Browse Articles

Moisture-tolerant Mg-metal electrodes for practical fabrication of rechargeable Mg batteries

Abstract Despite striking advantages in terms of cost and safety, penetration of rechargeable Mg batteries into the commercial market is still hampered by major technical challenges, including intrinsic hypersensitivity of Mg metal to moisture, which readily forms a compact ion-insulating film on the surface. To unlock this critical constraint, a moisture-tolerant Mg electrode is developed that is capable of efficient Mg plating-stripping even in the highly moist electrolytes. Here we show that short immersion of Mg metal in trimethyl phosphate creates a sacrificial protection layer containing dimethyl magnesium in magnesium dimethyl phosphate, which synergistically scavenges water molecules from the electrolytes instantly, enabling manufacturing of Mg-ion cells under moist and/or atmospheric conditions. This simple and scalable strategy provides a practical route to reducing the manufacturing costs of rechargeable Mg batteries, thereby expediting their early commercialization.

Politics matter more than credentials in laypeople’s judgments of expertise

Abstract We explored the cues laypeople use to determine who is an expert on a given topic. In Study 1 ( n  = 208), we collected participants’ self-reports of cues they consider important when evaluating a putative expert. Across various topics, participants rated good cues (e.g., relevant degree, more experience) as more important for expertise while disregarding poor or superficial cues (e.g., appearance). In Study 2 ( n  = 498), we conducted a conjoint experiment where we manipulated several cues of expertise in biographies of hypothetical experts. In line with the self-reports, good cues had the strongest effects on trust. In Study 3 ( n =  1,776), we examined whether participants would still recognize good cues when they received information about the expert’s political views. Using a highly politicized topic—abortion—we manipulated the expert’s views along with their credentials. Participants trusted likeminded experts more, and the effect of the expert’s views on participants’ trust was more than twice as large as the effect of credentials. Our results paint a complicated picture, where laypeople know what qualities to look for in experts but attend to political information more readily than to good cues of expertise.

Dual phagocytosis-checkpoint blockade revitalizes immune surveillance in mouse models of glioblastoma

Molecular structure and thermal decomposition kinetics of kerogen from the Paleocene oil-shale facies in the Bikaner–Nagaur Basin, western India

CAMPER: mechanistic artificial intelligence for designing peptides that target MRSA persisters

Enabling Rotated Stacking Displacement in Two‐Dimensional Covalent Organic Frameworks via Interlayer Electrostatic Repulsion

ABSTRACT Tuning the interlayer stacking in 2D covalent organic frameworks (2D COFs) allows unique structural and optoelectronic properties. However, the diversity of 2D COF stacking modes is limited to eclipsed, serrated, and shifted stacking. In this study, we develop a method for constructing COFs with rotated stacking by modulating interlayer electrostatic repulsion. COFs with rotated or eclipsed (AA) stacking are obtained via reactions between triamine and dialdehyde monomers with or without pyridinium substituents. Importantly, the modulation of pyridinium substituents enables the transformation of different stacking modes, as well as the conversion of amorphous to crystalline materials. Moreover, multicomponent‐based stacking regulation strategies are found to efficiently mediate photocatalytic hydrogen peroxide production, owing to their tunable photophysical properties. Our findings provide perspectives on leveraging interlayer repulsion to tailor interlayer stacking in 2D COFs, thereby diversifying their topologies and improving their optoelectronic properties.

Reformulated predictive torque and flux control with a full-order adaptive observer and accurate discrete-time models for sensorless induction machine drives

Abstract In this paper, we present a reformulation of both the predictive torque and flux control (PTC) scheme and the full-order adaptive observer (FAO) for induction machine drives. The proposed approach is based on a state-space representation expressed exclusively in terms of stator current and stator flux linkage, simplifying the observer structure and removing the explicit dependence on rotor flux variables found in conventional sensorless formulations. This representation is consistently applied within both the FAO and PTC frameworks, and second- and higher-order discrete-time models are derived using Taylor- and Runge–Kutta–based methods to enhance numerical accuracy and dynamic performance. The resulting FAO–PTC scheme is validated through Hardware-in-the-Loop simulations, demonstrating steady-state performance comparable to conventional designs, faster transient response, improved dynamic behaviour, and a reduced state-space order, albeit with slightly higher computational cost. Notably, simply employing a more accurate observer substantially enhances the performance of the sensorless scheme. Among the evaluated discretization strategies, the Taylor-based model provides the highest steady-state accuracy and fastest convergence, with only a modest increase in torque ripple. Overall, the proposed reformulated FAO–PTC framework achieves a balanced trade-off between accuracy, implementation simplicity, and computational efficiency for real-time sensorless induction machine drives.

