Thin Film Resistance Gating by Redox Charge Exchange: Evidence for a Quantum Transition State.

Field effect transistors (FETs) and related devices have enabled tremendous advances in electronics, as well as studies of fundamental phenomena. FETs are classically actuated as fields charge/discharge materials, thereby modifying their resistance. Here, we develop charge exchange transistors (CETs) that comprise thin films whose resistance is modified by quantum charge exchange processes, e.g., redox and bonding. We first use CETs to probe the metallocene-thin film interaction during cyclic voltammetry. Remarkably, CETs reveal transient resistance peaks associated with charge transfer during both oxidation and reduction. Our data combined with kinetics and density functional theory modeling are consistent with a multistep redox pathway, including the formation/destruction of a quantum transition state that overlaps molecule + thin film band states. As a further proof-of-principle demonstration, we also use CETs to monitor n-alkanethiol self-assembly on thin Au films in real-time. CETs exhibit monotonic resistance increase consistent with previously reported fast-then-slow kinetics attributed to thiol-thin film bond formation (charge localization) and etching and/or molecule reorganization.

Naringin as a natural candidate for anti-autoimmune hepatitis: Inhibitory potency and hepatoprotective mechanism.

BACKGROUND: Autoimmune hepatitis (AIH), primarily mediated by T cells, is characterized by liver inflammation. Despite the advancements in understanding its pathogenesis, effective therapeutic options are limited. Naringin, a flavonoid abundant in citrus fruits, is recognized for its anti-inflammatory properties and ability to protect against various inflammatory diseases, including drug-induced liver injury. However, the exact effects of naringin on AIH and the mechanisms involved remain poorly understood. PURPOSE: We aim to determine the role of naringin in AIH, exploring its targets and actions in this disease. METHODS: Network pharmacology, molecular docking, and molecular dynamics simulations were utilized to predict the HUB targets connecting naringin, T cell-mediated autoimmune disorders, and AIH. Cellular thermal shift assays were used to determine the binding abilities of naringin with the HUB targets. An in vivo experiment confirmed the impact of naringin treatment on AIH development and underlying mechanisms. RESULTS: Naringin demonstrated therapeutic effects on ConA-induced AIH. There were 455 shared targets between naringin, T cell-mediated autoimmune diseases, and AIH. Ten HUB genes (AKT1, ALB, IL-6, IL-1ß, CTNNB1, TNF, TP53, MAPK3, VEGFA, and JUN) were identified through the PPI network. Gene ontology analysis revealed involvement in gene expression regulation, lipopolysaccharide-mediated signaling, and I-kappa kinase/NFκB signaling. Pathway analysis suggested TNF, Th1/Th2 cell differentiation, and Toll-like receptor pathways, with favorable naringin-HUB gene binding. Molecular docking confirmed albumin (ALB), IL-1ß, IL-6, and TNF as primary targets for naringin. Molecular dynamics simulations showed stable binding in ALB-naringin, TNF-naringin, and IL-1ß-naringin complexes. Naringin's hepatoprotective effect on AIH was supported by increased serum ALB and decreased hepatic inflammatory cytokines including IL-1ß, IL-6, and TNF-α. CONCLUSION: Our data underscore the potential of naringin as a preventive or therapeutical agent in T cell-mediated autoimmune diseases including AIH.

pNet: A toolbox for personalized functional networks modeling.

Personalized functional networks (FNs) derived from functional magnetic resonance imaging (fMRI) data are useful for characterizing individual variations in the brain functional topography associated with the brain development, aging, and disorders. To facilitate applications of the personalized FNs with enhanced reliability and reproducibility, we develop an open-source toolbox that is user-friendly, extendable, and includes rigorous quality control (QC), featuring multiple user interfaces (graphics, command line, and a step-by-step guideline) and job-scheduling for high performance computing (HPC) clusters. Particularly, the toolbox, named personalized functional network modeling (pNet), takes fMRI inputs in either volumetric or surface type, ensuring compatibility with multiple fMRI data formats, and computes personalized FNs using two distinct modeling methods: one method optimizes the functional coherence of FNs, while the other enhances their independence. Additionally, the toolbox provides HTML-based reports for QC and visualization of personalized FNs. The toolbox is developed in both MATLAB and Python platforms with a modular design to facilitate extension and modification by users familiar with either programming language. We have evaluated the toolbox on two fMRI datasets and demonstrated its effectiveness and user-friendliness with interactive and scripting examples. pNet is publicly available at https://github.com/MLDataAnalytics/pNet.

