UBQLN2 and HSP70 participate in Parkin-mediated mitophagy by facilitating outer mitochondrial membrane rupture.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are two aging-related neurodegenerative diseases that share common key features, including aggregation of pathogenic proteins, dysfunction of mitochondria, and impairment of autophagy. Mutations in ubiquilin 2 (UBQLN2), a shuttle protein in the ubiquitin-proteasome system (UPS), can cause ALS/FTD, but the mechanism underlying UBQLN2-mediated pathogenesis is still uncertain. Recent studies indicate that mitophagy, a selective form of autophagy which is crucial for mitochondrial quality control, is tightly associated with neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, and ALS. In this study, we show that after Parkin-dependent ubiquitination of damaged mitochondria, UBQLN2 is recruited to poly-ubiquitinated mitochondria through the UBA domain. UBQLN2 cooperates with the chaperone HSP70 to promote UPS-driven degradation of outer mitochondrial membrane (OMM) proteins. The resulting rupture of the OMM triggers the autophagosomal recognition of the inner mitochondrial membrane receptor PHB2. UBQLN2 is required for Parkin-mediated mitophagy and neuronal survival upon mitochondrial damage, and the ALS/FTD pathogenic mutations in UBQLN2 impair mitophagy in primary cultured neurons. Taken together, our findings link dysfunctional mitophagy to UBQLN2-mediated neurodegeneration.

The interaction between E3 ubiquitin ligase Parkin and mitophagy receptor PHB2 links inner mitochondrial membrane ubiquitination to efficient mitophagy.

The autophagic clearance of mitochondria has been defined as mitophagy, which is triggered by mitochondrial damage and serves as a major pathway for mitochondrial homeostasis and cellular quality control. PINK1 and Parkin-mediated mitophagy is the most extensively studied form of mitophagy, which has been linked to the pathogenesis of neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. The current paradigm of this particular mitophagy pathway is that the ubiquitination of the outer mitochondrial membrane is the key step to enable the recognition of damaged mitochondria by the core autophagic component autophagosome. However, whether the inner mitochondrial membrane (IMM) is ubiquitinated by Parkin and its contribution to sufficient mitophagy remain unclear. Here, using molecular, cellular, and biochemical approaches, we report that prohibitin 2 (PHB2), an essential IMM receptor for mitophagy, is ubiquitinated by Parkin and thereby gains higher affinity to the autophagosome during mitophagy. Our findings suggest that Parkin directly binds to PHB2 through its RING1 domain and promotes K11- and K33-linked ubiquitination on K142/K200 sites of PHB2, thereby enhancing the interaction between PHB2 and MAP1LC3B/LC3B. Interestingly and importantly, our study allows us to propose a novel model in which IMM protein PHB2 serves as both a receptor and a ubiquitin-mediated base for autophagosome recruitment to ensure efficient mitophagy.

α-Acylation of Alkenes by a Single Photocatalyst.

A direct strategy for the difunctionalization of alkenes, with acylation occurring at the more substituted alkene position, would be attractive for complex ketone synthesis. We report herein a reaction driven by a single photocatalyst that enables α-acylation in this way with the introduction of a fluoromethyl, alkyl, sulfonyl or thioether group at the ß-position of the alkene with high chemo- and regioselectivity under extremely mild conditions. Crucial to the success of this method are rate differences in the kinetics of radical generation through single-electron transfer (SET) between different radical precursors and the excited photocatalyst (PC*). Thus, the ß-position of the alkene is first occupied by the group derived from the radical precursor that can be generated most readily, and α-keto acids could be used as an electrophilic reagent for the α-acylation of alkenes.

Direct 1,2-Dicarbonylation of Alkenes towards 1,4-Diketones via Photocatalysis.

1,4-Dicarbonyl compounds are intriguing motifs and versatile precursors in numerous pharmaceutical molecules and bioactive natural compounds. Direct incorporation of two carbonyl groups into a double bond at both ends is straightforward, but also challenging. Represented herein is the first example of 1,2-dicarbonylation of alkenes by photocatalysis. Key to success is that N(n-Bu)4+ not only associates with the alkyl anion to avoid protonation, but also activates the α-keto acid to undergo electrophilic addition. The α-keto acid is employed both for acyl generation and electrophilic addition. By tuning the reductive and electrophilic ability of the acyl precursor, unsymmetric 1,4-dicarbonylation is achieved for the first time. This metal-free, redox-neutral and regioselective 1,2-dicarbonylation of alkenes is executed by a photocatalyst for versatile substrates under extremely mild conditions and shows great potential in biomolecular and drug molecular derivatization.

