Observation of the Effect of Gait-induced Functional Electrical Stimulation on Stroke Patients with Foot Drop

Objective: To explore the effects of functional electrical stimulation and functional mid frequency electrical stimulation on lower limb function and balance function in stroke patients. Methods: 20 cases of stroke patients with foot drop after admission were randomly divided into the observation group and the control group, 10 cases in each group. On the basis of the two groups of patients, the observation group used the gait induced functional electrical stimulation to stimulate the peroneal nerve and the pretibial muscle in the observation group. The control group used the computer medium frequency functional electrical stimulation to stimulate the peroneal nerve and the anterior tibial muscle for 2 weeks. Before and after treatment, the lower extremity simple Fugl-Meyer scale (FMA), the Berg balance scale (BBS) and the improved Ashworth scale were evaluated respectively, and the comparative analysis was carried out in the group and between the groups. Results: After 2 weeks of treatment, the scores of FMA and BBS in the two groups were significantly higher than those before the treatment (P < 0.05), and the scores of FMA and BBS in the observation group were higher than those in the control group (P < 0.05), and the flexor muscle tension of the ankle plantar flexor muscle of the observed group was lower than that of the control group (P < 0.05). Conclusions: Exercise therapy combined with gait induced functional electrical stimulation or computer intermediate frequency functional electrical stimulation can significantly improve lower limb function and balance function in patients with ptosis, and the therapeutic effect of functional electrical stimulation combined with gait is better.

Sequence-level Semantic Representation Fusion for Recommender Systems

With the rapid development of recommender systems, there is increasing side information that can be employed to improve the recommendation performance. Specially, we focus on the utilization of the associated \emph{textual data} of items (eg product title) and study how text features can be effectively fused with ID features in sequential recommendation. However, there exists distinct data characteristics for the two kinds of item features, making a direct fusion method (eg adding text and ID embeddings as item representation) become less effective. To address this issue, we propose a novel {\ul \emph{Te}}xt-I{\ul \emph{D}} semantic fusion approach for sequential {\ul \emph{Rec}}ommendation, namely \textbf{\our}. The core idea of our approach is to conduct a sequence-level semantic fusion approach by better integrating global contexts. The key strategy lies in that we transform the text embeddings and ID embeddings by Fourier Transform from \emph{time domain} to \emph{frequency domain}. In the frequency domain, the global sequential characteristics of the original sequences are inherently aggregated into the transformed representations, so that we can employ simple multiplicative operations to effectively fuse the two kinds of item features. Our fusion approach can be proved to have the same effects of contextual convolution, so as to achieving sequence-level semantic fusion. In order to further improve the fusion performance, we propose to enhance the discriminability of the text embeddings from the text encoder, by adaptively injecting positional information via a mixture-of-experts~(MoE) modulation method. Our implementation is available at this repository: \textcolor{magenta}{\url{https://github.com/RUCAIBox/TedRec}}.Comment: 8 pages, 5 figure

Chiral symmetry breaking for deterministic switching of perpendicular magnetization by spin-orbit torque

Symmetry breaking is a characteristic to determine which branch of a bifurcation system follows upon crossing a critical point. Specifically, in spin-orbit torque (SOT) devices, a fundamental question arises: how to break the symmetry of the perpendicular magnetic moment by the in-plane spin polarization? Here, we show that the chiral symmetry breaking by the DMI can induce the deterministic SOT switching of the perpendicular magnetization. By introducing a gradient of saturation magnetization or magnetic anisotropy, non-collinear spin textures are formed by the gradient of effective SOT strength, and thus the chiral symmetry of the SOT-induced spin textures is broken by the DMI, resulting in the deterministic magnetization switching. We introduce a strategy to induce an out-of-plane (z) gradient of magnetic properties, as a practical solution for the wafer-scale manufacture of SOT devices.Comment: 16 pages, 4 figure

