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Steering the evolution of single spin systems is crucial for quantum computing and quantum sensing.The dynamics of quantum systems has been theoretically investigated with parity-time–symmetric Hamiltonians exhibiting exotic properties. Although parity-time symmetry has been explored in classical systems, its observation in a single quantum system remains elusive.We developed amethod to dilate a general parity-time–symmetric Hamiltonian into a Hermitian one.The quantum state evolutions ranging from regions of unbroken to broken PT symmetry have been observed with a single nitrogen-vacancy center in diamond.Owing to the universality of the dilation method, our result provides a route for further exploiting and understanding the exotic properties of parity-time symmetric Hamiltonian in quantum systems.

Exceptional points (EPs) are singularities in non-Hermitian systems, where k ( k  ≥ 2) eigenvalues and eigenstates coalesce. High-order EPs exhibit richer topological characteristics and better sensing performance than second-order EPs. Theory predicts even richer non-Hermitian topological phases for high-order EP geometries, such as lines or rings formed entirely by high-order EPs. However, experimental exploration of high-order EP geometries has hitherto proved difficult due to the demand for more degrees of freedom in the Hamiltonian’s parameter space or a higher level of symmetries. Here we observe a third-order exceptional line in an atomic-scale system. To this end, we use a nitrogen-vacancy spin in diamond and introduce multiple symmetries in the non-Hermitian Hamiltonian realized with the system. Furthermore, we show that the symmetries play an essential role in the occurrence of high-order EP geometries. Our approach can in future be further applied to explore high-order EP-related topological physics at the atomic scale and, potentially, for applications of high-order EPs in quantum technologies. As singularities in non-Hermitian systems, exceptional points exhibit rich topological characteristics and have potential for sensing applications. Now, a nitrogen-vacancy spin in diamond exhibits a third-order exceptional line upon the introduction of multiple symmetries in the non-Hermitian Hamiltonian of the spin system.

High-pressure diamond anvil cells have been widely used to create novel states of matter. Nevertheless, the lack of universal in-situ magnetic measurement techniques at megabar pressures makes it difficult to understand the underlying physics of materials’ behavior at extreme conditions, such as high-temperature superconductivity of hydrides and the formation or destruction of the local magnetic moments in magnetic systems. Here, we break through the limitations of pressure on quantum sensors by modulating the uniaxial stress along the nitrogen-vacancy axis and develop the in-situ magnetic detection technique at megabar pressures with high sensitivity ( ~ 1 μ T / Hz ) and sub-microscale spatial resolution. By directly imaging the magnetic field and the evolution of magnetic domains, we observe the macroscopic magnetic transition of Fe 3 O 4 in the megabar pressure range from ferrimagnetic ( α -Fe 3 O 4 ) to weak ferromagnetic ( β -Fe 3 O 4 ) and finally to paramagnetic ( γ -Fe 3 O 4 ). The scenarios for magnetic changes in Fe 3 O 4 characterized here shed light on the direct magnetic microstructure observation in bulk materials at high pressure and contribute to understanding magnetism evolution in the presence of numerous complex factors such as spin crossover, altered magnetic interactions and structural phase transitions. The study of magnetic-related phenomena under high-pressure conditions currently presents significant challenges. The authors develop an in-situ magnetic imaging technique at megabar pressures, revealing the magnetic transition of magnetite.

Objectives The upper respiratory tract flora may influence host immunity and modulate susceptibility to viral respiratory infections. This study aimed to investigate the associations between upper respiratory tract flora and immune cells in severe ILI, identify specific microbial taxa and immune response pathways contributing to disease severity, and elucidate how flora influences ILI progression by modulating immune cell functions. Methods Heritability of GWAS summary data was estimated using LDSC (v1.0.1). Gene-level genetic associations were analyzed with MAGMA. scRNA-seq data were integrated with genetic association data using scDRS. FUSION was used to construct cell type-specific expression quantitative trait locus models based on genotypes and scRNA-seq data from the onek1k project, which were combined with flora abundance-related GWAS data for a transcriptome-wide association study. Results From the LDSC analysis, data from 1195 severe ILI-associated GWASs with upper respiratory flora(h2 > 0.1) were included in subsequent analysis. TWAS identified 19 significant association pairs ( P adj  < 0.05), and 1226 differentially expressed genes between mild and severe ILI patients ( P adj  < 0.05 and | log 2 FC|>0.25). Functional enrichment analyses using GO, KEGG, and Reactome databases revealed that immune cells,such as CD4 + T effector memory cells, cDCs, NK cells, were enriched in multiple biological processes or pathways. Conclusions This study identified associations between severe ILI-related upper respiratory tract flora and cell type-specific gene expression, potentially explaining how differential flora influences ILI progression. CD16 + monocytes exhibited the most differentially expressed genes, followed by proliferating cells and cDCs, highlighting the significant role of immune cell-enriched pathways in ILI progression.