Discrete latent embedding of single-cell chromatin accessibility sequencing data for uncovering cell heterogeneity.

Single-cell epigenomic data has been growing continuously at an unprecedented pace, but their characteristics such as high dimensionality and sparsity pose substantial challenges to downstream analysis. Although deep learning models-especially variational autoencoders-have been widely used to capture low-dimensional feature embeddings, the prevalent Gaussian assumption somewhat disagrees with real data, and these models tend to struggle to incorporate reference information from abundant cell atlases. Here we propose CASTLE, a deep generative model based on the vector-quantized variational autoencoder framework to extract discrete latent embeddings that interpretably characterize single-cell chromatin accessibility sequencing data. We validate the performance and robustness of CASTLE for accurate cell-type identification and reasonable visualization compared with state-of-the-art methods. We demonstrate the advantages of CASTLE for effective incorporation of existing massive reference datasets in a weakly supervised or supervised manner. We further demonstrate CASTLE's capacity for intuitively distilling cell-type-specific feature spectra that unveil cell heterogeneity and biological implications quantitatively.

scPRAM accurately predicts single-cell gene expression perturbation response based on attention mechanism.

MOTIVATION: With the rapid advancement of single-cell sequencing technology, it becomes gradually possible to delve into the cellular responses to various external perturbations at the gene expression level. However, obtaining perturbed samples in certain scenarios may be considerably challenging, and the substantial costs associated with sequencing also curtail the feasibility of large-scale experimentation. A repertoire of methodologies has been employed for forecasting perturbative responses in single-cell gene expression. However, existing methods primarily focus on the average response of a specific cell type to perturbation, overlooking the single-cell specificity of perturbation responses and a more comprehensive prediction of the entire perturbation response distribution. RESULTS: Here, we present scPRAM, a method for predicting perturbation responses in single-cell gene expression based on attention mechanisms. Leveraging variational autoencoders and optimal transport, scPRAM aligns cell states before and after perturbation, followed by accurate prediction of gene expression responses to perturbations for unseen cell types through attention mechanisms. Experiments on multiple real perturbation datasets involving drug treatments and bacterial infections demonstrate that scPRAM attains heightened accuracy in perturbation prediction across cell types, species, and individuals, surpassing existing methodologies. Furthermore, scPRAM demonstrates outstanding capability in identifying differentially expressed genes under perturbation, capturing heterogeneity in perturbation responses across species, and maintaining stability in the presence of data noise and sample size variations. AVAILABILITY AND IMPLEMENTATION: https://github.com/jiang-q19/scPRAM and https://doi.org/10.5281/zenodo.10935038.

Targeting dysregulated phago-/auto-lysosomes in Sertoli cells to ameliorate late-onset hypogonadism.

Age-related changes in testicular function can impact health and well-being. The mechanisms underlying age-related testicular dysfunction, such as late-onset hypogonadism (LOH), remain incompletely understood. Using single-cell RNA sequencing on human testes with LOH, we delineated Sertoli cells (SCs) as pivotal metabolic coordinators within the testicular microenvironment. In particular, lysosomal acidity probing revealed compromised degradative capacity in aged SCs, hindering autophagy and phagocytic flux. Consequently, SCs accumulated metabolites, including cholesterol, and have increased inflammatory gene expression; thus, we termed these cells as phago-/auto-lysosomal deregulated SCs. Exposure to a high-fat diet-induced phago-/auto-lysosomal dysregulated-like SCs, recapitulating LOH features in mice. Notably, efferent ductular injection and systemic TRPML1 agonist administration restored lysosomal function, normalizing testosterone deficiency and associated abnormalities in high-fat diet-induced LOH mice. Our findings underscore the central role of SCs in testis aging, presenting a promising therapeutic avenue for LOH.

