Distinct phosphorylation states of mammalian CaMKIIß control the induction and maintenance of sleep.

The reduced sleep duration previously observed in Camk2b knockout mice revealed a role for Ca2+/calmodulin-dependent protein kinase II (CaMKII)ß as a sleep-promoting kinase. However, the underlying mechanism by which CaMKIIß supports sleep regulation is largely unknown. Here, we demonstrate that activation or inhibition of CaMKIIß can increase or decrease sleep duration in mice by almost 2-fold, supporting the role of CaMKIIß as a core sleep regulator in mammals. Importantly, we show that this sleep regulation depends on the kinase activity of CaMKIIß. A CaMKIIß mutant mimicking the constitutive-active (auto)phosphorylation state promotes the transition from awake state to sleep state, while mutants mimicking subsequent multisite (auto)phosphorylation states suppress the transition from sleep state to awake state. These results suggest that the phosphorylation states of CaMKIIß differently control sleep induction and maintenance processes, leading us to propose a "phosphorylation hypothesis of sleep" for the molecular control of sleep in mammals.

An InSAR Interferogram Filtering Method Based on Multi-Level Feature Fusion CNN.

Interferogram filtering is an essential step in processing data from interferometric synthetic aperture radar (InSAR), which greatly improves the accuracy of terrain reconstruction and deformation monitoring. Most traditional interferogram filtering methods achieve noise suppression and detail preservation through morphological estimation based on the statistical properties of the interferogram in the spatial or frequency domain. However, as the interferogram's spatial distribution is diverse and complex, traditional filtering methods struggle to adapt to different distribution and noise conditions and cannot handle detail preservation and noise suppression simultaneously. The study proposes a convolutional neural network (CNN)-based multi-level feature fusion model for interferogram filtering that differs from the traditional feedforward neural network (FNN). Adopting a multi-depth multi-path convolution strategy, the method preserves phase details and suppresses noise during interferogram filtering. In filtering experiments based on simulated data, qualitative and quantitative evaluations were used to validate the performance and generalization capabilities of the proposed method. The method's applicability was evaluated by visual observation during filtering and unwrapping experiments on real data, and the time-series deformation acquired by time series (TS)-InSAR technique is used to evaluate the effect of interferogram filters on deformation monitoring accuracy. Compared to commonly used interferogram filtering methods, the proposed method has significant advantages in terms of performance and efficiency. The study findings suggest new directions for research on high-precision InSAR data processing and provide technical support for practical applications of InSAR.

Establishment of a real-time Recombinase Polymerase Amplification (RPA) for the detection of decapod iridescent virus 1 (DIV1).

A rapid and simple real-time recombinase polymerase amplification (RPA) assay was developed to detect decapod iridescent virus 1 (DIV1). The assay was developed using optimized primers and probes designed from the conserved sequence of the DIV1 major capsid protein (MCP) gene. Using the optimized RPA assay, the DIV1 test was completed within 20 min at 39 ℃. The RPA assay was specific to DIV1 with a detection limit of 2.3 × 101 copies/reaction and there was no cross-reactivity with the other aquatic pathogens (WSSV, IHHNV, NHPB, VpAHPND, EHP, IMNV, YHV-1 and GAV) tested. Four out of 45 field-collected shrimp samples tested positive for DIV1 by real-time RPA. The same assay results were obtained by both methods. Thus, the real-time RPA assay developed could be a simple, rapid, sensitive, reliable and affordable method for the on-site diagnosis of DIV1 infection and has significant potential in helping to control DIV1 infections and reduce economic losses to the shrimp industry.

Hydrothermal route-enabled synthesis of sludge-derived carbon with oxygen functional groups for bisphenol A degradation through activation of peroxymonosulfate.

A considerable amount of sewage sludge (SS) is generated from wastewater treatment process, which is hazardous to the environment and in urge to be disposed. In this study, for the first time, we prepared carbocatalyst with abundant surface oxygen functional groups using the hazardous waste of SS as precursor via a facile hydrothermal coupled pyrolysis process. The hydrothermal treatment was found to be crucial for enhancing the oxygen content of sludge carbon (SC), most of which existed as ketonic groups. Catalytic performances of the developed SCs were examined by activating peroxymonosulfate (PMS) to degrade bisphenol A (BPA). Sample with more ketonic group performed better for BPA degradation. Under optimal reaction conditions, 100 % of BPA and 69.53 % of TOC could be removed in 20 min. Singlet oxygen (1O2) was suggested to be the main reactive oxygen species for degrading BPA and a BPA degradation pathway was proposed. The BPA solution showed decreased bio-toxicity after the oxidation process according to the acute ecotoxicity test. This study demonstrated the importance of surface functional groups on carbocatalyst for advanced oxidation process, which could be induced by a facile hydrothermal treatment. The feasibility of utilizing hazardous SS for advanced carbocatalyst fabrication was also revealed.