Compact mid-infrared fiber probe for in vivo multi-compound monitoring demonstrated using ex vivo human skin

Persistent Mono‐Oxo Bonding with Protactinium(V) Revealed in Highly Acidic Chloride Solutions

Abstract Protactinium is one of those long discovered elements with poorly known physico‐chemical properties. In aqueous solution, protactinium(V), highly prone to hydrolysis, may or may not display oxo bonding, depending on the medium, in a way that still appears unpredictable due to a critical lack of data. Here, we probe the stability of this bond in hydrochloric acid solutions. Extended X‐ray absorption fine structure (EXAFS) and X‐ray absorption near‐edge structure (XANES) spectroscopy, complemented by ab initio calculations, reveal that a short Pa─O oxo bond indeed exists at moderate hydrochloric acid concentration 3 M and unexpectedly persists even in highly acidic conditions (12 M). Our analysis identifies the coexistence of PaO(OH)Cl 1, 2 species at moderate acidity and PaOCl 4, 5 species at high acidity, with both pairs unambiguously displaying the characteristic mono‐oxo bond, with a total coordination number of seven. Notably, EXAFS spectral fitting using geometries obtained from relativistic quantum calculations reveals a Pa─O oxo bond length of approximately 1.83 Å, in excellent agreement with computational predictions. This finding overturns expectations and provides new insight into early actinide bonding behavior in extreme chemical conditions. Understanding such coordination chemistry is critical for advancing nuclear fuel management and more broadly actinide science.

Research on target detection algorithm for forest fire images based on multi-scale feature extraction

Kibble-Zurek mechanism and beyond in a holographic superfluid disk

Artificial intelligence-based intrusion detection and secure communication model for sustainable 6G-IoT networks

Residential green space, air pollution, and related metabolites in association with depression among cancer survivors

Abstract The association of natural environmental exposure and air pollution with depression incidence among cancer survivors, as well as the potential role of plasma metabolomics, remains unclear. Here, we analyze 21,507 cancer survivors from the UK Biobank over a median follow-up of 12.39 years and find that individuals exposed to higher levels of green space and natural environment (tertile 3 vs. tertile 1) within a 1000-m buffer have 15.8% (95% CI: 4.0%-26.1%) and 18.2% (95% CI: 7.0%-28.1%) lower risks of depression, respectively. The strongest protective association is observed among breast cancer survivors. In contrast, higher exposures to nitrogen dioxide and nitrogen oxides are associated with an increased risk of depression. Meanwhile, plasma metabolic signatures associated with green space and natural environment may partially mediate these associations. These findings highlight that residential green space, natural environment, and lower air pollution levels may reduce depression risk among cancer survivors, possibly via metabolic pathways.

Pilot degradation study of gamma irradiated ciprofloxacin in its primary packaging material for space pharmaceutical applications

Selective control of prefrontal neural timescales by parietal cortex

Abstract The frontal eye field (FEF) and posterior parietal cortex (PPC) are key hubs of the dorsal attention network, yet how parietal inputs shape prefrontal circuit temporal dynamics and attentional computations remains largely unknown. We measured intrinsic timescales of FEF neurons in male rhesus macaques and examined their changes during PPC inactivation. We observed two distinct classes of FEF neurons based on their intrinsic timescales: short-timescale neurons (~25 ms) and long-timescale neurons (~100 ms). Short-timescale neurons showed stronger transient visual responses, suggesting a role in rapid visual processing. In contrast, long-timescale neurons exhibited stronger sustained salience representation, suggesting a role in spatiotemporal integration to maintain stimulus-driven attention. During PPC inactivation, intrinsic timescales increased in both neuron types, with a substantially larger effect in short-timescale neurons. In addition, PPC inactivation selectively disrupted salience computation, particularly in long-timescale neurons. These findings provide causal evidence linking intrinsic local neural timescales to long-range inter-area communication and indicate the presence of at least two distinct network motifs that support different neuronal dynamics and functional computations within the FEF.