Characterization of the m6A regulators' landscape highlights the clinical significance of acute myocardial infarction.

Objective: Acute myocardial infarction (AMI) is a severe cardiovascular disease that threatens human life and health globally. N6-methyladenosine (m6A) governs the fate of RNAs via m6A regulators. Nevertheless, how m6A regulators affect AMI remains to be deciphered. To solve this issue, an integrative analysis of m6A regulators in AMI was conducted. Methods: We acquired transcriptome profiles (GSE59867, GSE48060) of peripheral blood samples from AMI patients and healthy controls. Key m6A regulators were used for LASSO, and consensus clustering was conducted. Next, the m6A score was also computed. Immune cell infiltration, ferroptosis, and oxidative stress were evaluated. In-vitro and in-vivo experiments were conducted to verify the role of the m6A regulator ALKBH5 in AMI. Results: Most m6A regulators presented notable expression alterations in circulating cells of AMI patients versus those of controls. Based on key m6A regulators, we established a gene signature and a nomogram for AMI diagnosis and risk prediction. AMI patients were classified into three m6A clusters or gene clusters, respectively, and each cluster possessed the unique properties of m6A modification, immune cell infiltration, ferroptosis, and oxidative stress. Finally, the m6A score was utilized to quantify m6A modification patterns. Therapeutic targeting of ALKBH5 greatly alleviated apoptosis and intracellular ROS in H/R-induced H9C2 cells and NRCMs. Conclusion: Altogether, our findings highlight the clinical significance of m6A regulators in the diagnosis and risk prediction of AMI and indicate the critical roles of m6A modification in the regulation of immune cell infiltration, ferroptosis, and oxidative stress.

Improving Image Segmentation with Contextual and Structural Similarity.

Deep learning models for medical image segmentation are usually trained with voxel-wise losses, e.g., cross-entropy loss, focusing on unary supervision without considering inter-voxel relationships. This oversight potentially leads to semantically inconsistent predictions. Here, we propose a contextual similarity loss (CSL) and a structural similarity loss (SSL) to explicitly and efficiently incorporate inter-voxel relationships for improved performance. The CSL promotes consistency in predicted object categories for each image sub-region compared to ground truth. The SSL enforces compatibility between the predictions of voxel pairs by computing pair-wise distances between them, ensuring that voxels of the same class are close together whereas those from different classes are separated by a wide margin in the distribution space. The effectiveness of the CSL and SSL is evaluated using a clinical cone-beam computed tomography (CBCT) dataset of patients with various craniomaxillofacial (CMF) deformities and a public pancreas dataset. Experimental results show that the CSL and SSL outperform state-of-the-art regional loss functions in preserving segmentation semantics.

EpiCarousel: memory- and time-efficient identification of metacells for atlas-level single-cell chromatin accessibility data.

SUMMARY: Recent technical advancements in single-cell chromatin accessibility sequencing (scCAS) have brought new insights to the characterization of epigenetic heterogeneity. As single-cell genomics experiments scale up to hundreds of thousands of cells, the demand for computational resources for downstream analysis grows intractably large and exceeds the capabilities of most researchers. Here, we propose EpiCarousel, a tailored Python package based on lazy loading, parallel processing, and community detection for memory- and time-efficient identification of metacells, i.e. the emergence of homogenous cells, in large-scale scCAS data. Through comprehensive experiments on five datasets of various protocols, sample sizes, dimensions, number of cell types, and degrees of cell-type imbalance, EpiCarousel outperformed baseline methods in systematic evaluation of memory usage, computational time, and multiple downstream analyses including cell type identification. Moreover, EpiCarousel executes preprocessing and downstream cell clustering on the atlas-level dataset with 707 043 cells and 1 154 611 peaks within 2 h consuming <75 GB of RAM and provides superior performance for characterizing cell heterogeneity than state-of-the-art methods. AVAILABILITY AND IMPLEMENTATION: The EpiCarousel software is well-documented and freely available at https://github.com/biox-nku/epicarousel. It can be seamlessly interoperated with extensive scCAS analysis toolkits.

