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Background Diagnosing seronegative rheumatoid arthritis (RA) can be challenging due to complex diagnostic criteria. We sought to discover diagnostic biomarkers for seronegative RA cases by studying metabolomic and lipidomic changes in RA patient serum. Methods We performed comprehensive metabolomic and lipidomic profiling in serum of 225 RA patients and 100 normal controls. These samples were divided into a discovery set (n = 243) and a validation set (n = 82). A machine-learning-based multivariate classification model was constructed using distinctive metabolites and lipids signals. Results Twenty-six metabolites and lipids were identified from the discovery cohort to construct a RA diagnosis model. The model was subsequently tested on a validation set and achieved accuracy of 90.2%, with sensitivity of 89.7% and specificity of 90.6%. Both seropositive and seronegative patients were identified using this model. A co-occurrence network using serum omics profiles was built and parsed into six modules, showing significant association between the inflammation and immune activity markers and aberrant metabolism of energy metabolism, lipids metabolism and amino acid metabolism. Acyl carnitines (20:3), aspartyl-phenylalanine, pipecolic acid, phosphatidylethanolamine PE (18:1) and lysophosphatidylethanolamine LPE (20:3) were positively correlated with the RA disease activity, while histidine and phosphatidic acid PA (28:0) were negatively correlated with the RA disease activity. Conclusions A panel of 26 serum markers were selected from omics profiles to build a machine-learning-based prediction model that could aid in diagnosing seronegative RA patients. Potential markers were also identified in stratifying RA cases based on disease activity.

Elasticity, featured by a recoverable strain, refers to the ability that materials can return to their original shapes after deformation. Typically, the elastic strains of most metals are well‐known 0.2%. In shape memory alloys and high entropy alloys, the elastic strains can be several percent, as called superelasticity, which are all triggered by external stresses. A superelasticity induced by magnetic field, termed as magneto‐superelasticity, is extremely important for contactless work of materials and for developing brand‐new large stroke actuators and high efficiency energy transducers. In magnetic shape memory alloys, the twin boundary motion driven by magnetic field can output a strain of several percent. However, this strain is unrecoverable when removing the magnetic field and hence it is not magneto‐superelasticity. Here, a giant magneto‐superelasticity of 5% in a Ni34Co8Cu8Mn36Ga14 single crystal is reported by introducing arrays of ordered dislocations to form preferentially oriented martensitic variants during the magnetically induced reverse martensitic transformation. This work provides an opportunity to achieve high performance in functional materials by defect engineering. Ordered dislocations are introduced into a Ni34Cu8Co8Mn36Ga14 single crystal to effectively control the preferential orientation of martensitic variants during cycles of magnetic field induced reverse martensitic transformation. A giant magneto‐superelasticity of 5% is realized. This work provides an opportunity to develop advanced superelastic materials and related high performance devices.

As one of the most prolific atomic bomb writers in Japan, Hayashi Kyōko’s oeuvre demonstrates the ongoing negotiation of her positionality in relation to the hibakusha identity. Adopting a psychoanalytic framework to interpret her narratives, this paper divides Hayashi’s four-decade-long writing career into three stages and closely examines representative works from each phase. Her early writings heavily focus on her past experiences surviving the bombing, fulfilling a cathartic need. In the transitional stage, Hayashi undergoes a symbolic pilgrimage around and beyond her hibakusha self, leading to her ‘self’-less final works dedicated to conveying antinuclear messages to a general audience. Despite the rich dynamics, Hayashi Kyōko’s works remain underexplored in the English-speaking world. Nevertheless, as we continue to live in the nuclear era, the genre of atomic bomb literature warrants further interpretation.

Polymers are composed of many smaller units connected by covalent bonds, with higher molecular weight and larger molecular structure. Due to their economical efficiency and easy modification, researchers have discovered the potential of polymers as the flotation reagent in mineral processing, including the roles of depressant, flocculant, and frother. This paper provides a comprehensive review of the utilization of polymers in mineral flotation, emphasizing their current applications and mechanistic investigations. The study categorizes polymers into three types: natural polymers, modified polymers, and synthesized polymers. Detailed discussions include the polymers structures, functional properties, adsorption mechanisms and specific application examples of each reagent are shown in the main text, which will provide a vital reference for the development of highly efficient and environmentally friendly reagents in mineral flotation.

High gradient magnetic separation is widely used in magnetic minerals upgrading, and its separation performance is significant depending on the parameters. In this investigation, the Mathematical model of the plate high gradient magnetic separator is established, the magnetic induction and the flow field distribution are investigated based on the COMSOL multi-physical simulation, and then the separation efficiency and TiO2 grade are analyzed using the plate high gradient magnetic separator. Additionally, the key factors affecting the efficiency of mineral separation are detailed in the experimental separation, the separation efficiency is demonstrated and its feasibility is verified by experiments. It is founded that the mathematical model and simulation results are basically validated by the experimental separation process, and the TiO2 grade can be effectively upgraded from 5.2% to 11.5% with the rinsing water consumption 9.5 L/min and the belt rotating speed 2 r/min. It is thus concluded that plate high gradient magnetic separator has provided an effective way in upgrading ilmenite quality.

