Deep Dynamic Epidemiological Modelling for COVID-19 Forecasting in Multi-level Districts

Objective: COVID-19 has spread worldwide and made a huge influence across the world. Modeling the infectious spread situation of COVID-19 is essential to understand the current condition and to formulate intervention measurements. Epidemiological equations based on the SEIR model simulate disease development. The traditional parameter estimation method to solve SEIR equations could not precisely fit real-world data due to different situations, such as social distancing policies and intervention strategies. Additionally, learning-based models achieve outstanding fitting performance, but cannot visualize mechanisms. Methods: Thus, we propose a deep dynamic epidemiological (DDE) method that combines epidemiological equations and deep-learning advantages to obtain high accuracy and visualization. The DDE contains deep networks to fit the effect function to simulate the ever-changing situations based on the neural ODE method in solving variants' equations, ensuring the fitting performance of multi-level areas. Results: We introduce four SEIR variants to fit different situations in different countries and regions. We compare our DDE method with traditional parameter estimation methods (Nelder-Mead, BFGS, Powell, Truncated Newton Conjugate-Gradient, Neural ODE) in fitting the real-world data in the cases of countries (the USA, Columbia, South Africa) and regions (Wuhan in China, Piedmont in Italy). Our DDE method achieves the best Mean Square Error and Pearson coefficient in all five areas. Further, compared with the state-of-art learning-based approaches, the DDE outperforms all techniques, including LSTM, RNN, GRU, Random Forest, Extremely Random Trees, and Decision Tree. Conclusion: DDE presents outstanding predictive ability and visualized display of the changes in infection rates in different regions and countries

Overexpression of Kcnmb2 in Dorsal CA1 of Offspring Mice Rescues Hippocampal Dysfunction Caused by a Methyl Donor-Rich Paternal Diet

BK channels are known regulators of neuronal excitability, synaptic plasticity, and memory. Our previous study showed that a paternal methyl donor-rich diet reduced the expression of Kcnmb2, which encodes BK channel subunit beta 2, and caused memory deficits in offspring mice. To explore the underlying cellular mechanisms, we investigated the intrinsic and synaptic properties of CA1 pyramidal neurons of the F1 offspring mice whose fathers were fed with either a methyl donor-rich diet (MD) or regular control diet (CD) for 6 weeks before mating. Whole-cell patch-clamp recordings of CA1 pyramidal neurons revealed a decrease in intrinsic excitability and reduced frequency of inhibitory post-synaptic currents in MD F1 mice compared to the CD F1 controls. AAV-based overexpression of Kcnmb2 in dorsal CA1 ameliorated changes in neuronal excitability, synaptic transmission, and plasticity in MD F1 mice. Our findings thus indicate that a transient paternal exposure to a methyl donor-rich diet prior to mating alters Kcnmb2-sensitive hippocampal functions in offspring animals

Inhibition of miR-29 by TGF-beta-Smad3 Signaling through Dual Mechanisms Promotes Transdifferentiation of Mouse Myoblasts into Myofibroblasts

MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression in post-transcriptional fashion, and emerging studies support their importance in regulating many biological processes, including myogenic differentiation and muscle development. miR-29 is a promoting factor during myogenesis but its full spectrum of impact on muscle cells has yet to be explored. Here we describe an analysis of miR-29 affected transcriptome in C2C12 muscle cells using a high throughput RNA-sequencing platform. The results reveal that miR-29 not only functions to promote myogenic differentiation but also suppresses the transdifferentiation of myoblasts into myofibroblasts. miR-29 inhibits the fibrogenic differentiation through down-regulating both extracellular matrix genes and cell adhesion genes. We further demonstrate that miR-29 is under negative regulation by TGF-beta (TGF-β)–Smad3 signaling via dual mechanisms of both inhibiting MyoD binding and enhancing Yin Yang 1 (YY1)-recruited Polycomb association. Together, these results identify miR-29 as a pleiotropic molecule in both myogenic and fibrogenic differentiation of muscle cells

