Paclitaxel-induced Immune Dysfunction and Activation of Transcription Factor AP-1 Facilitate Hepatitis B Virus Replication.

Background and Aims: Hepatitis B virus (HBV) reactivation is commonly observed in individuals with chronic HBV infection undergoing antineoplastic drug therapy. Paclitaxel (PTX) treatment has been identified as a potential trigger for HBV reactivation. This study aimed to uncover the mechanisms of PTX-induced HBV reactivation in vitro and in vivo, which may inform new strategies for HBV antiviral treatment. Methods: The impact of PTX on HBV replication was assessed through various methods including enzyme-linked immunosorbent assay, dual-luciferase reporter assay, quantitative real-time PCR, chromatin immunoprecipitation, and immunohistochemical staining. Transcriptome sequencing and 16S rRNA sequencing were employed to assess alterations in the transcriptome and microbial diversity in PTX-treated HBV transgenic mice. Results: PTX enhanced the levels of HBV 3.5-kb mRNA, HBV DNA, HBeAg, and HBsAg both in vitro and in vivo. PTX also promoted the activity of the HBV core promoter and transcription factor AP-1. Inhibition of AP-1 gene expression markedly suppressed PTX-induced HBV reactivation. Transcriptome sequencing revealed that PTX activated the immune-related signaling networks such as IL-17, NF-κB, and MAPK signaling pathways, with the pivotal common key molecule being AP-1. The 16S rRNA sequencing revealed that PTX induced dysbiosis of gut microbiota. Conclusions: PTX-induced HBV reactivation was likely a synergistic outcome of immune suppression and direct stimulation of HBV replication through the enhancement of HBV core promoter activity mediated by the transcription factor AP-1. These findings propose a novel molecular mechanism, underscoring the critical role of AP-1 in PTX-induced HBV reactivation.

Phenome-Wide Investigation of the Causal Associations Between Pre-Pregnancy Obesity Traits and Gestational Diabetes: A Two-Sample Mendelian Randomization Analyses.

Pre-pregnancy obesity was associated with gestational diabetes in observational studies, but whether this relationship is causal remains to be determined. To evaluate whether pre-pregnancy obesity traits causally affect gestational diabetes risk, a two-sample Mendelian randomization (MR) analysis was performed utilizing summary-level statistics from published genome-wide association studies (GWAS). Obesity-related traits included body mass index (BMI), overweight, obesity, obesity class 1, obesity class 2, obesity class 3, childhood obesity, waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), percent liver fat, visceral adipose tissue volume, abdominal subcutaneous adipose tissue volume. Effect estimates were evaluated using the inverse-variance weighting method. Weighted median, MR-Egger, simple mode, and weighted mode were performed as sensitivity analyses. Genetically predicted pre-pregnancy BMI [odds ratio (OR) = 1.68; 95% confidence interval (CI): 1.45-1.95; P = 9.13 × 10-12], overweight (OR = 1.49; 95% CI: 1.21-1.85; P = 2.06 × 10-4), obesity (OR = 1.25; 95% CI: 1.18-1.33; P = 8.01 × 10-13), obesity class 1 (OR = 1.31; 95% CI: 1.17-1.46; P = 1.49 × 10-6), obesity class 2 (OR = 1.26; 95% CI: 1.16-1.37; P = 5.23 × 10-8), childhood obesity (OR = 1.33; 95% CI: 1.23-1.44; P = 4.06 × 10-12), and WHR (OR = 2.35; 95% CI: 1.44-3.83; P = 5.89 × 10-4) were associated with increased risk of gestational diabetes. No significant association was observed with obesity class 3, WC, HC, percent liver fat, visceral adipose tissue volume, or abdominal subcutaneous adipose tissue volume. Similar results were observed in sensitivity analyses. Therefore, genetically predicted pre-pregnancy obesity traits may increase the risk of gestational diabetes. Weight control before pregnancy may be beneficial to prevent gestational diabetes.

The associations between dietary flavonoids intake and risk of depressive symptom in diabetic patients: Data from NHANES 2007-2008, 2009-2010, and 2017-2018.

