Improved spatial–temporal graph convolutional networks for upper limb rehabilitation assessment based on precise posture measurement

After regular rehabilitation training, paralysis sequelae can be significantly reduced in patients with limb movement disorders caused by stroke. Rehabilitation assessment is the basis for the formulation of rehabilitation training programs and the objective standard for evaluating the effectiveness of training. However, the quantitative rehabilitation assessment is still in the experimental stage and has not been put into clinical practice. In this work, we propose improved spatial-temporal graph convolutional networks based on precise posture measurement for upper limb rehabilitation assessment. Two Azure Kinect are used to enlarge the angle range of the visual field. The rigid body model of the upper limb with multiple degrees of freedom is established. And the inverse kinematics is optimized based on the hybrid particle swarm optimization algorithm. The self-attention mechanism map is calculated to analyze the role of each upper limb joint in rehabilitation assessment, to improve the spatial-temporal graph convolution neural network model. Long short-term memory is built to explore the sequence dependence in spatial-temporal feature vectors. An exercise protocol for detecting the distal reachable workspace and proximal self-care ability of the upper limb is designed, and a virtual environment is built. The experimental results indicate that the proposed posture measurement method can reduce position jumps caused by occlusion, improve measurement accuracy and stability, and increase Signal Noise Ratio. By comparing with other models, our rehabilitation assessment model achieved the lowest mean absolute deviation, root mean square error, and mean absolute percentage error. The proposed method can effectively quantitatively evaluate the upper limb motor function of stroke patients

First identification of long non-coding RNAs in fungal parasite Nosema ceranae

International audienceAbstractNosema ceranae is a unicellular fungal parasite of honey bees and causes huge losses for apiculture. Until present, no study on N. ceranae long non-coding RNAs (lncRNAs) was documented. Here, we sequenced purified spores of N. ceranae using strand-specific library construction and high-throughput RNA sequencing technologies. In total, 83 novel lncRNAs were predicted from N. ceranae spore samples, including lncRNAs, long intergenic non-coding RNAs (lincRNAs), and sense lncRNAs. Moreover, these lncRNAs share similar characteristics with those identified in mammals and plants, such as shorter length and fewer exon number and transcript isoforms than protein-coding genes. Finally, the expression of 12 lncRNAs was confirmed with RT-PCR, confirming their true existence. To our knowledge, this is the first evidence of lncRNAs produced by a microsporidia species, offering novel insights into basic biology such as regulation of gene expression of this widespread taxonomic group

The C-terminal tail of presenilin regulates Omi/HtrA2 protease activity

Presenilin mutations are responsible for most cases of autosomal dominant inherited forms of early onset Alzheimer disease. Presenilins play an important role in amyloid beta-precursor processing, NOTCH receptor signaling, and apoptosis. However, the molecular mechanisms by which presenilins regulate apoptosis are not fully understood. Here, we report that presenilin-1 (PS1) regulates the proteolytic activity of the serine protease Omi/HtrA2 through direct interaction with its regulatory PDZ domain. We show that a peptide corresponding to the cytoplasmic C-terminal tail of PS1 dramatically increases the proteolytic activity of Omi/HtrA2 toward the inhibitor of apoptosis proteins and beta-casein and induces cell death in an Omi/HtrA2-dependent manner. Consistent with these results, ectopic expression of full-length PS1, but not PS1 lacking the C-terminal PDZ binding motif, potentiated Omi/HtrA2-induced cell death. Our results suggest that the C terminus of PS1 is an activation peptide ligand for the PDZ domain of Omi/HtrA2 and may regulate the protease activity of Omi/HtrA2 after its release from the mitochondria during apoptosis. This mechanism of Omi/HtrA2 activation is similar to the mechanism of activation of the related bacterial DegS protease by the outer-membrane porins

A HALP score-based prediction model for survival of patients with the upper tract urothelial carcinoma undergoing radical nephroureterectomy

The combination of hemoglobin, albumin, lymphocyte, and platelet (HALP) score has been confirmed as an important risk biomarker in several cancers. Hence, we aimed at evaluating the prognostic value of the HALP score in patients with non-metastatic upper tract urothelial carcinoma (UTUC). We retrospectively enrolled 533 of the 640 patients from two centers (315 and 325 patients, respectively) who underwent radical nephroureterectomy (RNU) for UTUC in this study. The cutoff value of HALP was determined using the Youden index by performing receiver operating characteristic (ROC) curve analysis. The relationship between postoperative survival outcomes and preoperative HALP level was assessed using Kaplan-Meier analysis and Cox regression analysis. As a result, the cutoff value of HALP was 28.67 and patients were then divided into HALP<28.67 group and HALP≥28.67 group. Kaplan-Meier analysis and log-rank test revealed that HALP was significantly associated with overall survival (OS) (P<0.001) and progression-free survival (PFS) (P<0.001). Multivariate analysis demonstrated that lower HALP score was an independent risk factor for OS (HR=1.54, 95%CI, 1.14-2.01, P=0.006) and PFS (HR=1.44, 95%CI, 1.07-1.93, P=0.020). Nomograms of OS and PFS incorporated with HALP score were more accurate in predicting prognosis than without. In the subgroup analysis, the HALP score could also stratify patients with respect to survival under different pathologic T stages. Therefore, pretreatment HALP score was an independent prognostic factor of OS and PFS in UTUC patients undergoing RNU

