An autosomal-dominant childhood-onset disorder associated with pathogenic variants in VCP.

Valosin-containing protein (VCP) is an AAA+ ATPase that plays critical roles in multiple ubiquitin-dependent cellular processes. Dominant pathogenic variants in VCP are associated with adult-onset multisystem proteinopathy (MSP), which manifests as myopathy, bone disease, dementia, and/or motor neuron disease. Through GeneMatcher, we identified 13 unrelated individuals who harbor heterozygous VCP variants (12 de novo and 1 inherited) associated with a childhood-onset disorder characterized by developmental delay, intellectual disability, hypotonia, and macrocephaly. Trio exome sequencing or a multigene panel identified nine missense variants, two in-frame deletions, one frameshift, and one splicing variant. We performed in vitro functional studies and in silico modeling to investigate the impact of these variants on protein function. In contrast to MSP variants, most missense variants had decreased ATPase activity, and one caused hyperactivation. Other variants were predicted to cause haploinsufficiency, suggesting a loss-of-function mechanism. This cohort expands the spectrum of VCP-related disease to include neurodevelopmental disease presenting in childhood.

ZNF263 cooperates with ZNF31 to promote the drug resistance and EMT of pancreatic cancer through transactivating RNF126.

The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is attribute to the aggressive local invasion, distant metastasis and drug resistance of PDAC patients, which was strongly accelerated by epithelial-mesenchymal transition (EMT). In current study, we systematically investigate the role of ZNF263/RNF126 axis in the initiation of EMT in PDAC in vitro and vivo. ZNF263 is firstly identified as a novel transactivation factor of RNF126. Both ZNF263 and RNF126 were overexpressed in PDAC tissues, which were associated with multiple advanced clinical stages and poor prognosis of PDAC patients. ZNF263 overexpression promoted cell proliferation, drug resistance and EMT in vitro via activating RNF126 following by the upregulation of Cyclin D1, N-cad, and MMP9, and the downregulation of E-cad, p21, and p27. ZNF263 silencing contributed to the opposite phenotype. Mechanistically, ZNF263 transactivated RNF126 via binding to its promoter. Further investigations revealed that ZNF263 interacted with ZNF31 to coregulate the transcription of RNF126, which in turn promoted ubiquitination-mediated degradation of PTEN. The downregulation of PTEN activated AKT/Cyclin D1 and AKT/GSK-3ß/ß-catenin signaling, thereby promoting the malignant phenotype of PDAC. Finally, the coordination of ZNF263 and RNF126 promotes subcutaneous tumor size and distant liver metastasis in vivo. ZNF263, as an oncogene, promotes proliferation, drug resistance and EMT of PDAC through transactivating RNF126.

Emerging Doped Metal-Organic Frameworks: Recent Progress in Synthesis, Applications, and First-Principles Calculations.

Metal-organic frameworks (MOFs) are crystalline porous materials with a long-range ordered structure and excellent specific surface area and have found a wide range of applications in diverse fields, such as catalysis, energy storage, sensing, and biomedicine. However, their poor electrical conductivity and chemical stability, low capacity, and weak adhesion to substrates have greatly limited their performance. Doping has emerged as a unique strategy to mitigate the issues. In this review, the concept, classification, and characterization methods of doped MOFs are first introduced, and recent progress in the synthesis and applications of doped MOFs, as well as the rapid advancements and applications of first-principles calculations based on the density functional theory (DFT) in unraveling the mechanistic origin of the enhanced performance are summarized. Finally, a perspective is included to highlight the key challenges in doping MOF materials and an outlook is provided on future research directions.

Exploring 2D Energy Storage Materials: Advances in Structure, Synthesis, Optimization Strategies, and Applications for Monovalent and Multivalent Metal-Ion Hybrid Capacitors.

The design and development of advanced energy storage devices with good energy/power densities and remarkable cycle life has long been a research hotspot. Metal-ion hybrid capacitors (MHCs) are considered as emerging and highly prospective candidates deriving from the integrated merits of metal-ion batteries with high energy density and supercapacitors with excellent power output and cycling stability. The realization of high-performance MHCs needs to conquer the inevitable imbalance in reaction kinetics between anode and cathode with different energy storage mechanisms. Featured by large specific surface area, short ion diffusion distance, ameliorated in-plane charge transport kinetics, and tunable surface and/or interlayer structures, 2D nanomaterials provide a promising platform for manufacturing battery-type electrodes with improved rate capability and capacitor-type electrodes with high capacity. In this article, the fundamental science of 2D nanomaterials and MHCs is first presented in detail, and then the performance optimization strategies from electrodes and electrolytes of MHCs are summarized. Next, the most recent progress in the application of 2D nanomaterials in monovalent and multivalent MHCs is dealt with. Furthermore, the energy storage mechanism of 2D electrode materials is deeply explored by advanced characterization techniques. Finally, the opportunities and challenges of 2D nanomaterials-based MHCs are prospected.

