Browse Articles

Vacancies in sulfides facilitate fluid-induced solid-state diffusion and critical metals accumulation

Engineering anisotropic electrodynamics at the graphene/CrSBr interface

Abstract Graphene is a privileged 2D platform for hosting confined light-matter excitations known as surface plasmon polaritons (SPPs), as it possesses low intrinsic losses and a high degree of optical confinement. However, the isotropic nature of graphene limits its ability to guide and focus SPPs, making it less suitable than anisotropic elliptical and hyperbolic materials for polaritonic lensing and canalization. Here, we present graphene/CrSBr as an engineered 2D interface that hosts highly anisotropic SPP propagation across mid-infrared and terahertz energies. Using scanning tunneling microscopy, scattering-type scanning near-field optical microscopy, and first-principles calculations, we demonstrate mutual doping in excess of 1013 cm–2 holes/electrons between the interfacial layers of graphene/CrSBr. SPPs in graphene activated by charge transfer interact with charge-induced electronic anisotropy in the interfacial doped CrSBr, leading to preferential SPP propagation along the quasi-1D chains that compose each CrSBr layer. This multifaceted proximity effect both creates SPPs and endows them with anisotropic propagation lengths that differ by an order-of-magnitude between the in-plane crystallographic axes of CrSBr.

Forcing mechanisms of the half-precession cycle in the western equatorial Pacific temperature

Immune checkpoint inhibitors plus debulking surgery for patients with metastatic renal cell carcinoma: clinical outcomes and immunological correlates of a prospective pilot trial

Exploring the principles behind antibiotics with limited resistance

Abstract Antibiotics that target multiple cellular functions are anticipated to be less prone to bacterial resistance. Here we hypothesize that while dual targeting is crucial, it is not sufficient in preventing resistance. Only those antibiotics that simultaneously target membrane integrity and block another cellular pathway display reduced resistance development. To test the hypothesis, we focus on three antibiotic candidates, POL7306, Tridecaptin M152-P3 and SCH79797, all of which fulfill the above criteria. Here we show that resistance evolution against these antibiotics is limited in ESKAPE pathogens, including Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii and Pseudomonas aeruginosa, while dual-target topoisomerase antibiotics are prone to resistance. We discover several mechanisms restricting resistance. First, de novo mutations result in only a limited elevation in resistance, including those affecting the molecular targets and efflux pumps. Second, resistance is inaccessible through gene amplification. Third, functional metagenomics reveal that mobile resistance genes are rare in human gut, soil and clinical microbiomes. Finally, we detect rapid eradication of bacterial populations upon toxic exposure to membrane targeting antibiotics. We conclude that resistance mechanisms commonly found in natural bacterial pathogens provide only limited protection to these antibiotics. Our work provides guidelines for the future development of antibiotics.

Ab initio quantum many-body description of superconducting trends in the cuprates

Sub-femtomolar drug monitoring via co-calibration mechanism with nanoconfined DNA probes

Abstract Synthetic drugs fundamentally reshape the illicit drug market due to their low cost, ease of production, and rapid manufacturing processes. However, current drug detection methods, which rely on complex instruments, have limited applicability and often neglect the influence of pH fluctuations, leading to potential bias and unreliable results. Herein, we propose co-calibration DNA probes on a nanoconfined biosensor (N C B S ), covering the range of sweat pH 3–8 to achieve significantly enhanced target signal recognition. The N C B S exhibits a linear response range of 10 3 -10 8 fM with a low limit of detection (LOD) of 3.58 fM in artificial sweat. Compared to the single-aptamer N C B S , the dual-aptamer N C B S offers a broader linear response range, primarily due to the synergistic effects of changes in surface wettability and the capture of hydrion, which together reduce signal interference in proton transport. The linear response range doubles, and its detection sensitivity improves by 4–5 orders of magnitude compared to existing drug detection methods. This sensing strategy expands the application scope of aptamer-based composite probes, offering an approach for ultra-sensitive drug detection and demonstrating significant potential in sweat sensing and drug monitoring fields.