Electro-Chemo-Mechanically Stable and Sodiophilic Interface for Na Metal Anode in Liquid-based and Solid-State Batteries.

Na metal batteries (NMBs) are attracting increasing attention because of their high energy density. However, the widespread application of NMBs is hindered by the growth of Na dendrites and interface instability. The design of artificial solid electrolyte interphase (SEI) with tuned chemical/electrochemical/mechanical properties is the key to achieving high-performance NMBs. This work develops a metal-doped nanoscale polymeric film with tunable composition, sodiophilic sites and improved stiffness. The incorporation of metal crosslinkers in the polymer chains results in exceptional electrochemical stability for Na metal anodes, leading to a significantly prolonged lifespan even at high current densities, which is at the top of the reported literature. The mechanical properties measurements and electro-chemo-mechanical phase-field model are performed to interpret the impact of the ionic transportation capability (decoupled mechanical) and mechanic property in the metal-doped polymer interface. In addition, this approach provides a promising strategy for the rational design of electrode interfaces, providing enhanced mechanical stability and improved sodiophilicity, which can open up opportunities for the fabrication of next-generation energy storage.

FEGNet: A Feedback Enhancement Gate Network for Automatic Polyp Segmentation.

Regular colonoscopy is an effective way to prevent colorectal cancer by detecting colorectal polyps. Automatic polyp segmentation significantly aids clinicians in precisely locating polyp areas for further diagnosis. However, polyp segmentation is a challenge problem, since polyps appear in a variety of shapes, sizes and textures, and they tend to have ambiguous boundaries. In this paper, we propose a U-shaped model named Feedback Enhancement Gate Network (FEGNet) for accurate polyp segmentation to overcome these difficulties. Specifically, for the high-level features, we design a novel Recurrent Gate Module (RGM) based on the feedback mechanism, which can refine attention maps without any additional parameters. RGM consists of Feature Aggregation Attention Gate (FAAG) and Multi-Scale Module (MSM). FAAG can aggregate context and feedback information, and MSM is applied for capturing multi-scale information, which is critical for the segmentation task. In addition, we propose a straightforward but effective edge extraction module to detect boundaries of polyps for low-level features, which is used to guide the training of early features. In our experiments, quantitative and qualitative evaluations show that the proposed FEGNet has achieved the best results in polyp segmentation compared to other state-of-the-art models on five colonoscopy datasets.

Symmetric cross-entropy multi-threshold color image segmentation based on improved pelican optimization algorithm.

To address the problems of low accuracy and slow convergence of traditional multilevel image segmentation methods, a symmetric cross-entropy multilevel thresholding image segmentation method (MSIPOA) with multi-strategy improved pelican optimization algorithm is proposed for global optimization and image segmentation tasks. First, Sine chaotic mapping is used to improve the quality and distribution uniformity of the initial population. A spiral search mechanism incorporating a sine cosine optimization algorithm improves the algorithm's search diversity, local pioneering ability, and convergence accuracy. A levy flight strategy further improves the algorithm's ability to jump out of local minima. In this paper, 12 benchmark test functions and 8 other newer swarm intelligence algorithms are compared in terms of convergence speed and convergence accuracy to evaluate the performance of the MSIPOA algorithm. By non-parametric statistical analysis, MSIPOA shows a greater superiority over other optimization algorithms. The MSIPOA algorithm is then experimented with symmetric cross-entropy multilevel threshold image segmentation, and eight images from BSDS300 are selected as the test set to evaluate MSIPOA. According to different performance metrics and Fridman test, MSIPOA algorithm outperforms similar algorithms in global optimization and image segmentation, and the symmetric cross entropy of MSIPOA algorithm for multilevel thresholding image segmentation method can be effectively applied to multilevel thresholding image segmentation tasks.

Three-dimensional continuous picking path planning based on ant colony optimization algorithm.

