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Cellular and functional insights into FIH-mediated hydroxylation of TRPA1

A simplified, robust protocol for [18F]fluoride elution under mild conditions to enhance late-stage aromatic radiofluorinations

Abstract Direct radiofluorination of base-sensitive PET precursors is challenging due to the harsh reaction conditions of traditional fluorine-18 radiochemistry. In particular, the presence of inorganic bases with a relatively high conjugate p K a (e.g. K 2 CO 3 ) and phase-transfer catalysts (e.g. Kryptofix 2.2.2), and/or the need for azeotropic removal of elution solvents during fluorine-18 workup have been detrimental to reaction yields. This has limited the practical applicability of base-sensitive but clinically interesting radiotracers and, ultimately, their accessibility for patient care. By lowering alkalinity and eliminating the need for phase-transfer catalysts and azeotropic drying, we speculated that radiochemical conversions (RCCs) and yields (RCYs) would substantially be improved. We demonstrate that this can be achieved by using a weak anion exchange cartridge for trapping fluorine-18. No preconditioning is required, and fluorine-18 is easily eluted directly into the reaction vessel using a solution of weak base and organic solvent, the types of which can be adjusted to the specific requirements of the desired reaction. We demonstrate the general applicability of the procedure using various elution solutions and base-sensitive, copper-mediated radiofluorinations. As proof of concept, we markedly improve RCCs and RCYs for base-labile tetrazine precursors. To demonstrate its versatility, we expand the procedure to other types of radiofluorination reactions, including non-metal-mediated and isotopic exchange reactions.

Finite set model predictive control of permanent magnet synchronous motor current based on super twisting sliding mode observer

This paper proposes a current model predictive control strategy for the permanent magnet synchronous motor (PMSM) based on a novel sliding mode observer to reduce the cost of PMSM and ensure good tracking performance. A super twisting sliding mode observer (STSMO) is designed to address the issues of high-frequency chattering and noise sensitivity caused by the large positive gain of traditional SMO. The discontinuous effect of the traditional SMO switching function is introduced into the derivative of the control rate, and a smooth estimate of the back electromotive force (EMF) is obtained through integration. Replace the sign function with a sigmoid function with smooth continuity to further reduce the chattering effect. To enhance the dynamic performance of the PMSM current loop, a finite control set model predictive control (FCS-MPC) strategy is employed in place of the conventional PI controller. Within each sampling period, all possible switching states are evaluated, and the optimal one is selected and directly applied to the inverter. Additionally, a dual-vector model predictive current control (DVMPCC) method is adopted to reduce current ripple. This approach synthesizes a voltage vector with arbitrary magnitude and direction by combining two voltage vectors within each sampling period. Numerical results demonstrate that the proposed sensorless PMSM predictive current control method achieves high accuracy in speed estimation and excellent dynamic response performance.

<i>CA</i> turns 75: Looking at the future but never forgetting the roots

Csk-dependent and -independent control of Src family kinases directs neuronal migration in the developing cerebral cortex

Soliton dynamics and stability in resonant nonlinear Schrödinger systems with cubic quintic effects via enhanced modified extended tanh function method

Abstract This study investigates solitary wave solutions of the three-dimensional, time-dependent nonlinear Schrödinger equation with cubic–quintic effects and a generalized Kudryashov-type self-phase modulation term. By applying the improved modified extended tanh function method, it obtains a broad spectrum of analytic solutions. These include bright soliton solutions, dark soliton solutions, singular periodic solutions, singular solutions, Jacobi elliptic function solutions, and a Weierstrass elliptic doubly periodic function solution. A detailed analysis demonstrates how variations in system parameters control the amplitude, width, and qualitative dynamics of the solitary waves. A comprehensive linear stability examination of the equilibrium points further reveals that parameter changes determine the emergence and disappearance of equilibrium states, with phase portraits illustrating the associated dynamical scenarios. The objectives are to establish the effectiveness of improved modified extended tanh function method in handling higher-dimensional nonlinear models, to enrich the catalogue of available exact solutions. The findings confirm that the proposed method is highly effective in generating exact solutions and in capturing intricate nonlinear structures influenced by the generalized Kudryashov contribution. This work expands the range of available solitary wave solutions and highlights their structural diversity. The study provides new theoretical insights into the interplay between nonlinearity, stability, and wave evolution, thereby offering valuable contributions to nonlinear optics, plasma physics, and higher-dimensional wave propagation.