Background Socioeconomic status (SES) inequity was recognized as a driver of some certain infectious diseases. However, few studies evaluated the association between SES and the burden of overall infections, and even fewer identified preventable mediators. This study aimed to assess the association between SES and overall infectious diseases burden, and the potential roles of factors including lifestyle, environmental pollution, chronic disease history. Methods We included 401,009 participants from the UK Biobank (UKB) and defined the infection status for each participant according to their diagnosis records. Latent class analysis (LCA) was used to define SES for each participant. We further defined healthy lifestyle score, environment pollution score (EPS) and four types of chronic comorbidities. We used multivariate logistic regression to test the associations between the four above covariates and infectious diseases. Then, we performed the mediation and interaction analysis to explain the relationships between SES and other variables on infectious diseases. Finally, we employed seven types of sensitivity analyses, including considering the Townsend deprivation index as an area level SES variable, repeating our main analysis for some individual or composite factors and in some subgroups, as well as in an external data from the US National Health and Nutrition Examination Survey, to verify the main results. Results In UKB, 60,771 (15.2%) participants were diagnosed with infectious diseases during follow-up. Lower SES [odds ratio ( OR ) = 1.5570] were associated with higher risk of overall infections. Lifestyle score mediated 2.9% of effects from SES, which ranged from 2.9 to 4.0% in different infection subtypes, while cardiovascular disease (CVD) mediated a proportion of 6.2% with a range from 2.1 to 6.8%. In addition, SES showed significant negative interaction with lifestyle score ( OR  = 0.8650) and a history of cancer ( OR  = 0.9096), while a significant synergy interaction was observed between SES and EPS ( OR  = 1.0024). In subgroup analysis, we found that males and African (AFR) with lower SES showed much higher infection risk. Results from sensitivity and validation analyses showed relative consistent with the main analysis. Conclusions Low SES is shown to be an important risk factor for infectious disease, part of which may be mediated by poor lifestyle and chronic comorbidities. Efforts to enhance health education and improve the quality of living environment may help reduce burden of infectious disease, especially for people with low SES.

Histological imaging is essential for the biomedical research and clinical diagnosis of human cancer. Although optical microscopy provides a standard method, it is a persistent goal to develop new imaging methods for more precise histological examination. Here, we use nitrogen-vacancy centers in diamond as quantum sensors and demonstrate micrometer-resolution immunomagnetic microscopy (IMM) for human tumor tissues. We immunomagnetically labeled cancer biomarkers in tumor tissues with magnetic nanoparticles and imaged them in a 400-nm resolution diamond-based magnetic microscope. There is barely magnetic background in tissues, and the IMM can resist the impact of a light background. The distribution of biomarkers in the high-contrast magnetic images was reconstructed as that of the magnetic moment of magnetic nanoparticles by employing deep-learning algorithms. In the reconstructed magnetic images, the expression intensity of the biomarkers was quantified with the absolute magnetic signal. The IMM has excellent signal stability, and the magnetic signal in our samples had not changed after more than 1.5 y under ambient conditions. Furthermore, we realized multimodal imaging of tumor tissues by combining IMM with hematoxylin-eosin staining, immunohistochemistry, or immunofluorescence microscopy in the same tissue section. Overall, our study provides a different histological method for both molecular mechanism research and accurate diagnosis of human cancer.

Satellite remote sensing precipitation products with high temporal–spatial resolution and large area coverage have great potential in hydrometeorological research. This paper analyzes the performance of four satellite products from 2000 to 2008 in the Yarlung Zangbo River Basin, namely the Tropical Rainfall Measuring Mission (TRMM), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), and Climate Prediction Center morphing method (CMORPH). The four products are evaluated from three aspects: spatial distribution, temporal characteristics, and hydrological simulation. The results show that: (1) the four products exhibit similar annual and daily precipitation patterns, with the highest daily precipitation accuracy concentrated in the center, followed by the east and west; (2) TRMM, CHIRPS, and CMORPH exhibit the largest positive bias for monthly precipitation estimation in December, while PERSIANN shows the largest positive bias in July. All products overestimate the precipitation of 0.1–5 mm/d, and underestimate the precipitation above 5 mm/d, especially for PERSIANN; (3) certain Products tend to perform better than others at elevations of 3000–4000 m and in relatively humid zones. TRMM shows relatively stable performance for various elevation and climate zones; (4) for hydrological model validation, TRMM has the best performance during the calibration period, although it is inferior to CHIRPS during the validation period. Overall, TRMM has the highest applicability in the Yarlung Zangbo River Basin; however, its impact on the uncertainty of hydrological modeling needs to be further studied.