Rbm46 inhibits reactive oxygen species in mouse embryonic stem cells through modulating BNIP3-mediated mitophagy.

Embryonic stem cells (ESCs) exhibit a metabolic preference for glycolysis over oxidative phosphorylation to meet their substantial adenosine triphosphate (ATP) demands during self-renewal. This metabolic choice inherently maintains low mitochondrial activity and minimal reactive oxygen species (ROS) generation. Nonetheless, the intricate molecular mechanisms governing the restraint of ROS production and the mitigation of cellular damage remain incompletely elucidated. In this study, we reveal the pivotal role of RNA-binding motif protein 46 (RBM46) in ESCs, acting as a direct post transcriptional regulator of ROS levels by modulating BCL2/adenovirus E1B 19 kDa protein-interacting protein 3 (Bnip3) mRNA expression. Rbm46 knockout lead to diminished mitochondrial autophagy, culminating in elevated ROS within ESCs, disrupting the delicate balance required for healthy self-renewal. These findings provide insights into a novel mechanism governing ROS regulation in ESCs.

Tobacco control knowledge and beliefs among healthcare workers in respiratory departments in Fujian Province, China: A cross-sectional study.

INTRODUCTION: Smoking prevalence is high in China, and healthcare workers are important for tobacco control. This study aimed to determine the smoking status, cognition of tobacco hazards, and smoking cessation-related knowledge among respiratory healthcare workers, and to explore their ability to provide smoking cessation assistance. METHODS: A cross-sectional study was conducted in 2021 among 1028 respiratory healthcare workers from 89 hospitals in Fujian Province, China. A self-designed electronic questionnaire was used to collect data on smoking status, knowledge of smoking hazards, and smoking cessation knowledge. Descriptive statistics were calculated for all questions. Logistic regression analysis was used to explore the relationship between awareness of the tobacco control goals of Healthy China 2030 and demographic characteristics. RESULTS: Among the healthcare workers surveyed, 3.4% were smokers, all of whom were male. Most respondents (99.4%) were aware of smoking as a cause of lung cancer, but awareness of smoking as a cause of non-respiratory cancer was lower. The awareness rate of smoking cessation support was high (>90%), but only 40.0% of participants were aware of the Healthy China 2030 tobacco control targets. Male (HR=2.16; 95% CI: 1.69-2.80) and participation in the cessation clinic (HR=1.47; 95% CI: 1.10-1.96) were associated with higher awareness of the targets. CONCLUSIONS: Respiratory healthcare workers in Fujian Province demonstrated a high level of awareness regarding behavioral and pharmacotherapy support for smoking cessation. In order to enable healthcare workers to play a more active role in tobacco control, there is a need to increase public awareness of smoking cessation services in Fujian Province.

Polycarboxyl ionic liquid functionalized Yb-MOFs nanoballs based dual-wavelength responsive photoelectrochemical aptasensor for the simultaneous determination of AFB1 and OTA.

