Inverse-free zeroing neural network for time-variant nonlinear optimization with manipulator applications.

In this paper, the problem of time-variant optimization subject to nonlinear equation constraint is studied. To solve the challenging problem, methods based on the neural networks, such as zeroing neural network and gradient neural network, are commonly adopted due to their performance on handling nonlinear problems. However, the traditional zeroing neural network algorithm requires computing the matrix inverse during the solving process, which is a complicated and time-consuming operation. Although the gradient neural network algorithm does not require computing the matrix inverse, its accuracy is not high enough. Therefore, a novel inverse-free zeroing neural network algorithm without matrix inverse is proposed in this paper. The proposed algorithm not only avoids the matrix inverse, but also avoids matrix multiplication, greatly reducing the computational complexity. In addition, detailed theoretical analyses of the convergence performance of the proposed algorithm is provided to guarantee its excellent capability in solving time-variant optimization problems. Numerical simulations and comparative experiments with traditional zeroing neural network and gradient neural network algorithms substantiate the accuracy and superiority of the novel inverse-free zeroing neural network algorithm. To further validate the performance of the novel inverse-free zeroing neural network algorithm in practical applications, path tracking tasks of three manipulators (i.e., Universal Robot 5, Franka Emika Panda, and Kinova JACO2 manipulators) are conducted, and the results verify the applicability of the proposed algorithm.

A naturally isolated symbiotic bacterium suppresses flavivirus transmission by Aedes mosquitoes.

The commensal microbiota of the mosquito gut plays a complex role in determining the vector competence for arboviruses. In this study, we identified a bacterium from the gut of field Aedes albopictus mosquitoes named Rosenbergiella sp. YN46 (Rosenbergiella_YN46) that rendered mosquitoes refractory to infection with dengue and Zika viruses. Inoculation of 1.6 × 103 colony forming units (CFUs) of Rosenbergiella_YN46 into A. albopictus mosquitoes effectively prevents viral infection. Mechanistically, this bacterium secretes glucose dehydrogenase (RyGDH), which acidifies the gut lumen of fed mosquitoes, causing irreversible conformational changes in the flavivirus envelope protein that prevent viral entry into cells. In semifield conditions, Rosenbergiella_YN46 exhibits effective transstadial transmission in field mosquitoes, which blocks transmission of dengue virus by newly emerged adult mosquitoes. The prevalence of Rosenbergiella_YN46 is greater in mosquitoes from low-dengue areas (52.9 to ~91.7%) than in those from dengue-endemic regions (0 to ~6.7%). Rosenbergiella_YN46 may offer an effective and safe lead for flavivirus biocontrol.

Leveraging Representation Learning for the Construction and Application of a Knowledge Graph for Traditional Chinese Medicine: Framework Development Study.

BACKGROUND: Knowledge discovery from treatment data records from Chinese physicians is a dramatic challenge in the application of artificial intelligence (AI) models to the research of traditional Chinese medicine (TCM). OBJECTIVE: This paper aims to construct a TCM knowledge graph (KG) from Chinese physicians and apply it to the decision-making related to diagnosis and treatment in TCM. METHODS: A new framework leveraging a representation learning method for TCM KG construction and application was designed. A transformer-based Contextualized Knowledge Graph Embedding (CoKE) model was applied to KG representation learning and knowledge distillation. Automatic identification and expansion of multihop relations were integrated with the CoKE model as a pipeline. Based on the framework, a TCM KG containing 59,882 entities (eg, diseases, symptoms, examinations, drugs), 17 relations, and 604,700 triples was constructed. The framework was validated through a link predication task. RESULTS: Experiments showed that the framework outperforms a set of baseline models in the link prediction task using the standard metrics mean reciprocal rank (MRR) and Hits@N. The knowledge graph embedding (KGE) multitagged TCM discriminative diagnosis metrics also indicated the improvement of our framework compared with the baseline models. CONCLUSIONS: Experiments showed that the clinical KG representation learning and application framework is effective for knowledge discovery and decision-making assistance in diagnosis and treatment. Our framework shows superiority of application prospects in tasks such as KG-fused multimodal information diagnosis, KGE-based text classification, and knowledge inference-based medical question answering.

Excess sarcoplasmic reticulum-mitochondria calcium transport induced by Sphingosine-1-phosphate contributes to cardiomyocyte hypertrophy.

Sphingosine-1-phosphate (S1P) has been shown to possess pro-hypertrophic properties in the heart, but the detailed molecular mechanism that underlies the pathological process is rarely explored. In the present study, we aim to explore the role of S1P-mediated intracellular Ca2+ signaling, with a focus on sarcoplasmic reticulum (SR)-mitochondria communication, in cardiomyocyte hypertrophy. Cultured neonatal rat ventricular myocytes (NRVMs) displayed significantly hypertrophic growth after treatment with 1 µmol/L S1P for 48 h, as indicated by the cell surface area or mRNA expressions of hypertrophic marker genes (ANP, BNP and ß-MHC). Importantly, mitochondrial Ca2+ and reactive oxygen species (ROS) levels were dramatically elevated upon S1P stimulation, and pharmacological blockage of which abolished NRVM hypertrophy. 0.5 Hz electrical pacing induced similar cytosolic Ca2+ kinetics to S1P stimulation, but unaffected the peak of mitochondrial [Ca2+]. With interference of the expression of type 2 inositol 1,4,5-trisphosphate receptors (IP3R2), which are unemployed in electrical paced Ca2+ activity but may be activated by S1P, alteration in mitochondrial Ca2+ as well as the hypertrophic effect in NRVMs under S1P stimulation were attenuated. The hypertrophic effect of S1P can also be abolished by pharmacological block of S1PR1 or Gi signaling. Collectively, our study highlights the mechanistic role of IP3R2-mediated excess SR-mitochondria Ca2+ transport in S1P-induced cardiomyocyte hypertrophy.