Spatiotemporally Controlled Protein Corona‐Armored DNA Nanomachine for Multitype Biomarker Imaging in Living Cells

Abstract DNA nanomachines have significant potential for biosensing because of their high programmability, signal amplification ability, and excellent biocompatibility. However, under physiological conditions, their performance is often hindered by insufficient endogenous driving forces, nuclease degradation, and lysosomal entrapment. In this study, we develop a protein corona (PC)‐armored DNA nanomachine with spatiotemporal control for multiple intracellular biomarker imaging. By pre‐assembling a UV‐responsive PC shell, the DNA nanomachine forms a physical barrier that protects nucleic acids from nucleases, reduces uncontrollable PC formation during unimpaired operation, and enhances cellular uptake via PC‐mediated targeting. After internalization, the retained PC promotes lysosomal escape, followed by light‐triggered disassembly for precise cytoplasmic operation of the nanomachine. Notably, our nanomachine employs RNA as a track and the widely expressed intracellular RNase H enzyme as the driving force, circumventing sequence limitations and establishing a general operational platform. Through this modulation, we achieve in situ imaging of microRNA in U87 human glioblastoma cells and ATP in A549 lung carcinoma cells, pioneering a PC‐enabled paradigm for DNA nanomachines and building a versatile intracellular diagnostic platform for precision medicine.

Adaptive federated clustering for uncertainty-aware learning on decentralized big data platforms

Federated learning (FL) struggles with scalability in decentralized big data platforms due to data heterogeneity, communication bottlenecks, and computational inefficiencies. We propose Adaptive Federated Clustering (AFC), a novel framework that addresses these challenges through three key innovations: (1) adaptive client selection based on computational capacity and data relevance, (2) hierarchical aggregation organizing clients into clusters for localized updates, and (3) sparsity- and quantization-based model compression. Experiments on CIFAR-10, CIFAR-100, Fashion-MNIST, and MIMIC-III demonstrate AFC achieves 4.3% higher accuracy than FedAvg, 49% lower communication cost, and 35% faster convergence. Under backdoor attacks, AFC shows only 2.8% accuracy degradation versus 7% for FedAvg. While AFC assumes relatively stable network connectivity and does not yet support fine-grained personalization, it significantly outperforms existing algorithms in scalability, robustness, and efficiency. These results demonstrate AFC’s practical value for secure collaborative learning on decentralized platforms, particularly in healthcare and IoT applications where bandwidth constraints and data heterogeneity are prevalent.

Learning from prostate cancer statistics

Tetramerization of the DNA mismatch repair protein MutS enhances daughter strand incision preferentially in the vicinity of replication errors

A transfer learning-driven fine-tuning of YOLOv10 for improved brain tumor detection in MRI images

A 6-month longitudinal and comparative study of corneal biomechanical properties after SMILE with two different optical zone sizes

Purpose To precisely evaluate the independent influence of two different optical zone (OZ) sizes (6.3 mm vs. 6.5 mm) on corneal biomechanical properties within 6 months after Small Incision Lenticule Extraction (SMILE) using multivariable-adjusted statistical models. Methods This retrospective study included myopic patients who underwent SMILE between 2022 and 2024. Patients were grouped into two groups based on the planned OZ: Group A (6.3 mm, 44 eyes) and Group B (6.5 mm, 54 eyes). Corneal biomechanical parameters were measured using the Corvis ST preoperatively and at 1, 3, and 6 months postoperatively. Linear Mixed Models (LMM) were used to assess the independent effect of OZ size, adjusting for key baseline covariates and accounting for inter-eye correlation by including a random intercept for patient identifier (ID). Results A total of 98 eyes were analyzed. Baseline analysis revealed a significant imbalance between the groups, with Group A (6.3 mm OZ) having higher myopia and a greater corneal stromal ablation depth (both P &lt; 0.001). The central finding from the LMM analysis was that, after adjusting for all covariates, optical zone size (6.3 mm vs. 6.5 mm) had no independent, statistically significant effect on 11 of the 12 biomechanical parameters (all P &gt; 0.05), with the sole exception of Ambrosio Relational Thickness Horizontal (ARTH) (P = 0.012). In contrast, several preoperative covariates, particularly corneal stromal ablation depth and preoperative central corneal thickness, were identified as significant predictors of multiple postoperative biomechanical parameters. Conclusion The independent effect of a 0.2 mm difference in optical zone size on corneal biomechanical properties after SMILE appears to be limited. After comprehensive statistical adjustment, the results suggest that preoperative anatomical and surgical parameters, especially corneal stromal ablation depth, are the primary drivers of the postoperative biomechanical response, rather than the minor difference in OZ size itself. This study underscores the importance of confounder adjustment in refractive surgery research and suggests that maximizing the residual stromal bed may be more critical for maintaining corneal biomechanical integrity than fine-tuning the optical zone diameter.