Developing an accurate and precise approach for the simultaneous detection of ochratoxin A (OTA) and aflatoxin B1 (AFB1) is significant for food safety surveillance. Herein, a photoelectrochemical sensing platform was constructed based on polycarboxylic ionic liquid functionalized metal-organic framework integrated with gold nanoparticles (Yb-MOFs@AuNPs). Sulfhydryl functionalized hairpin DNA (hDNA) was immobilized on a Yb-MOFs@AuNPs modified glassy carbon electrode (GCE) surface through Au-S bond. After blocking residual active binding sites with BSA, gold nanoparticles-labeled AFB1 aptamer (AuNPs-Apt 1) and gold nanorods-labeled OTA aptamer (AuNRs-Apt 2) were introduced to construct a photoelectrochemical aptasensor for the simultaneous determination of AFB1 and OTA. Due to the surface plasmon resonance effect and the nanometer size effect of gold nanomaterials, the photoelectrochemical aptasensor can output photocurrent responses as being excited with different wavelengths at 520 nm and 808 nm, respectively. When the AFB1 and OTA concentration in the range of 0.001-50.0 ng mL-1, a good linear relationship between the photocurrent difference (ΔI) before and after recognizing targets and the logarithm of AFB1 or OTA concentration was obtained. The detection limits for AFB1 and OTA were 0.40 pg mL-1 and 0.19 pg mL-1, respectively. AFB1 and OTA in corn samples were detected simultaneously by the photoelectrochemical aptasensor.

Proteomics-based vaccine targets annotation and design of multi-epitope vaccine against antibiotic-resistant Streptococcus gallolyticus.

Streptococcus gallolyticus is a non-motile, gram-positive bacterium that causes infective endocarditis. S. gallolyticus has developed resistance to existing antibiotics, and no vaccine is currently available. Therefore, it is essential to develop an effective S. gallolyticus vaccine. Core proteomics was used in this study together with subtractive proteomics and reverse vaccinology approach to find antigenic proteins that could be utilized for the design of the S. gallolyticus multi-epitope vaccine. The pipeline identified two antigenic proteins as potential vaccine targets: penicillin-binding protein and the ATP synthase subunit. T and B cell epitopes from the specific proteins were forecasted employing several immunoinformatics and bioinformatics resources. A vaccine (360 amino acids) was created using a combination of seven cytotoxic T cell lymphocyte (CTL), three helper T cell lymphocyte (HTL), and five linear B cell lymphocyte (LBL) epitopes. To increase immune responses, the vaccine was paired with a cholera enterotoxin subunit B (CTB) adjuvant. The developed vaccine was highly antigenic, non-allergenic, and stable for human use. The vaccine's binding affinity and molecular interactions with the human immunological receptor TLR4 were studied using molecular mechanics/generalized Born surface area (MMGBSA), molecular docking, and molecular dynamic (MD) simulation analyses. Escherichia coli (strain K12) plasmid vector pET-28a ( +) was used to examine the ability of the vaccine to be expressed. According to the outcomes of these computer experiments, the vaccine is quite promising in terms of developing a protective immunity against diseases. However, in vitro and animal research are required to validate our findings.

Facile fabrication of Ni, Fe-doped δ-MnO2 derived from Prussian blue analogues as an efficient catalyst for stable Li-CO2 batteries.

Rechargeable Li-CO2 batteries are regarded as an ideal new-generation energy storage system, owing to their high energy density and extraordinary CO2 capture capability. Developing a suitable cathode to improve the electrochemical performance of Li-CO2 batteries has always been a research hotspot. Herein, Ni-Fe-δ-MnO2 nano-flower composites are designed and synthesized by in situ etching a Ni-Fe PBA precursor as the cathode for Li-CO2 batteries. Ni-Fe-δ-MnO2 nanoflowers composed of ultra-thin nanosheets possess considerable surface spaces, which can not only provide abundant catalytic active sites, but also facilitate the nucleation of discharge products and promote the CO2 reduction reaction. On the one hand, the introduction of Ni and Fe elements can improve the electrical conductivity of δ-MnO2. On the other hand, the synergistic catalytic effect between Ni, Fe elements and δ-MnO2 will greatly enhance the cycling performance and reduce the overpotential of Li-CO2 batteries. Consequently, the Li-CO2 battery based on the Ni-Fe-δ-MnO2 cathode shows a high discharge capacity of 8287 mA h g-1 and can stabilize over 100 cycles at a current density of 100 mA g-1. The work offers a promising guideline to design efficient manganese-based catalysts for Li-CO2 batteries.

[Advances in the biological characteristics and stem maintenance mechanisms of tumor stem cells].

