Clinical metabolomics characteristics of diabetic kidney disease: A meta-analysis of 1875 cases with diabetic kidney disease and 4503 controls.

AIMS: Diabetic Kidney Disease (DKD), one of the major complications of diabetes, is also a major cause of end-stage renal disease. Metabolomics can provide a unique metabolic profile of the disease and thus predict or diagnose the development of the disease. Therefore, this study summarises a more comprehensive set of clinical biomarkers related to DKD to identify functional metabolites significantly associated with the development of DKD and reveal their driving mechanisms for DKD. MATERIALS AND METHODS: We searched PubMed, Embase, the Cochrane Library and Web of Science databases through October 2022. A meta-analysis was conducted on untargeted or targeted metabolomics research data based on the strategy of standardized mean differences and the process of ratio of means as the effect size, respectively. We compared the changes in metabolite levels between the DKD patients and the controls and explored the source of heterogeneity through subgroup analyses, sensitivity analysis and meta-regression analysis. RESULTS: The 34 clinical-based metabolomics studies clarified the differential metabolites between DKD and controls, containing 4503 control subjects and 1875 patients with DKD. The results showed that a total of 60 common differential metabolites were found in both meta-analyses, of which 5 metabolites (p < 0.05) were identified as essential metabolites. Compared with the control group, metabolites glycine, aconitic acid, glycolic acid and uracil decreased significantly in DKD patients; cysteine was significantly higher. This indicates that amino acid metabolism, lipid metabolism and pyrimidine metabolism in DKD patients are disordered. CONCLUSIONS: We have identified 5 metabolites and metabolic pathways related to DKD which can serve as biomarkers or targets for disease prevention and drug therapy.

Pest recognition in microstates state: an improvement of YOLOv7 based on Spatial and Channel Reconstruction Convolution for feature redundancy and vision transformer with Bi-Level Routing Attention.

Introduction: In order to solve the problem of precise identification and counting of tea pests, this study has proposed a novel tea pest identification method based on improved YOLOv7 network. Methods: This method used MPDIoU to optimize the original loss function, which improved the convergence speed of the model and simplifies the calculation process. Replace part of the network structure of the original model using Spatial and Channel reconstruction Convolution to reduce redundant features, lower the complexity of the model, and reduce computational costs. The Vision Transformer with Bi-Level Routing Attention has been incorporated to enhance the flexibility of model calculation allocation and content perception. Results: The experimental results revealed that the enhanced YOLOv7 model significantly boosted Precision, Recall, F1, and mAP by 5.68%, 5.14%, 5.41%, and 2.58% respectively, compared to the original YOLOv7. Furthermore, when compared to deep learning networks such as SSD, Faster Region-based Convolutional Neural Network (RCNN), and the original YOLOv7, this method proves to be superior while being externally validated. It exhibited a noticeable improvement in the FPS rates, with increments of 5.75 HZ, 34.42 HZ, and 25.44 HZ respectively. Moreover, the mAP for actual detection experiences significant enhancements, with respective increases of 2.49%, 12.26%, and 7.26%. Additionally, the parameter size is reduced by 1.39 G relative to the original model. Discussion: The improved model can not only identify and count tea pests efficiently and accurately, but also has the characteristics of high recognition rate, low parameters and high detection speed. It is of great significance to achieve realize the intelligent and precise prevention and control of tea pests.

Ultrafast Chiral Precession of Spin and Orbital Angular Momentum Induced by Circularly Polarized Laser Pulse in Elementary Ferromagnets.

Despite spin (SAM) and orbital (OAM) angular momentum dynamics being well-studied in demagnetization processes, their components receive less focus. Here, we utilize real-time time-dependent density functional theory (rt-TDDFT) to unveil significant x and y components of SAM and OAM induced by circularly left (σ+) and right (σ-) polarized laser pulses in ferromagnetic Fe, Co, and Ni. Our results show that the magnitude of the OAM is an order of magnitude larger than that of the SAM, highlighting a stronger optical response from the orbital degrees of freedom of electrons. Intriguingly, σ+ and σ- pulses induce chirality in the precession of SAM and OAM, respectively, with clear associations with laser frequency and duration. Finally, we demonstrate the time scale of the OAM and SAM precession occurs even earlier than that of the demagnetization process and the OISTR effect. Our results provide detailed insight into the dynamics of SAM and OAM during and shortly after a polarized laser pulse.

HmsU-Net: A hybrid multi-scale U-net based on a CNN and transformer for medical image segmentation.

Accurate medical image segmentation is of great significance for subsequent diagnosis and analysis. The acquisition of multi-scale information plays an important role in segmenting regions of interest of different sizes. With the emergence of Transformers, numerous networks adopted hybrid structures incorporating Transformers and CNNs to learn multi-scale information. However, the majority of research has focused on the design and composition of CNN and Transformer structures, neglecting the inconsistencies in feature learning between Transformer and CNN. This oversight has resulted in the hybrid network's performance not being fully realized. In this work, we proposed a novel hybrid multi-scale segmentation network named HmsU-Net, which effectively fused multi-scale features. Specifically, HmsU-Net employed a parallel design incorporating both CNN and Transformer architectures. To address the inconsistency in feature learning between CNN and Transformer within the same stage, we proposed the multi-scale feature fusion module. For feature fusion across different stages, we introduced the cross-attention module. Comprehensive experiments conducted on various datasets demonstrate that our approach surpasses current state-of-the-art methods.

Biodegradable active composite hydrogel packaging for postharvest climacteric bananas preservation.