Elasticity, featured by a recoverable strain, refers to the ability that materials can return to their original shapes after deformation. Typically, the elastic strains of most metals are well‐known 0.2%. In shape memory alloys and high entropy alloys, the elastic strains can be several percent, as called superelasticity, which are all triggered by external stresses. A superelasticity induced by magnetic field, termed as magneto‐superelasticity, is extremely important for contactless work of materials and for developing brand‐new large stroke actuators and high efficiency energy transducers. In magnetic shape memory alloys, the twin boundary motion driven by magnetic field can output a strain of several percent. However, this strain is unrecoverable when removing the magnetic field and hence it is not magneto‐superelasticity. Here, a giant magneto‐superelasticity of 5% in a Ni 34 Co 8 Cu 8 Mn 36 Ga 14 single crystal is reported by introducing arrays of ordered dislocations to form preferentially oriented martensitic variants during the magnetically induced reverse martensitic transformation. This work provides an opportunity to achieve high performance in functional materials by defect engineering.

Okra （Abelmoschus esculentus L. ） is a novel heahhcare vegetable that has been developed rapidly in recent years in China. It contains abundant bioactive substances with significant heahbeare functions. So far, many domestic research institutions have carried out researches about the extraction technology of bioactive substances and their heahhcare functions. At present, tender pods and other organs of A. esculentus are mainly used freshly and directly, but rare products have been processed and developed. In this paper, the research progress of bioactive substances and processing ofA. esculentus was summarized, aiming at providing reference for the deep processing and comprehensive utilization of A. escu/entus in the future in China.

Using the tight-binding approach, we study the band gaps of boron nitride (BN)/ graphene nanoribbon (GNR) planar heterostructures, with GNRs embedded in a BN sheet. The width of BN has little effect on the band gap of a heterostructure. The band gap oscillates and decreases from 2.44 eV to 0.26 eV, as the width of armchair GNRs, nA, increases from 1 to 20, while the band gap gradually decreases from 3.13 eV to 0.09 eV, as the width of zigzag GNRs, nZ, increases from 1 to 80. For the planar heterojunctions with either armchair-shaped or zigzag-shaped edges, the band gaps can be manipulated by local potentials, leading to a phase transition from semiconductor to metal. In addition, the influence of lattice mismatch on the band gap is also investigated.

Precise extrinsic calibration is a fundamental prerequisite for data fusion in multi-LiDAR systems. However, conventional methods are often encumbered by dependencies on initial estimates, auxiliary sensors, or manual feature selection, which renders them complex, time-consuming, and limited in adaptability across diverse environments. To address these limitations, this paper proposes a novel, high-precision extrinsic calibration method for multi-LiDAR systems with a narrow Field of View (FoV), achieved through the synergistic use of circular and planar features. Our approach commences with the automatic segmentation of the calibration target’s point cloud using an improved VoxelNet. Subsequently, a denoising step, combining RANSAC and a Gaussian Mean Intensity Filter (GMIF), is applied to ensure high-quality feature extraction. From the refined point cloud, planar and circular features are robustly extracted via Principal Component Analysis (PCA) and least-squares fitting, respectively. Finally, the extrinsic parameters are optimized by minimizing a nonlinear objective function formulated with joint constraints from both geometric features. Simulation results validate the high precision of our method, with rotational and translational errors contained within 0.08° and 0.8 cm. Furthermore, real-world experiments confirm its effectiveness and superiority, outperforming conventional point-cloud registration techniques.

Diabetes mellitus (DM), a chronic metabolic disease with a high global prevalence, has increasingly been recognized for its adverse effects on the male reproductive system, particularly spermatogenesis. This review systematically summarizes the multifaceted impacts of diabetes on spermatogenesis, encompassing molecular mechanisms such as oxidative stress, endocrine disruption, dysregulated gene expression, metabolic imbalance, apoptosis, microcirculation impairment, and chronic inflammation, as revealed by recent studies. The intricate effects of these mechanisms on sperm quality, reproductive function, and offspring health are also thoroughly explored. A key innovation of this review lies in integrating recent advances, especially those highlighting the roles of epigenetic modifications, mitochondrial dysfunction, and insulin resistance (IR)-related pathways in spermatogenesis. Furthermore, the review evaluates the potential of personalized interventions, including glycemic control, antioxidant therapies, and lifestyle modifications, providing a scientific foundation for the development of more effective preventive and therapeutic strategies. This comprehensive analysis offers forward-looking guidance for future research and clinical interventions addressing diabetes-associated male infertility.