAE may have a significant impact on the management of patients with suspected mid-gastrointestinal bleeding.

Deep Exploration of the Planets HR 8799 b, c, and d with Moderate-resolution Spectroscopy

The four directly imaged planets orbiting the star HR 8799 are an ideal laboratory to probe atmospheric physics and formation models. We present more than a decade’s worth of Keck/OSIRIS observations of these planets, which represent the most detailed look at their atmospheres to date by its resolution and signal-to-noise ratio. We present the first direct detection of HR 8799 d, the second-closest known planet to the star, at moderate spectral resolution with Keck/OSIRIS (K band; R ≈ 4000). Additionally, we uniformly analyze new and archival OSIRIS data (H and K band) of HR 8799 b, c, and d. First, we show detections of water (H2O) and carbon monoxide (CO) in the three planets and discuss the ambiguous case of methane (CH4) in the atmosphere of HR 8799 b. Then, we report radial-velocity (RV) measurements for each of the three planets. The RV measurement of HR 8799 d is consistent with predictions made assuming coplanarity and orbital stability of the HR 8799 planetary system. Finally, we perform a uniform atmospheric analysis on the OSIRIS data, published photometric points, and low-resolution spectra. We do not infer any significant deviation from the stellar value of the carbon-to-oxygen ratio (C/O) of the three planets, which therefore does not yet yield definitive information about the location or method of formation. However, constraining the C/O for all the HR 8799 planets is a milestone for any multiplanet system, and particularly important for large, widely separated gas giants with uncertain formation processes.

PlantRep: a resource of plant repeats

We re-annotated repeats of 459 plant genomes and released a new datatabase: PlantRep (http://www.plantrep.cn/). PlantRep sheds lights of repeat evolution and provides fundamental data for deep exploration of genome.

Writing for Wikipedia: An Exercise in Microbiology, Writing, Research, Communication, and Public Service

The COVID-19 pandemic has had a tremendous impact on how postsecondary education was and is delivered. Educators were forced to rapidly move their instruction online and find new and innovative ways to convey content, stimulate student engagement, and satisfy curricular requirements. The purpose of this article is to describe the use of a Wikipedia writing assignment in Veterinary Bacteriology and Mycology, a second-year course in the Doctor of Veterinary Medicine (DVM) curriculum at the University of Saskatchewan. Students had the opportunity to write and edit incomplete articles on topics related to course content. In addition to deep exploration of a topic, this fostered the development of research and communication skills, which have been articulated as core competencies in veterinary programs.

Memory comes from the forgotten: analyzing photographic albums created by Canadian military personnel from the first World War

This thesis evaluates four photographic albums created by Canadian military personnel who served in the First World War from 1914-1918, housed at the Canadian War Museum in Ottawa, Ontario, Canada. The albums depict the personnel’s time spent in overseas service during the First World War and reflect their personal representations of the conflict. The evaluation of these photographic albums supports the argument that stronger historical context, and in turn a stronger collective memory of the event, can be developed by deep exploration of how active Canadian military personnel of the war chose to remember the event through the subject matter depicted within their albums.

Memory comes from the forgotten: analyzing photographic albums created by Canadian military personnel from the first World War

This thesis evaluates four photographic albums created by Canadian military personnel who served in the First World War from 1914-1918, housed at the Canadian War Museum in Ottawa, Ontario, Canada. The albums depict the personnel’s time spent in overseas service during the First World War and reflect their personal representations of the conflict. The evaluation of these photographic albums supports the argument that stronger historical context, and in turn a stronger collective memory of the event, can be developed by deep exploration of how active Canadian military personnel of the war chose to remember the event through the subject matter depicted within their albums.

Comparative Analysis for the Performance of Long-Read-Based Structural Variation Detection Pipelines in Tandem Repeat Regions

There has been growing recognition of the vital links between structural variations (SVs) and diverse diseases. Research suggests that, with much longer DNA fragments and abundant contextual information, long-read technologies have advantages in SV detection even in complex repetitive regions. So far, several pipelines for calling SVs from long-read sequencing data have been proposed and used in human genome research. However, the performance of these pipelines is still lack of deep exploration and adequate comparison. In this study, we comprehensively evaluated the performance of three commonly used long-read SV detection pipelines, namely PBSV, Sniffles and PBHoney, especially the performance on detecting the SVs in tandem repeat regions (TRRs). Evaluated by using a robust benchmark for germline SV detection as the gold standard, we thoroughly estimated the precision, recall and F1 score of insertions and deletions detected by the pipelines. Our results revealed that all these pipelines clearly exhibited better performance outside TRRs than that in TRRs. The F1 scores of Sniffles in and outside TRRs were 0.60 and 0.76, respectively. The performance of PBSV was similar to that of Sniffles, and was generally higher than that of PBHoney. In conclusion, our findings can be benefit for choosing the appropriate pipelines in real practice and are good complementary to the application of long-read sequencing technologies in the research of rare diseases.