BACKGROUND: The increasing incidence of depressive symptoms in diabetic patients contributes to the global burden of disease, but few epidemiological studies have evaluated the relationship between dietary flavonoids intake and depressive symptoms in diabetic patients in American adults. OBJECTIVE: This study intended to evaluate the associations of dietary flavonoids intake and depressive symptoms in diabetic patients in American adults. METHODS: We conducted a cross-sectional analysis of 1993 adults aged ≥20 years old who participated in the 2007-2008, 2009-2010, and 2017-2018 National Health and Nutrition Examination Surveys (NHANES). Chi-square test and independent-sample t-test were used to compare subjects' characteristics. Logistic regression model was further used to analyze the relationship between dietary flavonoid intake and depressive symptoms in diabetic patients. Restricted cubic spline (RCS) analysis was used to investigate the non-linear relationship between dietary flavonoid intake and the prevalence of depressive symptoms in diabetic patients. The weighted quartile sum (WQS) regression was used to analyze the effect of 29 flavonoids monomers. RESULTS: The results showed that the total flavonoid intake in the third quartile (OR, 0.635; 95 % CI,0.419-0.962; P, 0.032) was significantly associated with a reduced risk of depressive symptoms in diabetic patients compared with the lowest quartile. And there was a U-shaped association between dietary flavonoid intake and risk of depressive symptoms in diabetic patients. Top contributors of flavonoid monomers were eriodictyol, naringenin, and theaflavin-3'-gallate, accounting for a percentage of 30.83 %, 22.17 %, and 6.92 %, respectively. CONCLUSION: Moderate (56.07-207.12 mg/day) dietary flavonoid intake was associated with a reduced risk of depressive symptoms in diabetic patients. The important flavonoid monomers were eriodictyol, naringenin, and theaflavin-3'-gallate.

Nuclear-Electronic Orbital Time-Dependent Configuration Interaction Method.

Combining real-time electronic structure with the nuclear-electronic orbital (NEO) method has enabled the simulation of complex nonadiabatic chemical processes. However, accurate descriptions of hydrogen tunneling and double excitations require multiconfigurational treatments. Herein, we develop and implement the real-time NEO time-dependent configuration interaction (NEO-TDCI) approach. Comparison to NEO-full CI calculations of absorption spectra for a molecular system shows that the NEO-TDCI approach can accurately capture the tunneling splitting associated with the electronic ground state as well as vibronic progressions corresponding to double electron-proton excitations associated with excited electronic states. Both of these features are absent from spectra obtained with single reference real-time NEO methods. Our simulations of hydrogen tunneling dynamics illustrate the oscillation of the proton density from one side to the other via a delocalized, bilobal proton wave function. These results indicate that the NEO-TDCI approach is highly suitable for studying hydrogen tunneling and other inherently multiconfigurational systems.

Deciphering Charge Transfer Processes in Transition Metal Complexes from the Perspective of Ultrafast Electronic and Nuclear Motions.

Chemical transformations in charge transfer states result from the interplay between electronic dynamics and nuclear reorganization along excited-state trajectories. Here, we investigate the ultrafast structural dynamics following photoinduced electron transfer from the metal-metal-to-ligand charge transfer state of an electron donor, a Pt dimer complex, to a covalently linked electron acceptor group using ultrafast time-resolved wide-angle X-ray scattering and optical transient absorption spectroscopy methods to disentangle the interdependence of the excited-state electronic and nuclear dynamics. Following photoexcitation, Pt-Pt bond formation and contraction takes up to 1 ps, much slower than the corresponding process in analogous complexes without electron acceptor groups. Because the Pt-Pt distance change is slow with respect to excited-state electron transfer, it can affect the rate of electron transfer. These results have potential impacts on controlling electron transfer rates via structural alterations to the electron donor group, tuning the charge transfer driving force.

Identification of UDP-glucuronosyltransferase (UGT) isoforms involved in the metabolism of Chlorophenols (CPs).