Background The polygenic score (PGS) is an estimate of an individual’s genetic susceptibility to a specific complex trait and has been instrumental to the development of precision medicine. As an increasing number of genome-wide association studies (GWAS) have emerged, numerous sophisticated statistical and computational methods have been developed to facilitate the PGS construction. However, both the complex statistical estimation procedure and the various data formats of summary statistics and reference panel make the PGS calculation challenging and not easily accessible to researchers with limited statistical and computational backgrounds. Results Here, we propose PGSFusion, a webserver designed to carry out PGS construction for targeting variety of analytic requirements while requiring minimal prior computational knowledge. Implemented with well-established web development technologies, PGSFusion streamlines the construction of PGS using 17 PGS methods in four categories: 11 single-trait, one multiple-trait, two annotation-based and three cross-ancestry based methods. In addition, PGSFusion also utilizes UK Biobank data to provide two kinds of in-depth analyses for 201 complex traits: i) prediction performance evaluation to display the consistency between PGS and specific traits and the effect size of PGS in different genetic risk groups; ii) joint effect analysis to investigate the interaction between PGS and covariates, as well as the effect size of covariates in different genetic subgroups. PGSFusion benchmarks the prediction performances for different methods in one summary statistics. PGSFusion automatically identifies the required parameters in different data formats of uploaded GWAS summary statistics files, provides a selection of suitable methods, and outputs calculated PGSs and their corresponding epidemiological results. Finally, we showcase three case studies in different application scenarios, highlighting its versatility and values to researchers. Conclusions Overall, PGSFusion presents an easy-to-use, effective, and extensible platform for PGS construction, promoting the accessibility and utility of PGS for researchers in the field of precision medicine. PGSFusion is freely available at http://www.pgsfusion.net/ .

Electron spin resonance (ESR) spectroscopy has broad applications in physics, chemistry, and biology. As a complementary tool, zero-field ESR (ZF-ESR) spectroscopy has been proposed for decades and shown its own benefits for investigating the electron fine and hyperfine interaction. However, the ZF-ESR method has been rarely used due to the low sensitivity and the requirement of much larger samples than conventional ESR. In this work, we present a method for deploying ZF-ESR spectroscopy at the nanoscale by using a highly sensitive quantum sensor, the nitrogen vacancy center in diamond. We also measure the nanoscale ZF-ESR spectrum of a few P1 centers in diamond, and show that the hyperfine coupling constant can be directly extracted from the spectrum. This method opens the door to practical applications of ZF-ESR spectroscopy, such as investigation of the structure and polarity information in spin-modified organic and biological systems. Demonstrations of sensing devices using nitrogen vacancy centres have shown significantly improved sensitivity compared to traditional methods. Here the authors demonstrate an approach for performing nanoscale electron spin resonance without magnetic fields in order to achieve better spectral resolution.

Electrical stimulation of the brain has shown promising prospects in treating various brain diseases. Although biphasic pulse stimulation remains the predominant clinical approach, there has been increasing interest in exploring alternative stimulation waveforms, such as sinusoidal stimulation, to improve the effectiveness of brain stimulation and to expand its application to a wider range of brain disorders. Despite this growing attention, the effects of sinusoidal stimulation on neurons, especially on their nonlinear firing characteristics, remains unclear. To address the question, 50 Hz sinusoidal stimulation was applied on Schaffer collaterals of the rat hippocampal CA1 region . Single unit activity of both pyramidal cells and interneurons in the downstream CA1 region was recorded and analyzed. Two fractal indexes, namely the Fano factor and Hurst exponent, were used to evaluate changes in the long-range correlations, a manifestation of nonlinear dynamics, in spike sequences of neuronal firing. The results demonstrate that sinusoidal electrical stimulation increased the firing rates of both pyramidal cells and interneurons, as well as altered their firing to stimulation-related patterns. Importantly, the sinusoidal stimulation increased, rather than decreased the scaling exponents of both Fano factor and Hurst exponent, indicating an increase in the long-range correlations of both pyramidal cells and interneurons. The results firstly reported that periodic sinusoidal stimulation without long-range correlations can increase the long-range correlations of neurons in the downstream post-synaptic area. These results provide new nonlinear mechanisms of brain sinusoidal stimulation and facilitate the development of new stimulation modes.