The association between serum follicle-stimulating hormone and luteinizing hormone levels and congestive heart failure in postmenopausal women: a cross-sectional study

Purkinje cell intrinsic activity shapes cerebellar development and function

Abstract The emergence of functional cerebellar circuits is heavily influenced by activity-dependent processes. However, the contribution of intrinsic Purkinje cell activity to cerebellar development remains less understood. Here, we demonstrate that before synaptic networks mature, Purkinje cell intrinsic activity is essential for regulating dendritic growth, establishing connections with cerebellar nuclei, and ensuring proper cerebellar function. Disrupting this activity during the postnatal period impairs motor function, with earlier perturbations causing more severe deficits. Importantly, only early developmental disruptions lead to pronounced defects in cellular morphology, highlighting key temporal windows for dendritic growth and maturation. Transcriptomic analyses reveal that early intrinsic activity drives the expression of activity-dependent genes, including Prkcg and Car8 , which are essential for dendritic development. Our findings emphasize the importance of temporally regulated intrinsic activity in Purkinje cells in guiding cerebellar circuit development, providing a potential unifying mechanism underlying cerebellum-associated disorders.

Genomic dissection of iron toxicity tolerance in rice identifies key loci, candidate genes, and associated haplotypes

Abstract Rice ( Oryza sativa L.) is known for its inherent tolerance to highly acidic soils, yet the underlying genetic and physiological mechanisms, particularly for iron (Fe) toxicity tolerance, remain insufficiently characterised. Although several quantitative trait loci (QTLs) and candidate genes (CGs) associated with Fe-toxicity tolerance have been identified, their fine mapping is unresolved. In this study, we performed a meta-QTL (M-QTL) analysis by integrating data from 11 QTL mapping studies and nine genome-wide association studies (GWAS), resulting in 63 M-QTLs with a minimum cluster size of two. The largest cluster comprised 10 QTLs, with an average cluster size of 4.01. Phenotypic variance explained (R 2 ) ranged from 7% to 31% (mean 11.77%), and the average confidence interval (CI) was reduced from 4.68 to 2.12. Gene retrieval within these M-QTL regions identified 4,070 non-redundant genes. Comparison with 5 Fe-toxicity-related transcriptomic datasets revealed 897 differentially expressed genes, of which 284 were common to at least two datasets and designated as CGs. Characterisation of these CGs identified key regulatory elements, transcription factors, and transporters implicated in Fe tolerance. Notable CGs included OsNRAMP6 , OsCDAP1 , OsFRO2 , OsFRDL2 , OsPT2 , OsPDR9 , OsHSP70 , OsACS2 , OsZIP8 , OsWRKY46 , OsTIP2;2 , OsGSTU17 , OsINH2 , and OsPEZ1 . Association analysis identified 13 novel marker–trait associations (MTAs), and haplotype analysis revealed nine haplotypes (H001–H009). M-QTL1.6 and M-QTL7.3 were characterised by large QTL clusters and multiple candidate genes, while M-QTL10.1 contained an Fe-tolerance–associated haplotype within OsFRDL2 . Key MTAs (MTA8, MTA16, MTA19, MTA24) formed central nodes in protein–protein interaction networks. This study identifies stable M-QTLs and favourable haplotypes associated with Fe toxicity tolerance in rice, offering clear genomic targets that regulate plant growth under excess iron stress.

Nitrogen fixation in a non-equilibrium spatially distributed electric field

Data-driven design of LNA-blockers for efficient contaminant removal in Ribo-Seq libraries

Abstract Ribo-Seq libraries often contain highly abundant non-coding RNA contaminants, which are challenging to remove due to their high sequence variability and diverse fragmentation patterns. We present an organism-independent computational pipeline that identifies experiment-specific target sequences and enables their efficient depletion using custom-tailored LNA probes in a single pipetting step. We demonstrate that LNA-based depletion is most effective during library amplification and has no effect on gene-level quantification. Contaminant depletion in Arabidopsis libraries nearly doubled the yield of coding reads, significantly improving cost-effectiveness.