Oral delivery of therapeutic proteins by engineered bacterial type zero secretion system

Author Correction: Fully addressable designer superstructures assembled from one single modular DNA origami

Polymeric ionic liquid promotes acidic electrocatalytic CO2 conversion to multicarbon products with ampere level current on Cu

A comprehensive multicriteria decision analysis framework for shallow geothermal energy suitability evaluation in Yinchuan Area, China

Association between gallbladder disease and colorectal neoplasia: a meta-analysis

Association between current relative fat mass and history of female infertility based on the NHANES survey

Exploring the determinants of mathematics teachers’ willingness to implement STEAM education using structural equation modeling

Multiple color images security by SPN over the residue classes of Gaussian integer $$\:Z{\left[i\right]}_{h}$$

SiO2 nanoparticles as disruptors of endogenous resolution mechanisms of inflammatory responses that exacerbate pneumonia

Low-frequency tremor-like episodes before the 2023 MW 7.8 Türkiye earthquake linked to cement quarrying

Abstract Recent advances in artificial intelligence have enhanced the detection and identification of transient low-amplitude signals across the entire frequency spectrum, shedding light on deformation processes preceding natural hazards. This study investigates low-frequency, low-amplitude signals preceding the 2023 M W 7.8 Kahramanmaraş earthquake in Türkiye. Using a deep neural network, we extract key features from the spectrograms of continuous seismic signals and employ unsupervised clustering to reveal distinct transient patterns. We identify an increased occurrence of low-frequency tremor-like signals during the six months preceding the mainshock. However, the location of these signals suggests that their origin is not tectonic, but rather related to anthropogenic activities at cement plants along the Narlı Fault, where the M W 7.8 mainshock nucleated. Such findings highlight the importance of understanding the origin of patterns detected by machine-learning methods and the large variety of seismic signals due to anthropogenic activities. Furthermore, the search for the origin of the tremor-like signals motivated an investigation into the local seismicity around the Narlı Fault. The resulting extended seismicity catalog suggests that seismicity in this area arises from a combination of tectonic and anthropogenic processes.

Impact of using oral spherical carbon adsorbent in predialysis chronic kidney disease period on cardiovascular outcome after dialysis therapy

A novel lightweight multi-scale feature fusion segmentation algorithm for real-time cervical lesion screening

Optimizing spatial normalization of multisubject inner ear MRI: comparison of different geometry-preserving co-registration approaches

Abstract Spatial normalization of multisubject inner ear imaging data is challenging, due to both substantial intraindividual differences and the small size of the organ compared to other intracranial structures. Automatic whole brain co-registration to standard space can only roughly co-align the peripheral vestibular endorgan, and complemental manual registration is highly time-consuming. Here, we compared the accuracy of four geometry-maintaining co-registration methods (one semi-manual method and three automatic methods). High-resolution structural T2-MRI of 153 inner ears from patients and healthy participants were co-registered to an inner-ear atlas. The semi-manual method used a three-point landmark-based approach (3P), two automatic methods were based on unassisted standard algorithms (Advanced Normalization Tools (ANTs), Elastix (EL)), while the fourth automatic method utilized a volumetrically dilated, atlas-based mask (thick inner ear, TIE) for probabilistic inner ear masking. Registration accuracy was evaluated by neurotologists blinded to the respective registration paradigm, and the resulting median volumes were quantified using colocalization analyses. The mask-aided automatic approach showed the best ratings, followed by the semi-manual three-point landmark-based registration (mean ratings (lower: better) TIE 2.21 ± 1.15; 3P 2.58 ± 0.61; EL 3.42 ± 1.06; ANTs 3.49 ± 1.26). The semi-manual method had the lowest rate of insufficient registrations, followed by TIE (3P: 3.70%; TIE: 8.28%; EL: 22.66%; ANTs: 27.02%). TIE showed the highest colocalization metrics with the atlas. Only TIE and 3P allowed for sufficient semicircular canal visualization in method-wise average volumes. Overall, geometry-preserving spatial normalization of multisubject inner ear imaging data is possible and could allow groupwise examinations of the bony labyrinth or temporal bone morphology in the future.