The structure and catalytic mechanism of a pseudoknot-containing hammerhead ribozyme.

We have determined the crystal structure of a pseudoknot (PK)-containing hammerhead ribozyme that closely resembles the pistol ribozyme, with essentially identical secondary structure and connectivity. The activity is more sensitive to deletion of the G8 2'OH than to the absence of magnesium ions, indicating that the catalytic mechanism is the same as the extended hammerhead, and distinct from the pistol ribozyme. Here we show that nucleophilic attack is almost perfectly in-line, and the G8 2'OH is well positioned to act as general acid, being directed towards the O5' leaving group, and 2.9 Å away from it. Despite the similarity in overall structure to the pistol ribozyme, the local structure close to the cleavage site differs, and the PK hammerhead retains its unique mechanistic identity and demonstrates enhanced activity over other hammerhead ribozymes under standard conditions.

Intercalation in 2D materials and in situ studies.

Intercalation of atoms, ions and molecules is a powerful tool for altering or tuning the properties - interlayer interactions, in-plane bonding configurations, Fermi-level energies, electronic band structures and spin-orbit coupling - of 2D materials. Intercalation can induce property changes in materials related to photonics, electronics, optoelectronics, thermoelectricity, magnetism, catalysis and energy storage, unlocking or improving the potential of 2D materials in present and future applications. In situ imaging and spectroscopy technologies are used to visualize and trace intercalation processes. These techniques provide the opportunity for deciphering important and often elusive intercalation dynamics, chemomechanics and mechanisms, such as the intercalation pathways, reversibility, uniformity and speed. In this Review, we discuss intercalation in 2D materials, beginning with a brief introduction of the intercalation strategies, then we look into the atomic and intrinsic effects of intercalation, followed by an overview of their in situ studies, and finally provide our outlook.

Identification of AURKA as a Biomarker Associated with Cuproptosis and Ferroptosis in HNSCC.

Cuproptosis and ferroptosis represent copper- and iron-dependent forms of cell death, respectively, and both are known to play pivotal roles in head and neck squamous cell carcinoma (HNSCC). However, few studies have explored the prognostic signatures related to cuproptosis and ferroptosis in HNSCC. Our objective was to construct a prognostic model based on genes associated with cuproptosis and ferroptosis. We randomly assigned 502 HSNCC samples from The Cancer Genome Atlas (TCGA) into training and testing sets. Pearson correlation analysis was utilized to identify cuproptosis-associated ferroptosis genes in the training set. Cox proportional hazards (COX) regression and least absolute shrinkage operator (LASSO) were employed to construct the prognostic model. The performance of the prognostic model was internally validated using single-factor COX regression, multifactor COX regression, Kaplan-Meier analysis, principal component analysis (PCA), and receiver operating curve (ROC) analysis. Additionally, we obtained 97 samples from the Gene Expression Omnibus (GEO) database for external validation. The constructed model, based on 12 cuproptosis-associated ferroptosis genes, proved to be an independent predictor of HNSCC prognosis. Among these genes, the increased expression of aurora kinase A (AURKA) has been implicated in various cancers. To further investigate, we employed small interfering RNAs (siRNAs) to knock down AURKA expression and conducted functional experiments. The results demonstrated that AURKA knockdown significantly inhibited the proliferation and migration of HNSCC cells (Cal27 and CNE2). Therefore, AURKA may serve as a potential biomarker in HNSCC.

Fluorination Effect on Lithium- and Manganese-Rich Layered Oxide Cathodes.

Lithium- and manganese-rich (LMR) layered oxides are promising high-energy cathodes for next-generation lithium-ion batteries, yet their commercialization has been hindered by a number of performance issues. While fluorination has been explored as a mitigating approach, results from polycrystalline-particle-based studies are inconsistent and the mechanism for improvement in some reports remains unclear. In the present study, we develop an in situ fluorination method that leads to fluorinated LMR with no apparent impurities. Using well-defined single-crystal Li1.2Ni0.2Mn0.6O2 (LNMO) as a platform, we show that a high fluorination level leads to decreased oxygen activities, reduced side reactions at high voltages, and a broadly improved cathode performance. Detailed characterization reveals a particle-level Mn3+ concentration gradient from the surface to the bulk of fluorinated-LNMO crystals, ascribed to the formation of a Ni-rich LizNixMn2-xO4-yFy (x > 0.5) spinel phase on the surface and a "spinel-layered" coherent structure in the bulk where domains of a LiNi0.5Mn1.5O4 high-voltage spinel phase are integrated into the native layered framework. This work provides fundamental understanding of the fluorination effect on LMR and key insights for future development of high-energy Mn-based cathodes with an intergrown/composite crystal structure.

