Additional file 2 of Mut2Vec: distributed representation of cancerous mutations

It contains the most enriched clusters with IntOGen driver mutations obtained by six clustering methods(K-Means, Agglomerative hierarchical clustering, BIRCH, Spectral clustering, Affinity Propagation, and Gaussian Mixture) and five options of the number of clusters(50, 100, 200, 300 and 500); except Affinity Propagation. (PDF 108 kb

Additional file 1 of Mut2Vec: distributed representation of cancerous mutations

It contains the visualization results with mutation vectors trained with an autoencoder and a denoising autoencoder. (PDF 427 kb

Added Value of Structured Reporting for US of the Pediatric Appendix: Additional CT Examinations and Negative Appendectomy

Purpose This study aimed to determine the incremental value of using a structured report (SR) for US examinations of the pediatric appendix. Materials and Methods Between January 2009 and June 2016, 1150 pediatric patients with suspected appendicitis who underwent US examinations of the appendix were included retrospectively. In November 2012, we developed a five-point scale SR for appendix US examinations. The patients were divided into two groups according to the form of the US report: free-text or SR. The primary clinical outcomes were compared between the two groups, including the rate of CT imaging following US examinations, the negative appendectomy rate (NAR), and the appendiceal perforation rate (PR). Results In total, 550 patients were included in the free-text group and 600 patients in the SR group. The rate of additional CT examinations decreased by 5.3% in the SR group (8.2%, p = 0.003), and the NAR decreased by 8.4% in the SR group (7.8%, p = 0.028). There was no statistical difference in the appendiceal PR (37.6% vs. 48.0%, p = 0.078). Conclusion The use of an SR to evaluate US examinations for suspected pediatric appendicitis results in lower CT use and fewer negative appendectomies without an increase in appendiceal PR

WALDIO: Eliminating the Filesystem Journaling in Resolving the Journaling of Journal Anomaly

This work is dedicated to resolve the Journaling of Journal Anomaly in Android IO stack.We orchestrate SQLite and EXT4 filesystem so that SQLite???s file-backed journaling activity can dispense with the expensive filesystem intervention, the journaling, without compromising the file integrity under unexpected filesystem failure. In storing the logs, we exploit the direct IO to suppress the filesystem interference. This work consists of three key ingredients: (i) Preallocation with Explicit Journaling, (ii) Header Embedding, and (iii) Group Synchronization. Preallocation with Explicit Journaling eliminates the filesystem journaling properly protecting the file metadata against the unexpected system crash. We redesign the SQLite B-tree structure with Header Embedding to make it direct IO compatible and block IO friendly. With Group Synch, we minimize the synchronization overhead of direct IO and make the SQLite operation NAND Flash friendly. Combining the three technical ingredients, we develop a new journal mode in SQLite, the WALDIO. We implement it on the commercially available smartphone. WALDIO mode achieves 5.1x performance (insert/sec) against WAL mode which is the fastest journaling mode in SQLite. It yields 2.7x performance (inserts/ sec) against the LS-MVBT, the fastest SQLite journaling mode known to public. WALDIO mode achieves 7.4x performance (insert/sec) against WAL mode when it is relieved from the overhead of explicitly synchronizing individual log-commit operations. WALDIO mode reduces the IO volume to 1/6 compared against the WAL mode

Development of an assessment method for freely moving nonhuman primates’ eating behavior using manual and deep learning analysis

Purpose: Although eating is imperative for survival, few comprehensive methods have been developed to assess freely moving nonhuman primates' eating behavior. In the current study, we distinguished eating behavior into appetitive and consummatory phases and developed nine indices to study them using manual and deep learning-based (DeepLabCut) techniques. Method: The indices were utilized to three rhesus macaques by different palatability and hunger levels to validate their utility. To execute the experiment, we designed the eating behavior cage and manufactured the artificial food. The total number of trials was 3, with 1 trial conducted using natural food and 2 trials using artificial food. Result: As a result, the indices of highest utility for hunger effect were approach frequency and consummatory duration. Appetitive composite score and consummatory duration showed the highest utility for palatability effect. To elucidate the effects of hunger and palatability, we developed 2D visualization plots based on manual indices. These 2D visualization methods could intuitively depict the palatability perception and hunger internal state. Furthermore, the developed deep learning-based analysis proved accurate and comparable with manual analysis. When comparing the time required for analysis, deep learning-based analysis was 24-times faster than manual analysis. Moreover, temporal and spatial dynamics were visualized via manual and deep learning-based analysis. Based on temporal dynamics analysis, the patterns were classified into four categories: early decline, steady decline, mid-peak with early incline, and late decline. Heatmap of spatial dynamics and trajectory-related visualization could elucidate a consumption posture and a higher spatial occupancy of food zone in hunger and with palatable food. Discussion: Collectively, this study describes a newly developed and validated multi-phase method for assessing freely moving nonhuman primate eating behavior using manual and deep learning-based analyses. These effective tools will prove valuable in food reward (palatability effect) and homeostasis (hunger effect) research

Abundant expression of SRPR in mouse epidermal keratinocyte.

<p>(A-B) <i>Srpr</i> was abundantly expressed in keratinocyte (PAM212 and HaCaT cell) and mouse dorsal skin at both mRNA by RT-PCR (A) and protein level by western blot analysis (B). (C-D) SRPR expression in dorsal skin (C) and HF (D) of BALB/C mice at postnatal days P10, P14, P17, P21, P28, P35, P42 and P49 by immunohistochemistry. Brown signals indicated the SRPR-positive epidermis cells (arrowhead), HF (arrow) and hair cortex (star). Scale bar = 100 μm.</p