Cobalt ion doping and morphology tailoring enable superior zinc-ion storage in sodium vanadate nanoflowers.

Layered sodium vanadium materials have aroused increasing interest owing to their open layered structures and high theoretical capacity. Nevertheless, the strong electrostatic interactions between vanadium oxide layers and intercalated Zn2+ and the weak electronic conductivity severely limit their further development. Here, we design a series of cobalt ion-doped sodium vanadium electrode materials with nanoflower-like morphologies. Due to the open interlayer space and improved electron transfer enabled by cobalt ion preintercalation and sufficient contact area between the electrode and electrolyte provided by the three-dimensional (3D) flower-like morphology, the cobalt ion-doped sodium vanadate (CNVO-2) cathode exhibits excellent electrochemical performance, including an exceptional specific capacity (411 mA h g-1 at 0.5 A g-1) and ultrahigh structural stability (90.4 % capacity retention after 3000 cycles at 10 A g-1), outperforming many advanced ZIBs cathode materials. In addition, through various ex situ characterization techniques, an ionic exchange and multiple ion cointercalation mechanism is first revealed in sodium vanadate cathode material.

Mesoporous copper-doped δ-MnO2 superstructures to enable high-performance aqueous zinc-ion batteries.

Aqueous zinc-ion batteries (AZIBs) are competitive alternatives for large-scale energy-storage devices owing to the abundance of zinc and low cost, high theoretical specific capacity, and high safety of these batteries. High-performance and stable cathode materials in AZIBs are the key to storing Zn2+. Manganese-based cathode materials have attracted considerable attention because of their abundance, low toxicity, low cost, and abundant valence states (Mn2+, Mn3+, Mn4+, and Mn7+). However, as a typical cathode material, birnessite-MnO2 (δ-MnO2) has low conductivity and structural instability. The crystal structure may undergo severe distortion, disorder, and structural damage, leading to severe cyclic instability. In addition, its energy-storage mechanism is still unclear, and most of the reported manganese oxide-based materials do not have excellent electrochemical performance. Herein, we propose a copper-doped Cu0.05K0.11Mn0.84O2·0.54H2O (Cu2-KMO) cathode, which exhibits a large interlayer spacing, a stable structure, and accelerated reaction kinetics. This cathode was prepared using a simple hydrothermal method. The AZIB assembled using Cu2-KMO showed high specific capacity (600 mA h g-1 at 0.1 A g-1 after 75 cycles). The dissolution-deposition energy storage mechanism of Cu-KMO in AZIBs with double electron transfer was revealed using ex situ tests. The good electrochemical performance of the Cu2-KMO cathode fabricated by the doping strategy in this study provides ideas for the subsequent preparation of manganese dioxide using other strategies.

Oxygen vacancy enriched Na1.19V8O20·4.42H2O nanosheets for fast and stable Zn-ion batteries.

Here, a facile hydrothermal method is employed to prepare an oxygen vacancy enriched sodium-ion intercalation Na1.19V8O20·4.42H2O nanosheet cathode with large interlayer spacing, fast reaction kinetics, and stable structure for superior zinc-ion batteries (ZIBs). The assembled ZIB exhibits a high specific capacity and excellent structural stability without capacity decay over 2000 cycles. Moreover, the multiple ion co-intercalation mechanism and partial phase transition mechanism are elucidated based on ex situ characterization techniques.

Damage Detection of Unwashed Eggs through Video and Deep Learning.

Broken eggs can be harmful to human health but are also unfavorable for transportation and production. This study proposes a video-based detection model for the real-time detection of broken eggs regarding unwashed eggs in dynamic scenes. A system capable of the continuous rotation and translation of eggs was designed to display the entire surface of an egg. We added CA into the backbone network, fusing BiFPN and GSConv with the neck to improve YOLOv5. The improved YOLOV5 model uses intact and broken eggs for training. In order to accurately judge the category of eggs in the process of movement, ByteTrack was used to track the eggs and assign an ID to each egg. The detection results of the different frames of YOLOv5 in the video were associated by ID, and we used the method of five consecutive frames to determine the egg category. The experimental results show that, when compared to the original YOLOv5, the improved YOLOv5 model improves the precision of detecting broken eggs by 2.2%, recall by 4.4%, and mAP:0.5 by 4.1%. The experimental field results showed an accuracy of 96.4% when the improved YOLOv5 (combined with ByteTrack) was used for the video detection of broken eggs. The video-based model can detect eggs that are always in motion, which is more suitable for actual detection than a single image-based detection model. In addition, this study provides a reference for the research of video-based non-destructive testing.