Chlorophenols (CPs) are a group of pollutants that pose a great threat to the environment, they are widely used in industrial and agricultural wastes, pesticides, herbicides, textiles, pharmaceuticals and plastics. Among CPs, pentachlorophenol was listed as one of the persistent organic pollutants (POPs) by the Stockholm convention. This study aims to identify the UDP-glucosyltransferase (UGT) isoforms involved in the metabolic elimination of CPs. CPs' mono-glucuronide was detected in the human liver microsomes (HLMs) incubation mixture with co-factor uridine-diphosphate glucuronic acid (UDPGA). HLMs-catalyzed glucuronidation metabolism reaction equations followed Michaelis-Menten or substrate inhibition type. Recombinant enzymes and chemical reagents inhibition experiments were utilized to phenotype the main UGT isoforms involved in the glucuronidation of CPs. UGT1A6 might be the major enzyme in the glucuronidation of mono-chlorophenol isomer. UGT1A1, UGT1A6, UGT1A9, UGT2B4 and UGT2B7 were the most important five UGT isoforms for metabolizing the di-chlorophenol and tri-chlorophenol isomers. UGT1A1 and UGT1A3 were the most important UGT isoforms in the catalysis of tetra-chlorophenol and pentachlorophenol isomers. Species differences were investigated using rat liver microsomes (RLMs), pig liver microsomes (PLMs), dog liver microsomes (DLMs), and monkey liver microsomes (MyLMs). All these results were helpful for elucidating the metabolic elimination and toxicity of CPs.

Enhancing antitumor immunity and achieving tumor eradication with IL11RA mRNA immunotherapy.

Current methods for delivering genes to target tumors face significant challenges, including off-target effects and immune responses against delivery vectors. In this study, we developed a novel approach using messenger RNA (mRNA) to encode IL11RA for local immunotherapy, aiming to harness the immune system to combat tumors. Our research uncovered a compelling correlation between IL11RA expression and CD8 + T cell levels across multiple tumor types, with elevated IL11RA expression correlating with improved overall survival. Examination of the Pan-Cancer Atlas dataset showed a significant reduction in IL11RA expression in various cancer types compared to normal tissue, raising questions about its potential role in tumorigenesis. To achieve efficient in vivo expression of IL11RA, we synthesized two mRNA sequences mimicking the wild-type protein. These mRNA sequences were formulated and capped to ensure effective delivery, resulting in robust expression within tumor sites. Our investigation into IL11RA mRNA therapy demonstrated its effectiveness in controlling tumor growth when administered both intratumorally and intravenously in mouse models. Additionally, IL11RA mRNA treatment significantly stimulated the expansion of CD8 + T cells within tumors, draining lymph nodes, and the spleen. Transcriptome analysis revealed distinct transcriptional patterns associated with T cell functions. Using multiple deconvolution algorithms, we found substantial infiltration of CD8 + T cells following IL11RA mRNA treatment, highlighting its immunomodulatory effects within the tumor microenvironment. In conclusion, IL11RA mRNA therapy presents a promising strategy for tumor regression with potential immunomodulatory effects and clinical implications for improved survival outcomes.

Synthesis and Single Crystal X-ray Diffraction Structure of an Indium Arsenide Nanocluster.

The discovery of magic-sized clusters as intermediates in the synthesis of colloidal quantum dots has allowed for insight into formation pathways and provided atomically precise molecular platforms for studying the structure and surface chemistry of those materials. The synthesis of monodisperse InAs quantum dots has been developed through the use of indium carboxylate and As(SiMe3)3 as precursors and documented to proceed through the formation of magic-sized intermediates. Herein, we report the synthesis, isolation, and single-crystal X-ray diffraction structure of an InAs nanocluster that is ubiquitous across reports of InAs quantum dot synthesis. The structure, In26As18(O2CR)24(PR'3)3, differs substantially from previously reported semiconductor nanocluster structures even within the III-V family. However, it can be structurally linked to III-V and II-VI cluster structures through the anion sublattice. Further analysis using variable temperature absorbance spectroscopy and support from computation deepen our understanding of the reported structure and InAs nanomaterials as a whole.

Unveiling Hidden Shake-Up Features in the Uranyl M4-Edge Spectrum.

The M4,5-edge high energy resolution X-ray absorption near-edge structure (HR-XANES) spectra of actinyls offer valuable insights into the electronic structure and bonding properties of heavy-element complexes. To conduct a comprehensive spectral analysis, it is essential to employ computational methods that accurately account for relativistic effects and electron correlation. In this work, we utilize variational relativistic multireference configurational interaction methods to compute and analyze the X-ray M4-edge absorption spectrum of uranyl. By employing these advanced computational techniques, we achieve excellent agreement between the calculated spectral features and experimental observations. Moreover, the calculations unveil significant shake-up features, which arise from the intricate interplay between strongly correlated 3d core-electron and ligand excitations. This research provides important theoretical insights into the spectral characteristics of heavy-element complexes. Furthermore, it establishes the foundation for utilizing M4,5-edge spectroscopy as a means to investigate the chemical activities of such complexes. By leveraging this technique, we can gain a deeper understanding of the bonding behavior and reactivity of heavy-element compounds.

Tetravalent Cerium Alkyl and Benzyl Complexes.

High-valent cerium complexes of alkyl and benzyl ligands are unprecedented due to the incompatibility of the typically highly oxidizing Ce4+ ion and the reducing alkyl or benzyl ligand. Herein we report the synthesis and isolation of the first tetravalent cerium alkyl and benzyl complexes supported by the tri-tert-butyl imidophosphorane ligand, [NP(tBu)3]1-. The Ce4+ monoiodide complex, [Ce4+I(NP(tert-butyl)3)3] (1-CeI), serves as a precursor to the alkyl and benzyl complexes, [Ce4+(Npt)(NP(tert-butyl)3)3] (2-CeNpt) (Npt = neopentyl, CH2C(CH3)3) and [Ce4+(Bn)(NP(tert-butyl)3)3] (2-CeBn) (Bn = benzyl, CH2Ph). The bonding and structure of these complexes are characterized by single-crystal XRD, NMR and UV-vis-NIR spectroscopy, cyclic voltammetry, and DFT studies.

A Many-Body Perspective of Nuclear Quantum Effects in Aqueous Clusters.

Nuclear quantum effects play an important role in the structure and thermodynamics of aqueous systems. By performing a many-body expansion with nuclear-electronic orbital (NEO) theory, we show that proton quantization can give rise to significant energetic contributions for many-body interactions spanning several molecules in single-point energy calculations of water clusters. Although zero-point motion produces a large increase in energy at the one-body level, nuclear quantum effects serve to stabilize higher-order molecular interactions. These results are significant because they demonstrate that nuclear quantum effects play a nontrivial role in many-body interactions of aqueous systems. Our approach also provides a pathway for incorporating nuclear quantum effects into water potential energy surfaces. The NEO approach is advantageous for many-body expansion analyses because it includes nuclear quantum effects directly in the energies.

Overdestabilization vs Overstabilization in the Theoretical Analysis of f-Orbital Covalency.

The complex nature of the f-orbital electronic structures and their interaction with the chemical environment pose significant computational challenges. Advanced computational techniques that variationally include scalar relativities and spin-orbit coupling directly at the molecular orbital level have been developed to address this complexity. Among these, variational relativistic multiconfigurational multireference methods stand out for their high accuracy and systematic improvement in studies of f-block complexes. Additionally, these advanced methods offer the potential for calibrating low-scaling electronic structure methods such as density functional theory. However, studies on the Cl K-edge X-ray absorption spectra of the [Ce(III)Cl6]3- and [Ce(IV)Cl6]2- complexes show that time-dependent density functional theory with approximate exchange-correlation kernels can lead to inaccuracies, resulting in an overstabilization of 4f orbitals and incorrect assessments of covalency. In contrast, approaches utilizing small active space wave function methods may understate the stability of these orbitals. The results herein demonstrate the need for large active space, multireference, and variational relativistic methods in studying f-block complexes.

Dirac-Coulomb-Breit Molecular Mean-Field Exact-Two-Component Relativistic Equation-of-Motion Coupled-Cluster Theory.

We present a relativistic equation-of-motion coupled-cluster with single and double excitation formalism within the exact two-component framework (X2C-EOM-CCSD), where both scalar relativistic effects and spin-orbit coupling are variationally included at the reference level. Three different molecular mean-field treatments of relativistic corrections, including the one-electron, Dirac-Coulomb, and Dirac-Coulomb-Breit Hamiltonian, are considered in this work. Benchmark calculations include atomic excitations and fine-structure splittings arising from spin-orbit coupling. Comparison with experimental values and relativistic time-dependent density functional theory is also carried out. The computation of the oscillator strength using the relativistic X2C-EOM-CCSD approach allows for studies of spin-orbit-driven processes, such as the spontaneous phosphorescence lifetime.

Photodriven electron-transfer dynamics in a series of heteroleptic Cu(I)-anthraquinone dyads.

Solar fuels catalysis is a promising route to efficiently harvesting, storing, and utilizing abundant solar energy. To achieve this promise, however, molecular systems must be designed with sustainable components that can balance numerous photophysical and chemical processes. To that end, we report on the structural and photophysical characterization of a series of Cu(I)-anthraquinone-based electron donor-acceptor dyads. The dyads utilized a heteroleptic Cu(I) bis-diimine architecture with a copper(I) bis-phenanthroline chromophore donor and anthraquinone electron acceptor. We characterized the structures of the complexes using x-ray crystallography and density functional theory calculations and the photophysical properties via resonance Raman and optical transient absorption spectroscopy. The calculations and resonance Raman spectroscopy revealed that excitation of the Cu(I) metal-to-ligand charge-transfer (MLCT) transition transfers the electron to a delocalized ligand orbital. The optical transient absorption spectroscopy demonstrated that each dyad formed the oxidized copper-reduced anthraquinone charge-separated state. Unlike most Cu(I) bis-phenanthroline complexes where increasingly bulky substituents on the phenanthroline ligands lead to longer MLCT excited-state lifetimes, here, we observe a decrease in the long-lived charge-separated state lifetime with increasing steric bulk. The charge-separated state lifetimes were best explained in the context of electron-transfer theory rather than with the energy gap law, which is typical for MLCT excited states, despite the complete conjugation between the phenanthroline and anthraquinone moieties.

A carboxylate linker strategy mediated densely accessible Fe-N4 sites for enhancing oxygen electroreduction in Zn-air batteries.

Iron-nitrogen-carbon single-atom catalysts derived from zeolitic-imidazolate-framework-8 (ZIF-8) have presented its great potential for the oxygen reduction reaction (ORR) in Zn-air batteries (ZABs). However, due to insufficient active Fe-N sites, its ORR activity is inferior to Pt-based catalysts. Herein, a carboxylate (OAc) linker strategy is proposed to design a ZIF-8-derived FeNCOAc catalyst with abundant accessible Fe-N4 single-atom sites. Except that imidazole groups can coordinate with Fe ions, the OAc linker on the unsaturated coordination Zn nodes can anchor and coordinate with more Fe ions, resulting in a significant increase in Fe-N4 site density. Meanwhile, the corrosion of carbon skeleton by OAc oxidation during heat-treatment leads to improved porosity of catalyst. Benefitting from the highly dense Fe-N4 sites and hierarchical pores, the FeNCOAc endows superior performance in alkaline medium (E1/2 = 0.906 V), which is confirmed by density functional theory calculation results. Meanwhile, the assembled liquid ZAB delivers a favorable peak power density of 173.9 mW cm-2, and a high specific capacity of 770.9 mAh g-1 as well as outstanding durability. Besides, the solid-state ZAB also shows outstanding discharge performance.

Optimizing Shot Assignment in Variational Quantum Eigensolver Measurement.

Variational quantum eigensolvers (VQEs) show promise for tackling complex quantum chemistry challenges and realizing quantum advantages. However, in VQE, the measurement step encounters difficulties due to errors in objective function evaluation, e.g., the energy of a quantum state. While increasing the number of measurement shots can mitigate measurement errors, this approach leads to higher costs. Strategies for shot assignment have been investigated, allowing for the allocation of varying shot numbers to different Hamiltonian terms and reducing measurement variance through term-specific insights. In this paper, we introduce a dynamic approach, the Variance-Preserved Shot Reduction (VPSR) method. This technique strives to minimize the total number of measurement shots while preserving the variance of measurements throughout the VQE process. Our numerical experiments on H2 and LiH molecular ground states demonstrate the effectiveness of VPSR in achieving VQE convergence with a notably lower shot count.

Comparison of Variational and Perturbative Spin-Orbit Coupling within Two-Component CASSCF.