Fruit-picking robots are one of the important means to promote agricultural modernization and improve agricultural efficiency. With the development of artificial intelligence technology, people are demanding higher picking efficiency from fruit-picking robots. And a good fruit-picking path determines the efficiency of fruit-picking. Currently, most picking path planning is a point-to-point approach, which means that the path needs to be re-planned after each completed path planning. If the picking path planning method of the fruit-picking robot is changed from a point-to-point approach to a continuous picking method, it will significantly improve its picking efficiency. The optimal sequential ant colony optimization algorithm(OSACO) is proposed for the path planning problem of continuous fruit-picking. The algorithm adopts a new pheromone update method. It introduces a reward and punishment mechanism and a pheromone volatility factor adaptive adjustment mechanism to ensure the global search capability of the algorithm, while solving the premature and local convergence problems in the solution process. And the multi-variable bit adaptive genetic algorithm is used to optimize its initial parameters so that the parameter selection does not depend on empirical and the combination of parameters can be intelligently adjusted according to different scales, thus bringing out the best performance of the ant colony algorithm. The results show that OSACO algorithms have better global search capability, higher quality of convergence to the optimal solution, shorter generated path lengths, and greater robustness than other variants of the ant colony algorithm.

Gefitinib facilitates PINK1/Parkin-mediated mitophagy by enhancing mitochondrial recruitment of OPTN.

Gefitinib, a well-known epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor for the targeted therapy of lung cancer, induces autophagy in association with drug resistance. However, it remains unclear whether gefitinib treatment can affect the selective form of autophagy (i.e., mitophagy) and be beneficial for the treatment of human diseases with decreased autophagy, such as neurodegenerative diseases. Here, we show that gefitinib treatment promotes PINK1/Parkin-mediated mitophagy in both nonneuronal and neuronal cells, and this effect is independent of EGFR. Moreover, we found that gefitinib treatment increases the recruitment of the autophagy receptor optineurin (OPTN) to damaged mitochondria, which is a downstream signaling event in PINK1/Parkin-mediated mitophagy. In addition, gefitinib treatment significantly alleviated neuronal damage in TBK1-deficient neurons, resulting in impeded mitophagy. In conclusion, our study suggests that gefitinib promotes PINK1/Parkin-mediated mitophagy via OPTN and may be beneficial for the treatment of neurodegenerative diseases that are associated with defective mitophagy.

Critical climate issues toward carbon neutrality targets.

In 2020, China announced the "emission peak, carbon neutrality" policy, that is, China aims to have CO2 emissions peak before 2030 and achieve carbon neutrality before 2060. The scenario of carbon neutrality will be significantly distinguished from the scenario we experienced since the industrial revolution. However, instrumental data are unavailable in the future carbon-neutral scenario. Earth system models and climate dynamics theory are needed to comprehend and project the climate change. In this paper, we illustrate our perspective of the issues related to "emission peak, carbon neutrality", including climate dynamics, climate-carbon feedback, interaction between China and global climate and carbon emissions and solutions, etc. We highlight that climate change has profoundly affected human production and life. The frequent occurrence of extreme weather disasters in recent years, together with the impact of epidemics, make the future "carbon peak & carbon-neutral" scenario more complex. There is whopping uncertainty but also a massive challenge to the scientific community. Thus, carbon neutrality is closely related to domestic production and lives, and there is little time left for planning. We believe that we will make a breakthrough in climate dynamics in the context of carbon neutrality with our joint efforts, which will serve our country's carbon emission policy at different stages.

Research on adaptive transmission and controls of COVID-19 on the basis of a complex network.

COVID-19 has caused massive disruption on the global economy and presents a considerable risk to human lives. Some countries have successfully controlled the pandemic by adopting strict measures, such as lockdown and travel restriction, but such methods are difficult to be applied widely due to their huge costs. To explore available and low-cost solutions, this study proposes an adaptive transmission model on the basis of a complex network, and gives control simulation method of COVID-19. The suggested model considers adaptive changes such as travel network and people's travel intention to form a three-level adaptive network transmission model among cities, communities, and people. The improved susceptible-exposed-infectious-recovered-dead transmission process is integrated into the network. Simulation experiments under high-, low-, and conventional-cost controls are performed. In these experiments, the travel restriction and closing cities are considered, and sensitivity analyses of the parameters are conducted to explore low-cost measures. Meanwhile, time duration and application conditions of different controls are discussed. Results show that lockdown is the most effective way, and the contact and infection rates are the two most important factors to control the pandemic. Low-cost combined control measures are feasible and effective for most countries. Finally, several suggestions are given for national and urban preventions and controls of COVID-19 and other infectious diseases in the future.