Reviewer acknowledgement 2025

Structural basis for E3 ubiquitin ligase UHRF1 binding to nucleosome core particle and histone H3 ubiquitination

AttBiLSTM_DE: enhancing anticancer peptide prediction using word embedding and an optimized attention-based BiLSTM framework

Choline Iodide‐Mediated Sulfur Conversion and Zinc Plating/Stripping Chemistry in Aqueous Zn–S Batteries

Abstract Aqueous Zn–S batteries are promising candidates for future energy storage due to their intrinsic safety, environmental friendliness, and low cost. However, their practical application is hindered by sluggish sulfur redox kinetics and rapid zinc anode degradation. Here, we introduce choline iodide (ChI) as a multifunctional electrolyte additive that enables bidirectional catalysis of sulfur conversion and simultaneous protection of the zinc anode. During discharge, Ch + promotes the formation of soluble polysulfide intermediates, which rapidly combine with Zn 2+ to form ZnS via a solid–liquid–solid pathway, accelerating reaction kinetics. During charge, iodine species catalyze the conversion of ZnS back to sulfur. Moreover, Ch + adsorbs on the zinc anode, suppressing dendrite growth and the hydrogen evolution reaction. Importantly, Ch + also inhibits polyiodide shuttling at high iodine concentrations, maximizing catalytic efficiency. Coupled with a CoNC solid‐phase catalyst, the Zn–S cell achieves a record‐low polarization of 0.26 V at 0.1 C, delivers 780 mAh g −1 at 10 C, and maintains 380 mAh g −1 after 5500 cycles.

Infiltration of CXCL9+ macrophages confers a favorable prognosis in breast cancer: Insights from an integrated single-cell RNA and bulk RNA sequencing study

Background Breast cancer is the most common cancer among women and a leading contributor to disease-related mortality. While advancements in diagnostic techniques and the widespread dissemination of medical knowledge have improved outcomes, immunotherapy targeting the tumor microenvironment offers a promising approach to further reducing the disease burden. Methods We first explored cellular heterogeneity within breast cancer tumors using single-cell RNA sequencing and subsequently analyzed the association between the infiltration levels of various cell types and survival prognosis using a deconvolution algorithm combined with bulk RNA sequencing. Our analysis identified CXCL9 + macrophages as being associated with improved survival outcomes. Next, WGCNA was used to identify genes related to CXCL9 + macrophage infiltration, and a survival risk model was constructed based on these genes. Finally, experiments were conducted to validate the effects of CXCL9 + macrophages on breast cancer cells. Results We found that CXCL9 + macrophage primarily interacted with cytokines and activated T and NK cells through the CXCL9/10/11-CXCR3 axis. Increased infiltration, as observed in bulk RNA sequencing, was associated with improved patient survival. The risk model constructed based on CXCL9 + macrophage infiltration-related genes demonstrated strong efficacy in predicting patient survival outcomes. Finally, in vitro experiments confirmed that CXCL9 + macrophages inhibited the viability of breast cancer cells. Conclusion CXCL9 + macrophages could play a significant role in inhibiting breast cancer, and their infiltration into tumor tissues is associated with improved survival in breast cancer patients. Immunotherapy targeting CXCL9 + macrophages hold great potential as a therapeutic strategy.

N-terminal half of MED14 is critical for Mediator-RNA polymerase II interaction and the resulting transcription

Study on the crack resistance of USP warm-mix rubber asphalt and its mixtures

Multiple‐Birth‐Acceptor: Easily‐Synthesized Mixture for Easily‐Fabricated Quaternary Organic Solar Cells with Beyond 20% Efficiency

Abstract Ternary strategy has been proved very effective to improve the power conversion efficiency (PCE) of organic solar cells (OSCs). However, quaternary OSCs (QOSCs), containing four components in the active layer, have been rarely reported due to the complexity of material synthesis and optimization of active layer composition. Here, we developed a simple method to fabricate high‐performance QOSCs by using “multiple‐birth‐acceptor” (MBA), a mixture of three molecules synthesized simultaneously. These A‐DA'D‐A type MBAs ( MBA31 , MBA11 , MBA13, and MBA19 ) were synthesized by reacting one DA'D‐type central segment (BTP‐2CHO) with two A terminal units (γ‐IC‐Cl and IC‐2Cl) with different feed ratios (γ‐IC‐Cl: IC‐2Cl = 3:1, 1:1, 1:3, and 1:9). Without the need to isolate individual components, these MBAs can be utilized directly as electron acceptor to fabricate QOSCs. Compared with binary and ternary devices, QOSCs based on PM6: MBAs exhibit dramatically improved PCEs. Further device optimization, by using 2PACz as hole transport layer and DIB as an additive, PM6:MBA13‐ based device achieves a state‐of‐the‐art PCE of 20.10%, among the highest values reported for QOSCs to date. Obviously, this method simplifies the material synthesis and device fabrication process for QOSCs. This study provides a feasible method to synthesize MBAs and subsequently fabricate high‐performance QOSCs, and thereby opens up a new venue for the further optimization of OSCs.