The modeling of spin-orbit coupling (SOC) remains a challenge in computational chemistry due to the high computational cost. With the rising popularity of spin-driven processes and f-block metals in chemistry and materials science, it is incumbent on the community to develop accurate multiconfigurational SOC methods that scale to large systems and understand the limits of different treatments of SOC. Herein, we introduce an implementation of perturbative SOC in scalar-relativistic two-component CASSCF (srX2C-CASSCF-SO). Perspectives on the limitations and accuracy of srX2C-CASSCF-SO are presented via benchmark calculations.

Ferroptosis in lung cancer: dual role, multi-level regulation, and new therapeutic strategies.

Lung cancer is a highly prevalent malignant tumor worldwide, with high incidence and death rates. Recently, there has been increasing recognition of the role of ferroptosis, a unique cell death mechanism, in lung cancer. This review aims to summarize the current research progress on the relationship between ferroptosis and lung cancer. It also provides a comprehensive analysis of the regulatory processes of ferroptosis in various stages, including epigenetics, transcription, post-transcription, translation, and post-translation. Additionally, the review explores the dual nature of ferroptosis in lung cancer progression, which presents interesting therapeutic possibilities. On one hand, ferroptosis can promote the escape of immune surveillance and reduce the efficacy of treatment in the early stages of tumors. On the other hand, it can counter drug resistance, enhance radiosensitivity, and promote immunotherapy. The article also discusses various combination treatment strategies based on the mechanism of ferroptosis. Overall, this review offers a holistic perspective on the role of ferroptosis in the onset, progression, and treatment of lung cancer. It aims to contribute to future research and clinical interventions in this field.

Morphological control and performance engineering of Co-based materials for supercapacitors.

As one of the most promising energy storage devices, supercapacitors exhibit a higher power density than batteries. However, its low energy density usually requires high-performance electrode materials. Although the RuO2 material shows desirable properties, its high cost and toxicity significantly limit its application in supercapacitors. Recent developments demonstrated that Co-based materials have emerged as a promising alternative to RuO2 for supercapacitors due to their low cost, favorable redox reversibility and environmental friendliness. In this paper, the morphological control and performance engineering of Co-based materials are systematically reviewed. Firstly, the principle of supercapacitors is briefly introduced, and the characteristics and advantages of pseudocapacitors are emphasized. The special forms of cobalt-based materials are introduced, including 1D, 2D and 3D nanomaterials. After that, the ways to enhance the properties of cobalt-based materials are discussed, including adding conductive materials, constructing heterostructures and doping heteroatoms. Particularly, the influence of morphological control and modification methods on the electrochemical performances of materials is highlighted. Finally, the application prospect and development direction of Co-based materials are proposed.

Improved nested U-structure for accurate nailfold capillary segmentation.

Changes in the structure and function of nailfold capillaries may be indicators of numerous diseases. Noninvasive diagnostic tools are commonly used for the extraction of morphological information from segmented nailfold capillaries to study physiological and pathological changes therein. However, current segmentation methods for nailfold capillaries cannot accurately separate capillaries from the background, resulting in issues such as unclear segmentation boundaries. Therefore, improving the accuracy of nailfold capillary segmentation is necessary to facilitate more efficient clinical diagnosis and research. Herein, we propose a nailfold capillary image segmentation method based on a U2-Net backbone network combined with a Transformer structure. This method integrates the U2-Net and Transformer networks to establish a decoder-encoder network, which inserts Transformer layers into the nested two-layer U-shaped architecture of the U2-Net. This structure effectively extracts multiscale features within stages and aggregates multilevel features across stages to generate high-resolution feature maps. The experimental results demonstrate an overall accuracy of 98.23 %, a Dice coefficient of 88.56 %, and an IoU of 80.41 % compared to the ground truth. Furthermore, our proposed method improves the overall accuracy by approximately 2 %, 3 %, and 5 % compared to the original U2-Net, Res-Unet, and U-Net, respectively. These results indicate that the Transformer-U2Net network performs well in nailfold capillary image segmentation and provides more detailed and accurate information on the segmented nailfold capillary structure, which may aid clinicians in the more precise diagnosis and treatment of nailfold capillary-related diseases.