On the Trend-corrected Variant of Adaptive Stochastic Optimization Methods

Adam-type optimizers, as a class of adaptive moment estimation methods with the exponential moving average scheme, have been successfully used in many applications of deep learning. Such methods are appealing due to the capability on large-scale sparse datasets with high computational efficiency. In this paper, we present a new framework for Adam-type methods with the trend information when updating the parameters with the adaptive step size and gradients. The additional terms in the algorithm promise an efficient movement on the complex cost surface, and thus the loss would converge more rapidly. We show empirically the importance of adding the trend component, where our framework outperforms the conventional Adam and AMSGrad methods constantly on the classical models with several real-world datasets.Comment: 8 pages, 4 figures, 2 tables, IJCNN202

A Network Topology Control and Identity Authentication Protocol with Support for Movable Sensor Nodes

It is expected that in the near future wireless sensor network (WSNs) will be more widely used in the mobile environment, in applications such as Autonomous Underwater Vehicles (AUVs) for marine monitoring and mobile robots for environmental investigation. The sensor nodes’ mobility can easily cause changes to the structure of a network topology, and lead to the decline in the amount of transmitted data, excessive energy consumption, and lack of security. To solve these problems, a kind of efficient Topology Control algorithm for node Mobility (TCM) is proposed. In the topology construction stage, an efficient clustering algorithm is adopted, which supports sensor node movement. It can ensure the balance of clustering, and reduce the energy consumption. In the topology maintenance stage, the digital signature authentication based on Error Correction Code (ECC) and the communication mechanism of soft handover are adopted. After verifying the legal identity of the mobile nodes, secure communications can be established, and this can increase the amount of data transmitted. Compared to some existing schemes, the proposed scheme has significant advantages regarding network topology stability, amounts of data transferred, lifetime and safety performance of the network

Induction of the mesenchymal to epithelial transition by demethylation-activated microRNA-125b is involved in the anti-migration/invasion effects of arsenic trioxide on human chondrosarcoma

Background: In addition to treating acute promyelocytic leukemia, arsenic trioxide (ATO) suppresses other solid tumors, including chondrosarcoma. However, the effects of ATO on metastasis in chondrosarcoma cells, and the underlying molecular mechanisms remain unclear. Methods: The effects of ATO on the migratory and invasive capacities of chondrosarcoma cells were investigated by Wound healing, Transwell and EMT assays. The expression of miR-125b in human chondrosarcoma tissues and cell lines was detected by real-time PCR analysis. Bisulfite sequencing analysis (BSP) was used to detect the effects of ATO on the expression of miR-125b. The gain-of-function and loss-of-function experiments were performed on chondrosarcoma cell lines to investigate the effects of miR-125b on chondrosarcoma invasion, and to determine whether signal transducer and activator of transcription 3(Stat3) mediates these effects. Dual-luciferase reporter assay was used to identify whether Stat3 is a direct target of miR-125b. Results: MiR-125b was significantly downregulated in human metastatic chondrosarcoma tissues and cell lines but not in non-metastatic chondrosarcoma tissues. ATO up-regulates the expression of miR-125b by the demethylation of DNA. ATO induces MET and attenuates the invasive capacities of chondrosarcoma cells through miR-125b. Stat3 was verified as a direct target of miR-125b, which is involved in ATO regulating EMT-associated traits. Conclusions: These findings, for the first time, provides evidence that the miR-125b-mediated inhibition of Stat3 is involved in the ATO-induced attenuation of metastasis in chondrosarcoma cells.National Natural Science Foundation of China [81572633]; Research Fund for the Doctoral Program of Higher Education of China [20130001110076]SCI(E)[email protected]

A novel glycolysis-related gene signature for predicting the prognosis of multiple myeloma

Background: Metabolic reprogramming is an important hallmark of cancer. Glycolysis provides the conditions on which multiple myeloma (MM) thrives. Due to MM’s great heterogeneity and incurability, risk assessment and treatment choices are still difficult.Method: We constructed a glycolysis-related prognostic model by Least absolute shrinkage and selection operator (LASSO) Cox regression analysis. It was validated in two independent external cohorts, cell lines, and our clinical specimens. The model was also explored for its biological properties, immune microenvironment, and therapeutic response including immunotherapy. Finally, multiple metrics were combined to construct a nomogram to assist in personalized prediction of survival outcomes.Results: A wide range of variants and heterogeneous expression profiles of glycolysis-related genes were observed in MM. The prognostic model behaved well in differentiating between populations with various prognoses and proved to be an independent prognostic factor. This prognostic signature closely coordinated with multiple malignant features such as high-risk clinical features, immune dysfunction, stem cell-like features, cancer-related pathways, which was associated with the survival outcomes of MM. In terms of treatment, the high-risk group showed resistance to conventional drugs such as bortezomib, doxorubicin and immunotherapy. The joint scores generated by the nomogram showed higher clinical benefit than other clinical indicators. The in vitro experiments with cell lines and clinical subjects further provided convincing evidence for our study.Conclusion: We developed and validated the utility of the MM glycolysis-related prognostic model, which provides a new direction for prognosis assessment, treatment options for MM patients

Identification and validation of a novel cuproptosis-related gene signature in multiple myeloma

Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown.Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR).Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group (p < 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro.Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients