Progress of Single-Crystal Nickel-Cobalt-Manganese Cathode Research

The booming electric vehicle industry continues to place higher requirements on power batteries related to economic-cost, power density and safety. The positive electrode materials play an important role in the energy storage performance of the battery. The nickel-rich NCM (LiNixCoyMnzO2 with x + y + z = 1) materials have received increasing attention due to their high energy density, which can satisfy the demand of commercial-grade power batteries. Prominently, single-crystal nickel-rich electrodes with s unique micron-scale single-crystal structure possess excellent electrochemical and mechanical performance, even when tested at high rates, high cut-off voltages and high temperatures. In this review, we outline in brief the characteristics, problems faced and countermeasures of nickel-rich NCM materials. Then the distinguishing features and main synthesis methods of single-crystal nickel-rich NCM materials are summarized. Some existing issues and modification methods are also discussed in detail, especially the optimization strategies under harsh conditions. Finally, an outlook on the future development of single-crystal nickel-rich materials is provided. This work is expected to provide some reference for research on single-crystal nickel-rich ternary materials with high energy density, high safety levels, long-life, and their contribution to sustainable development

Type 2C Phosphatase 1 of Artemisia annua L. Is a Negative Regulator of ABA Signaling

The phytohormone abscisic acid (ABA) plays an important role in plant development and environmental stress response. Additionally, ABA also regulates secondary metabolism such as artemisinin in the medicinal plant Artemisia annua L. Although an earlier study showed that ABA receptor, AaPYL9, plays a positive role in ABA-induced artemisinin content improvement, many components in the ABA signaling pathway remain to be elucidated in Artemisia annua L. To get insight of the function of AaPYL9, we isolated and characterized an AaPYL9-interacting partner, AaPP2C1. The coding sequence of AaPP2C1 encodes a deduced protein of 464 amino acids, with all the features of plant type clade A PP2C. Transcriptional analysis showed that the expression level of AaPP2C1 is increased after ABA, salt, and drought treatments. Yeast two-hybrid and bimolecular fluorescence complementation assays (BiFC) showed that AaPYL9 interacted with AaPP2C1. The P89S, H116A substitution in AaPYL9 as well as G199D substitution or deletion of the third phosphorylation site-like motif in AaPP2C1 abolished this interaction. Furthermore, constitutive expression of AaPP2C1 conferred ABA insensitivity compared with the wild type. In summary, our data reveals that AaPP2C1 is an AaPYL9-interacting partner and involved in the negative modulation of the ABA signaling pathway in A. annua L

Research Progress and Perspectives on Wastewater-Based Epidemiology: A Bibliometric Analysis

Wastewater-based epidemiology (WBE) evaluates the health status, environmental exposure, and lifestyle habits of community inhabitants through the investigation of chemical or biological markers present in urban wastewater systems. This approach is frequently employed in discerning drug abuse, disease prevalence, and the presence of environmental contaminants. To comprehend the current state and developmental trajectories in WBE research, the current study utilizes the source literature of the Web of Science Core Collection (WOSCC) database. Implementing the Bibliometrix toolkit in R language and employing CiteSpace and VOSviewer for bibliometric analysis, this investigative pursuit effectuates an all-encompassing evaluation of the WBE literature, traversing a substantial time span of 16 years, encompassing 2008 through 2023. The results of this bibliometric analysis illuminate annual propensities and disciplinary distribution related to WBE research, while discerning the most impactful and prolific contributors, including authors, institutions, countries, and scholarly journals. The onset of the COVID-19 pandemic has engendered the expedited progression of WBE, leading to a substantial escalation in research endeavors in the past three years. By meticulously evaluating highly-cited publications, co-occurrence network of keywords, and keyword burst analysis, it is concluded that the research hotspots in this field focus on the monitoring of illicit drugs, psychoactive substances, and viruses in sewage. Subsequent investigations possess the capacity to propel the advancement of emerging methodologies for biomarker identification and analytical techniques. By concurrently integrating big data technologies (including artificial intelligence and cloud computing) with epidemiological and clinical data sets, a more expansive, precise, and efficacious rendition of WBE research can be realized

A Surface Defect Inspection Model via Rich Feature Extraction and Residual-Based Progressive Integration CNN

Surface defect inspection is vital for the quality control of products and the fault diagnosis of equipment. Defect inspection remains challenging due to the low level of automation in some manufacturing plants and the difficulty in identifying defects. To improve the automation and intelligence levels of defect inspection, a CNN model is proposed for the high-precision defect inspection of USB components in the actual demands of factories. First, the defect inspection system was built, and a dataset named USB-SG, which contained five types of defects—dents, scratches, spots, stains, and normal—was established. The pixel-level defect ground-truth annotations were manually marked. This paper puts forward a CNN model for solving the problem of defect inspection tasks, and three strategies are proposed to improve the model’s performance. The proposed model is built based on the lightweight SqueezeNet network, and a rich feature extraction block is designed to capture semantic and detailed information. Residual-based progressive feature integration is proposed to fuse the extracted features, which can reduce the difficulty of model fine-tuning and improve the generalization ability. Finally, a multi-step deep supervision scheme is proposed to supervise the feature integration process. The experiments on the USB-SG dataset prove that the model proposed in this paper has better performance than that of other methods, and the running speed can meet the real-time demand, which has broad application prospects in the industrial inspection scene

Versatile prodrug nanoparticles for acid-triggered precise imaging and organelle-specific combination cancer therapy

Integration of chemotherapy with photodynamic therapy (PDT) has been emerging as a novel strategy for treatment of triple negative breast cancer (TNBC). However, the clinical translation of this approach is hindered by the unwanted dark toxicity due to the "always-on" model and low tumor specificity of currently approved photosensitizer (PS). Here, the design of a multifunctional prodrug nanoparticle (NP) is described for precise imaging and organelle-specific combination cancer therapy. The prodrug NP is composed of a newly synthesized oxaliplatin prodrug, hexadecyl-oxaliplatintrimethyleneamine (HOT), an acid-activatable PS, derivative of Chlorin e6 (AC), and functionalized with a targeting ligand iRGD for tumor homing and penetration. HOT displays much higher antitumor efficiency than oxaliplatin by simultaneously inducing mitochondria depolarizing and DNA cross-linking. AC is specifically activated in the orthotopic or metastatic TNBC tumor for fluorescence imaging and PDT, while it remains inert in blood circulation to minimize the dark toxicity. Under the guide of acid-activatable fluorescence imaging, PDT and chemotherapy can be synergistically performed for highly efficient regression of TNBC. Taken together, this versatile prodrug nanoplatform could achieve tumor-specific imaging and organelle-specific combination therapy, which can provide an alternative option for cancer theranostic

Overexpression of allene oxide cyclase improves the biosynthesis of artemisinin in Artemisia annua L.

Jasmonates (JAs) are important signaling molecules in plants and play crucial roles in stress responses, secondary metabolites' regulation, plant growth and development. In this study, the promoter of AaAOC, which was the key gene of jasmonate biosynthetic pathway, had been cloned. GUS staining showed that AaAOC was expressed ubiquitiously in A. annua. AaAOC gene was overexpressed under control of 35S promoter. RT-Q-PCR showed that the expression levels of AaAOC were increased from 1.6- to 5.2-fold in AaAOC-overexpression transgenic A. annua. The results of GC-MS showed that the content of endogenous jasmonic acid (JA) was 2- to 4.7-fold of the control level in AaAOC-overexpression plants. HPLC showed that the contents of artemisinin, dihydroartemisinic acid and artemisinic acid were increased significantly in AaAOC-overexpression plants. RT-Q-PCR showed that the expression levels of FPS (farnesyl diphosphate synthase), CYP71AV1 (cytochrome P450 dependent hydroxylase) and DBR2 (double bond reductase 2) were increased significantly in AaAOC-overexpression plants. All data demonstrated that increased endogenous JA could significantly promote the biosynthesis of artemisinin in AaAOC-overexpression transgenic A. annua