Tumor is one of the most serious diseases that threaten human health and social development, and it is the second most common cause of death worldwide. The latest statistics show that malignant tumors have surpassed cardiovascular disease as the leading cause of death in developed countries. Drug resistance, metastasis, and recurrence of tumors continue to present urgent challenges in clinical treatment. Tumor stem cells (TSCs) are a specific subset of cells that possess high capabilities of self-renewal, differentiation potential, tumorigenicity and drug resistance. They are resistant to non-specific treatment methods such as chemotherapy and radiotherapy, and play a crucial role in tumor initiation, metastasis, drug resistance, and recurrence. The surface markers, stemness maintenance mechanisms, microenvironment, and metabolic reprogramming of TSCs have become areas of intense research focus. The latest research results provide novel targets and strategies for the identification of TSCs and targeted therapy. This paper reviews the surface markers (CD133, CD44, etc.), self-renewal and epithelial mesenchymal transition (EMT) signaling pathways (Wnt/ß-catenin, Hedgehog, etc.), microenvironment characteristics, metabolic reprogramming (glycolysis, oxidative phosphorylation, etc.) and their roles in the initiation, development, metastasis and drug resistance of TSCs.

The causal association between serum metabolites and lung cancer based on multivariate Mendelian randomization.

This study seeks to understand the causal association between serum metabolites and different lung cancer types, an area yet to be extensively studied. We Used a two-sample Mendelian randomization (TSMR) approach, utilizing 486 blood metabolites as exposures and 3 distinct lung cancer types genome-wide association studies datasets as outcomes. We employed inverse variance weighting, MR-Egger, weighted median, simple mode, and weighted mode to estimate causal effects. We performed sensitivity analyses using Cochran Q test, MR-Egger intercept test, and MR-pleiotropy residual sum and outlier (MR-PRESSO). Linkage disequilibrium score (LDSC) analysis was conducted on the selected metabolites, and common confounding single nucleotide polymorphisms were eliminated using the human genotype-phenotype association Database. Metabolic pathway analysis was performed with MetaboAnalyst 5.0 software. Subsequently, a multivariate Mendelian randomization analysis was conducted to ascertain independent risk exposures. Our findings suggest independent risk factors for specific types of lung cancer: 7-methylxanthine and isoleucine for lung adenocarcinoma, cysteine and 1-arachidonoylglycerophosphocholine are identified as independent protective and risk factors for squamous lung cancer. Undecanoate (11:0) with Linoleate (18:2n6) showed a protective effect for small cell lung cancer. Additionally, 11 metabolic pathways were associated with lung cancer. This novel perspective offers a multidimensional understanding of lung cancer phenotypes, providing valuable guidance for identifying and screening of diverse lung cancer phenotypes.

Effects of Neolamarckia cadamba leaves extract on microbial community and antibiotic resistance genes in cecal contents and feces of broilers challenged with lipopolysaccharides.