Image registration for in situ X-ray nano-imaging of a composite battery cathode with deformation.

The structural and chemical evolution of battery electrodes at the nanoscale plays an important role in affecting the cell performance. Nano-resolution X-ray microscopy has been demonstrated as a powerful technique for characterizing the evolution of battery electrodes under operating conditions with sensitivity to their morphology, compositional distribution and redox heterogeneity. In real-world batteries, the electrode could deform upon battery operation, causing challenges for the image registration which is necessary for several experimental modalities, e.g. XANES imaging. To address this challenge, this work develops a deep-learning-based method for automatic particle identification and tracking. This approach was not only able to facilitate image registration with good robustness but also allowed quantification of the degree of sample deformation. The effectiveness of the method was first demonstrated using synthetic datasets with known ground truth. The method was then applied to an experimental dataset collected on an operating lithium battery cell, revealing a high degree of intra- and interparticle chemical complexity in operating batteries.

Constructed Risk Prognosis Model Associated with Disulfidptosis lncRNAs in HCC.

Disulfidptosis is a novel cell death mode in which the accumulation of disulfide bonds in tumor cells leads to cell disintegration and death. Long-stranded noncoding RNAs (LncRNAs) are aberrantly expressed in hepatocellular carcinoma (HCC) and have been reported to carry significant potential as a biomarker for HCC prognosis. However, lncRNA studies with disulfidptosis in hepatocellular carcinoma have rarely been reported. Therefore, this study aimed to construct a risk prognostic model based on the disulfidptosis-related lncRNA and investigate the mechanisms associated with disulfidptosis in hepatocellular carcinoma. The clinical and transcriptional information of 424 HCC patients was downloaded from The Cancer Genome Atlas (TCGA) and divided into test and validation sets. Furthermore, 1668 lncRNAs associated with disulfidptosis were identified using Pearson correlation. Six lncRNA constructs were finally identified for the risk prognostic model using one-way Cox proportional hazards (COX), multifactorial COX, and lasso regression. Kaplan-Meier (KM) analysis, principal component analysis, receiver operating characteristic curve (ROC), C-index, and column-line plot results confirmed that the constructed model was an independent prognostic factor. Based on the disulfidptosis risk score, risk groups were identified as potential predictors of immune cell infiltration, drug sensitivity, and immunotherapy responsiveness. Finally, we confirmed that phospholipase B domain containing 1 antisense RNA 1 (PLBD1-AS1) and muskelin 1 antisense RNA (MKLN1-AS) were highly expressed in hepatocellular carcinoma and might be potential biomarkers in HCC by KM analysis and quantitative real-time PCR (RT-qPCR). This study demonstrated that lncRNA related to disulfidptosis could serve as a biomarker to predict prognosis and treatment targets for HCC.

Asynchronous domain dynamics and equilibration in layered oxide battery cathode.

To improve lithium-ion battery technology, it is essential to probe and comprehend the microscopic dynamic processes that occur in a real-world composite electrode under operating conditions. The primary and secondary particles are the structural building blocks of battery cathode electrodes. Their dynamic inconsistency has profound but not well-understood impacts. In this research, we combine operando coherent multi-crystal diffraction and optical microscopy to examine the chemical dynamics in local domains of layered oxide cathode. Our results not only pinpoint the asynchronicity of the lithium (de)intercalation at the sub-particle level, but also reveal sophisticated diffusion kinetics and reaction patterns, involving various localized processes, e.g., chemical onset, reaction front propagation, domains equilibration, particle deformation and motion. These observations shed new lights onto the activation and degradation mechanisms of state-of-the-art battery cathode materials.