Heat shock protein 90 promotes RNA helicase DDX5 accumulation and exacerbates hepatocellular carcinoma by inhibiting autophagy

Objective: Hepatocellular carcinoma (HCC), the main type of liver cancer, has a high morbidity and mortality, and a poor prognosis. RNA helicase DDX5, which acts as a transcriptional co-regulator, is overexpressed in most malignant tumors and promotes cancer cell growth. Heat shock protein 90 (HSP90) is an important molecular chaperone in the conformational maturation and stabilization of numerous proteins involved in cell growth or survival. Methods: DDX5 mRNA and protein expression in surgically resected HCC tissues from 24 Asian patients were detected by quantitative real-time PCR and Western blot, respectively. The interaction of DDX5-HSP90 was determined by molecular docking, immunoprecipitation, and laser scanning confocal microscopy. The autophagy signal was detected by Western blot. The cell functions and signaling pathways of DDX5 were determined in 2 HCC cell lines. Two different murine HCC xenograft models were used to determine the function of DDX5 and the therapeutic effect of an HSP90 inhibitor. Results: HSP90 interacted directly with DDX5 and inhibited DDX5 protein degradation in the AMPK/ULK1-regulated autophagy pathway. The subsequent accumulation of DDX5 protein induced the malignant phenotype of HCC by activating the β-catenin signaling pathway. The silencing of DDX5 or treatment with HSP90 inhibitor both blocked in vivo tumor growth in a murine HCC xenograft model. High levels of HSP90 and DDX5 protein were associated with poor prognoses. Conclusions: HSP90 interacted with DDX5 protein and subsequently protected DDX5 protein from AMPK/ULK1-regulated autophagic degradation. DDX5 and HSP90 are therefore potential therapeutic targets for HCC

A Novel Schema-Oriented Approach for Chinese New Word Identification

With the popularity of network application-s, new words become more common and bring the poor performance of natural lan-guage processing related applications in-cluding web search. Identifying new words automatically from texts is still a very chal-lenging problem, especially for Chinese. In this paper, we propose a novel schema-oriented approach for Chinese new word i-dentification (named “ChNWI”). This ap-proach has three main steps: (1) we suggest three composition schemas that cover nearly all two-character up to four-character Chi-nese word surfaces; (2) we employ support vector machine (SVM) to classify Chinese new words of three schemas using their u-nique linguistic characteristics; and (3) we design various rules to filter identified Chi-nese new words of three schemas. Our ex-tensive evaluations with two corpora (Chi-nese news titles and CIPS-SIGHAN 2012 CSMB) show ChNWI’s efficiency on Chi-nese new word identification.

Computing Data Cubes Using Massively Parallel Processors

To better support decision making, it was proposed to extend SQL to include data cube operations. Computation of data cube requires computing a number of interrelated group-bys, which is rather expensive operation when databases are large. In this paper, we propose to couple a relational database management system with massively parallel processors (MPP) to facilitate on-line analytic processing. Extended SQL queries involving complex data analysis such as data cube computation are decomposed. Data retrieved from the database are pipelined to the MPP machine where data cubes are computed in parallel. The system architecture and issues related to parallel computation of data cubes are described. A brute force parallel data cube processing algorithm was implemented and the results of some preliminary experiments are presented. 1. Introduction Aggregation is widely used in on-line analytical processing. In relational database systems, SQL supports a set of aggregate functions (SUM, COUN..

Study on fatigue life prediction method of composite laminates

Advanced composites have been widely used in aerospace field and transportation field in ground due to their excellent mechanical properties. Fatigue damage and life prediction of composites have always been the important and difficult issues in the field of composite mechanics. In this paper, the maximum stress criterion and Puck criterion were extended to fatigue failure criterion, and the fatigue damage analysis model of composite laminates was established by combining the gradual degradation model of material properties, the regularized fatigue life analysis method and the fatigue damage accumulation theory. Then, the model was used to predict the damage evolution and failure mechanism of composite laminates, and the fatigue tests with three stress levels (55%, 60% and 65%) were conducted. The fatigue life and failure mode of the numerical results matches well with the test results. Under fatigue loadings, the fatigue damage initiated from free edges on both sides of the plate to the inside of the laminates. The matrix damage first appeared in the 90° plies on two free sides, then the matrix damage and fiber damage of 45° plies were induced. The fiber damage of 0° ply finally appears and rapidly spreads to the center of laminates until the damage covers the entire cross section