The effects of Neolamarckia cadamba leaves extract (NCLE), with effective ingredients of flavonoids, on antibiotic resistance genes (ARGs) and relevant microorganisms in cecal contents and feces of broilers treated with or without lipopolysaccharide stimulation (LPS) were investigated. LPS stimulation increased (P < 0.05) the relative abundance of ARGs and mobile genetic elements (MGEs), such as tet(W/N/W), APH(3')-IIIa, ErmB, tet (44), ANT (6)-Ia, tet(O), tet (32), Vang_ACT_CHL, myrA, ANT (6)-Ib, IncQ1, tniB, and rep2 in cecal contents. However, the difference disappeared (P > 0.05) when NCLE was added at the same time. These differential ARGs and MGEs were mainly correlated (P < 0.01) with Clostridiales bacterium, Lachnospiraceae bacterium, and Candidatus Woodwardibium gallinarum. These species increased in LPS-stimulated broilers and decreased when NCLE was applied at the same time. In feces, LPS stimulation decreased (P < 0.05) the relative abundance of tet(Q), adeF, ErmF, Mef(En2), OXA-347, tet (40), npmA, tmrB, CfxA3, and ISCrsp1, while the LPS + NCLE treated group showed no significant effect (P > 0.05) on these ARGs. These differential ARGs and MGEs in feces were mainly correlated (P < 0.01) with Clostridiales bacterium, Pseudoflavonifractor sp. An184, Flavonifractor sp. An10, Ruminococcaceae bacterium, etc. These species increased in LPS-stimulated broilers and increased when NCLE was applied at the same time. In conclusion, LPS stimulation and NCLE influenced microbial communities and associated ARGs in both cecal contents and feces of broilers. NCLE alleviated the change of ARGs and MGEs in LPS-induced broilers by maintaining the microbial balance.IMPORTANCEAntibiotics showed a positive effect on gut health regulation and growth performance improvement in livestock breeding, but the antimicrobial resistance threat and environment pollution problem are increasingly severe with antibiotics abuse. As alternatives, plant extract containing bioactive substances are increasingly used to improve immunity and promote productivity. However, little is known about their effects on diversity and abundance of ARGs. Here, we investigated the effects of NCLE, with effective ingredients of flavonoids, on ARGs and relevant microorganisms in cecal contents and feces of broilers treated with or without lipopolysaccharide stimulation. We found that NCLE reduced the abundance of ARGs in cecal contents of lipopolysaccharide-induced broilers by maintaining the microbial balance. This study provides a comprehensive view of cecal and fecal microbial community, ARGs, and MGEs of broiler following LPS stimulation and NCLE treatment. It might be used to understand and control ARGs dissemination in livestock production.

BacPE: a versatile prime-editing platform in bacteria by inhibiting DNA exonucleases.

Prime editing allows precise installation of any single base substitution and small insertions and deletions without requiring homologous recombination or double-strand DNA breaks in eukaryotic cells. However, the applications in bacteria are hindered and the underlying mechanisms that impede efficient prime editing remain enigmatic. Here, we report the determination of vital cellular factors that affect prime editing in bacteria. Genetic screening of 129 Escherichia coli transposon mutants identified sbcB, a 3'→5' DNA exonuclease, as a key genetic determinant in impeding prime editing in E. coli, combinational deletions of which with two additional 3'→5' DNA exonucleases, xseA and exoX, drastically enhanced the prime editing efficiency by up to 100-fold. Efficient prime editing in wild-type E. coli can be achieved by simultaneously inhibiting the DNA exonucleases via CRISPRi. Our results pave the way for versatile applications of prime editing for bacterial genome engineering.

Aromatic Ketones as Mild Presodiating Reagents toward Cathodes for High-Performance Sodium-Ion Batteries.

Chemical presodiation (CP) is an effective strategy to enhance energy density of sodium ion batteries. However, the sodiation reagents reported so far are basically polycyclic aromatic hydrocarbons (PAHs) wth low reductive potential (~0.1 V vs. Na+ /Na), which could easily cause over-sodiation and structural deterioration of the presodiated cathodes. In this work, Aromatic ketones (AKs) are rationally designed as mild presodiating reagents by introducing a carbonyl group (C=O) into PAHs to balance the conjugated and inductive effect. As the representatives, two compounds 9-Fluorenoneb (9-FN) and Benzophenone (BP) manifest favorable equilibrium potential of 1.55 V and 1.07 V (vs. Na+ /Na), respectively. Note that 9-FN demonstrates versatile presodiating capability toward multiple Na uptake hosts (tunneled Na0.44 MnO2 , layered Na0.67 Ni0.33 Mn0.67 O2 , polyanionic Na4 Fe2.91 (PO4 )2 P2 O7 , Na3 V2 (PO4 )3 and Na3 V2 (PO4 )2 F3 ), enabling greatly improved initial charging capacity of the cathode to balance the irrevisible capacity of the anode. Our results indicate that the Aromatic ketones are competitive presodiating cathodic reagents for high-performance sodium-ion batteries, and will inspire more studies and application attempts in the future.