A modified lumped parameter model of distribution transformer winding

This work was supported by the National Key Research and Development Plan of China under Grant (2016YFB0900600XXX).The modelling of the distribution transformer winding is the starting point and serves as important basis for the transformer characteristics analysis and the lightning pulse response prediction. A distributed parameters model can depict the winding characteristics accurately, but it requires complex calculations. Lumped parameter model requires less calculations, but its applicable frequency range is not wide. This paper studies the amplitude-frequency characteristics of the lightning wave, compares the transformer modelling methods and finally proposes a modified lumped parameter model, based on the above comparison. The proposed model minimizes the errors provoked by the lumped parameter approximation, and the hyperbolic functions of the distributed parameter model. By this modification it becomes possible to accurately describe the winding characteristics and rapidly obtain the node voltage response. The proposed model can provide theoretical and experimental support to lightning protection of the distribution transformer.publishersversionpublishe

Integrated multi-omics identified the novel intratumor microbiome-derived subtypes and signature to predict the outcome, tumor microenvironment heterogeneity, and immunotherapy response for pancreatic cancer patients

Background: The extremely malignant tumour known as pancreatic cancer (PC) lacks efficient prognostic markers and treatment strategies. The microbiome is crucial to how cancer develops and responds to treatment. Our study was conducted in order to better understand how PC patients’ microbiomes influence their outcome, tumour microenvironment, and responsiveness to immunotherapy.Methods: We integrated transcriptome and microbiome data of PC and used univariable Cox regression and Kaplan–Meier method for screening the prognostic microbes. Then intratumor microbiome-derived subtypes were identified using consensus clustering. We utilized LASSO and Cox regression to build the microbe-related model for predicting the prognosis of PC, and utilized eight algorithms to assess the immune microenvironment feature. The OncoPredict package was utilized to predict drug treatment response. We utilized qRT-PCR to verify gene expression and single-cell analysis to reveal the composition of PC tumour microenvironment.Results: We obtained a total of 26 prognostic genera in PC. And PC samples were divided into two microbiome-related subtypes: Mcluster A and B. Compared with Mcluster A, patients in Mcluster B had a worse prognosis and higher TNM stage and pathological grade. Immune analysis revealed that neutrophils, regulatory T cell, CD8+ T cell, macrophages M1 and M2, cancer associated fibroblasts, myeloid dendritic cell, and activated mast cell had remarkably higher infiltrated levels within the tumour microenvironment of Mcluster B. Patients in Mcluster A were more likely to benefit from CTLA-4 blockers and were highly sensitive to 5-fluorouracil, cisplatin, gemcitabine, irinotecan, oxaliplatin, and epirubicin. Moreover, we built a microbe-derived model to assess the outcome. The ROC curves showed that the microbe-related model has good predictive performance. The expression of LAMA3 and LIPH was markedly increased within pancreatic tumour tissues and was linked to advanced stage and poor prognosis. Single-cell analysis indicated that besides cancer cells, the tumour microenvironment of PC was also rich in monocytes/macrophages, endothelial cells, and fibroblasts. LIPH and LAMA3 exhibited relatively higher expression in cancer cells and neutrophils.Conclusion: The intratumor microbiome-derived subtypes and signature in PC were first established, and our study provided novel perspectives on PC prognostic indicators and treatment options

Generation and Bioenergetic Profiles of Cybrids with East Asian mtDNA Haplogroups

Human mitochondrial DNA (mtDNA) variants and haplogroups may contribute to susceptibility to various diseases and pathological conditions, but the underlying mechanisms are not well understood. To address this issue, we established a cytoplasmic hybrid (cybrid) system to investigate the role of mtDNA haplogroups in human disease; specifically, we examined the effects of East Asian mtDNA genetic backgrounds on oxidative phosphorylation (OxPhos). We found that mtDNA single nucleotide polymorphisms such as m.489T>C, m.10398A>G, m.10400C>T, m.C16223T, and m.T16362C affected mitochondrial function at the level of mtDNA, mtRNA, or the OxPhos complex. Macrohaplogroup M exhibited higher respiratory activity than haplogroup N owing to its higher mtDNA content, mtRNA transcript levels, and complex III abundance. Additionally, haplogroup M had higher reactive oxygen species levels and NAD+/NADH ratios than haplogroup N, suggesting difference in mitonuclear interactions. Notably, subhaplogroups G2, B4, and F1 appeared to contribute significantly to the differences between haplogroups M and N. Thus, our cybrid-based system can provide insight into the mechanistic basis for the role of mtDNA haplogroups in human diseases and the effect of mtDNA variants on mitochondrial OxPhos function. In addition, studies of mitonuclear interaction using this system can reveal predisposition to certain diseases conferred by variations in mtDNA