Critical current density: Measurements vs. reality

Different experimental techniques are employed to evaluate the critical current density (Jc), namely transport current measurements and two different magnetisation measurements forming quasi-equilibrium and dynamic critical states. Our technique-dependent results for superconducting YBa 2Cu3O7 (YBCO) film and MgB2 bulk samples show an extremely high sensitivity of Jc and associated interpretations, such as irreversibility fields and Kramer plots, which lose meaning without a universal approach. We propose such approach for YBCO films based on their unique pinning features. This approach allows us to accurately recalculate the magnetic-field-dependent Jc obtained by any technique into the Jc behaviour, which would have been measured by any other method without performing the corresponding experiments. We also discovered low-frequency-dependent phenomena, governing flux dynamics, but contradicting the considered ones in the literature. The understanding of these phenomena, relevant to applications with moving superconductors, can clarify their dramatic impact on the electric-field criterion through flux diffusivity and corresponding measurements. © Copyright EPLA, 2013

A Novel Role for IκBζ in the Regulation of IFNγ Production

IκBζ is a novel member of the IκB family of NFκB regulators, which modulates NFκB activity in the nucleus, rather than controlling its nuclear translocation. IκBζ is specifically induced by IL-1β and several TLR ligands and positively regulates NFκB-mediated transcription of genes such as IL-6 and NGAL as an NFκB binding co-factor. We recently reported that the IL-1 family cytokines, IL-1β and IL-18, strongly synergize with TNFα for IFNγ production in KG-1 cells, whereas the same cytokines alone have minimal effects on IFNγ production. Given the striking similarities between the IL-1R and IL-18R signaling pathways we hypothesized that a common signaling event or gene product downstream of these receptors is responsible for the observed synergy. We investigated IκBζ protein expression in KG-1 cells upon stimulation with IL-1β, IL-18 and TNFα. Our results demonstrated that IL-18, as well as IL-1β, induced moderate IκBζ expression in KG-1 cells. However, TNFα synergized with IL-1β and IL-18, whereas by itself it had a minimal effect on IκBζ expression. NFκB inhibition resulted in decreased IL-1β/IL-18/TNFα-stimulated IFNγ release. Moreover, silencing of IκBζ expression led to a specific decrease in IFNγ production. Overall, our data suggests that IκBζ positively regulates NFκB-mediated IFNγ production in KG-1 cells

A Moving Window Double Locally Weighted Extreme Learning Machine on an Improved Sparrow Searching Algorithm and Its Case Study on a Hematite Grinding Process

In this paper, a double locally weighted extreme learning machine model based on a moving window is developed to realize process modeling. To improve model performances, an improved sparrow-searching algorithm is proposed to optimize the parameters of the proposed model. The effectiveness of the proposed model and algorithm are verified by data from a hematite grinding process. The experimental results show that the proposed algorithm can significantly improve the global search ability and convergence speed in the parameter optimization of the proposed model. The proposed model can correctly estimate the grinding particle size which is expected to be applied to other complex industries

Influence of different seismic motion input modes on the performance of isolated structures with different seismic measures

In order to obtain the influence of different seismic motion input modes on the performance of isolated structures with different seismic measures, the two aspects from near-fault seismic motion velocity pulse input and different dimension seismic motion input modes are studied. The finite element model of traditional seismic and base isolation frame structure with different aspect ratios is established. The actual near-seismic strong earthquake record with forward directional effect and slipping speed pulse is used as the input method of structural seismic motion to carry out nonlinear dynamics. The different dimensional seismic motion input method is selected as the quantitative, the tensile–compression stiffness ratio is the variable, and the time-history analysis of the isolation performance of a high-rise isolated structure is carried out. The experimental results show that for structures with an aspect ratio H/B of 1, 2, 3, and 4, the smaller the aspect ratio is, the better the damping effect is; the different dimensional vibration input has less isolation performance for the isolation bearing. From small to large, it is: one-dimensional vibration input, two-dimensional vibration input, three-dimensional vibration input