Genetic networks in Parkinson's and Alzheimer's disease

Parkinson\u27s disease (PD) and Alzheimer\u27s disease (AD) are the most common neurodegenerative diseases and there is increasing evidence that they share common physiological and pathological links. Here we have conducted the largest network analysis of PD and AD based on their gene expressions in blood to date. We identified modules that were not preserved between disease and healthy control (HC) networks, and important hub genes and transcription factors (TFs) in these modules. We highlighted that the PD module not preserved in HCs was associated with insulin resistance, and HDAC6 was identified as a hub gene in this module which may have the role of influencing tau phosphorylation and autophagic flux in neurodegenerative disease. The AD module associated with regulation of lipolysis in adipocytes and neuroactive ligand-receptor interaction was not preserved in healthy and mild cognitive impairment networks and the key hubs TRPC5 and BRAP identified as potential targets for therapeutic treatments of AD. Our study demonstrated that PD and AD share common disrupted genetics and identified novel pathways, hub genes and TFs that may be new areas for mechanistic study and important targets in both diseases

A Temporal-Pattern Backdoor Attack to Deep Reinforcement Learning

Deep reinforcement learning (DRL) has made significant achievements in many real-world applications. But these real-world applications typically can only provide partial observations for making decisions due to occlusions and noisy sensors. However, partial state observability can be used to hide malicious behaviors for backdoors. In this paper, we explore the sequential nature of DRL and propose a novel temporal-pattern backdoor attack to DRL, whose trigger is a set of temporal constraints on a sequence of observations rather than a single observation, and effect can be kept in a controllable duration rather than in the instant. We validate our proposed backdoor attack to a typical job scheduling task in cloud computing. Numerous experimental results show that our backdoor can achieve excellent effectiveness, stealthiness, and sustainability. Our backdoor's average clean data accuracy and attack success rate can reach 97.8% and 97.5%, respectively

Research on energy instability of composite coal based on unsteady diffusion to cause disaster

In China, due to the influence of geological tectonics, the phenomenon of primary structural coal and tectonic coal stratification exists in many coal seams. The existence of tectonic coal leads to a sharp increase in the risk of composite coal seam outburst, which seriously restricts the safe production of coal mines. According to the gas diffusion state in soft and hard composite coal bodies, the mechanical instability law of composite coal with unsteady diffusion was simulated and analyzed. The calculation model of adsorbed gas expansion energy by unsteady diffusion was established, and the influence of steady and unsteady diffusion on the expansion energy of adsorbed gas was discussed. The control effect of adsorbed gas expansion energy on outburst was analyzed from the perspective of energy, and the disaster-causing mechanism of composite coal outburst instability by unsteady diffusion was elucidated. The results shown that, the existence of tectonic coals in the composite coal seams could increase the plastic damage degree to the adjacent primary structural coals, and improve the gas migration rate within the plastic zone of the primary structural coals, thus increasing the risk of coal and gas outbursts. The expansion energy of adsorbed gas in primary structural coal and tectonic coal under unsteady diffusion condition was 0.50 - 0.57 times and 3.36 - 3.38 times higher than that under steady diffusion conditions, respectively. The presence of tectonic coals in composite coal seams led to a huge gas concentration difference between the fissure and matrix systems within the primary structural coal, which resulted in the rapid desorption of adsorbed gas within the primary structural coal matrix, increasing the expansion energy of adsorbed gas in the adjacent primary coals, and thus significantly increased the outburst risk of composite coal seam

Balancing public and private interests through optimization of concession agreement design for user-pay PPP projects

In user-pay public private partnership (PPP) projects, private sectors collect user fees to cover cost and reap revenue. For projects that cannot be self-financed, public sectors usually invest public funds to make them financially feasible. The concession agreement allocates revenues and risks, and lies in the center of balancing public and private interests. However, stakeholders may have contrary opinions regarding the optimization of concession agreement. While private sectors are concerned about earning money, public sectors pay more attention to the efficient use of public funds. To address this challenge, this paper firstly identifies several key concessionary items, including concession period, concession price, capital structure and government subsidy. Then, a multi-objective optimization model is presented using discounted cash flow method, in which key concessionary items act as decision variables and public and private interests are represented by two sub-objectives. Subsequently, the model is solved using non-dominated sorting genetic algorithm-II (NSGA-II). Furthermore, a numerical case based on Beijing No. 4 Metro Line is provided to demonstrate the application of the model. Results show that the proposed model can produce a series of viable combinations of concessionary items that balance public and private interests, which provides practical references for relative decision making activities

Bim contributes to the progression of Huntington\u27s disease-associated phenotypes

Abstract Huntington’s disease (HD) is a neurodegenerative disorder caused by an expanded polyglutamine (polyQ) tract in the huntingtin (HTT) protein. Mutant HTT (mHTT) toxicity is caused by its aggregation/oligomerisation. The striatum is the most vulnerable region, although all brain regions undergo neuronal degeneration in the disease. Here we show that the levels of Bim, a BH3-only protein, are significantly increased in HD human post-mortem and HD mouse striata, correlating with neuronal death. Bim reduction ameliorates mHTT neurotoxicity in HD cells. In the HD mouse model, heterozygous Bim knockout significantly mitigates mHTT accumulation and neuronal death, ameliorating disease-associated phenotypes and lifespan. Therefore, Bim could contribute to the progression of HD

International Consensus Guidelines for the Definition, Detection, and Interpretation of Autophagy-Dependent Ferroptosis

Macroautophagy/autophagy is a complex degradation process with a dual role in cell death that is influenced by the cell types that are involved and the stressors they are exposed to. Ferroptosis is an iron-dependent oxidative form of cell death characterized by unrestricted lipid peroxidation in the context of heterogeneous and plastic mechanisms. Recent studies have shed light on the involvement of specific types of autophagy (e.g. ferritinophagy, lipophagy, and clockophagy) in initiating or executing ferroptotic cell death through the selective degradation of anti-injury proteins or organelles. Conversely, other forms of selective autophagy (e.g. reticulophagy and lysophagy) enhance the cellular defense against ferroptotic damage. Dysregulated autophagy-dependent ferroptosis has implications for a diverse range of pathological conditions. This review aims to present an updated definition of autophagy-dependent ferroptosis, discuss influential substrates and receptors, outline experimental methods, and propose guidelines for interpreting the results