Climacteric bananas are susceptible to endogenous ethylene and temperature, resulting in dehydration, accelerated senescence and deterioration. The widely-used plastic cling films is particularly complicated due to their high consumption and non-degradability. Herein, this study proposed to fabricate a carboxymethyl cellulose/polyvinyl alcohol/pyrazoic acid (CPP) hydrogel for postharvest banana preservation. The hydrogel demonstrated excellent potential as a packaging film, including natural degradability (complete degradation within 50 days), high tensile performance, transparent visibility and biosafety. As a validation experiment, bananas in a 30 °C environment confirmed the effectiveness of CPP hydrogels in banana postharvest preservation. Compared with the blank control and CP hydrogel, CPP packaging film delayed the processes of browning, dehydration, softening, nutrients loss, ripening and senescence in bananas, thereby maintaining their commercial value. Accordingly, this study demonstrates the potential of hydrogel materials as an alternative strategy to climacteric fruit preservation and plastic film.

Visualisation of Droplet Flow Induced by Ultrasonic Dental Cleaning.

INTRODUCTION: During dental treatment procedures ultrasonic scalers generate droplets containing microorganisms such as bacteria and viruses. Hence, it is necessary to study the dynamic properties of generated droplets in order to investigate the risks associated with the spread of infection. The aim of this study was to visualise the flow state of droplets and to evaluate the impact of droplets generated during the use of an ultrasonic scaler during an oral surgical procedure. METHODS: We studied the spatial flow of liquid droplets through a combination of imaging and numeric simulation of a simulated dental treatment processes. First, we photographed the real time images of the ultrasonic scaler and evaluated the images using image-processing software Image J to visualise the flow of liquid droplets. Finally we simulated the flow process of liquid droplets by using the initial velocity of droplet splashing and the angle of the obtained information using computerised fluid dynamics technology. RESULTS: Under different working conditions, the droplet particle splashing velocity, maximum height, and spray angle varied, but the particle trajectory was generally parabolic. The maximum droplet velocity varied between 3.56 and 8.56 m/s, and the splashing height was between 40 and 110 mm. CONCLUSIONS: During risk assessment of an ultrasonic scaler usage, difficulties arise due to the insufficient research on droplet velocity and distribution. This study aims to address this gap by visualising the flow trajectories of droplets generated by ultrasonic scalers. The obtained data will assist in developing more effective interventions based on spatial and temporal distribution of droplets. This provides a new approach for droplet particle research and offers new strategies for public health prevention and control.

In Situ Vanadium-Deficient Engineering of V2 C MXene: A Pathway to Enhanced Zinc-Ion Batteries.

This research examines vanadium-deficient V2 C MXene, a two-dimensional (2D) vanadium carbide with exceptional electrochemical properties for rechargeable zinc-ion batteries. Through a meticulous etching process, a V-deficient, porous architecture with an expansive surface area is achieved, fostering three-dimensional (3D) diffusion channels and boosting zinc ion storage. Analytical techniques like scanning electron microscopy, transmission electron microscopy, Brunauer-Emmett-Teller, and X-ray diffraction confirm the formation of V2 C MXene and its defective porous structure. X-ray photoelectron spectroscopy further verifies its transformation from the MAX phase to MXene, noting an increase in V3+ and V4+ states with etching. Cyclic voltammetry reveals superior de-zincation kinetics, evidenced by consistent V3+ /V4+ oxidation peaks at varied scanning rates. Overall, this V-deficient MXene outperforms raw MXenes in capacity and rate, although its capacity diminishes over extended cycling due to structural flaws. Theoretical analyses suggest conductivity rises with vacancies, enhancing 3D ionic diffusion as vacancy size grows. This work sheds light on enhancing V-based MXene structures for optimized zinc-ion storage.

Study of aerosol dispersion and control in dental practice.

OBJECTIVES: In this study, we investigated the dispersion patterns of aerosols and droplets in dental clinics and developed a suction device to evaluate its effectiveness in reducing aerosols during dental procedures. MATERIALS AND METHODS: Firstly, the continuous images of oral aerosols and droplets were photographed with a high-speed camera, and the trajectories of these particles were recognized and processed by Image J to determine key parameters affecting particle dispersion: diffusion velocity, distance, and angle. Secondly, based on the parameter data, the flow field of aerosol particles around the oral cavity was simulated using computational fluid dynamics (CFD), and the flow field under adsorption conditions was simulated to demonstrate the aerodynamic characteristics and capture efficiencies of the single-channel and three-channel adsorption ports at different pressures. Finally, according to the simulated data, a three-channel suction device was developed, and the capture efficiency of the device was tested by the fluorescein tracer method. RESULTS: The dispersion experimental data showed that aerosol particles' maximum diffusion velocity, distance, and angle were 6.2 m/s, 0.55 m, and 130°, respectively. The simulated aerosol flow-field distribution was consistent with the aerosol dispersion patterns. The adsorption simulation results showed that the outlet flow rate of single-channel adsorption was 184.5 L/s at - 350 Pa, and the aerosol capture efficiency could reach 79.4%. At - 350 Pa and - 150 Pa, the outlet flow rate of three-channel adsorption was 228.9 L/s, and the capture efficiency was 99.23%. The adsorption experimental data showed that the capture efficiency of three-channel suction device was 97.71%. CONCLUSIONS: A three-channel suction device was designed by simulations and experiments, which can capture most aerosols in the dental clinic and prevent them from spreading. CLINICAL RELEVANCE: Using three-channel suction devices during oral treatment effectively reduces the spread of oral aerosols, which is essential to prevent the spread of epidemics and ensure the health and safety of patients and dental staff.

Association Between Human Metabolomics and Rheumatoid Arthritis: A Systematic Review and Meta-analysis.

OBJECTIVE: The underdiagnosis and inadequate treatment of rheumatoid arthritis (RA) can be attributed to the various clinical manifestations presented by patients. To address this concern, we conducted an extensive review and meta-analysis, focusing on RA-related metabolites. METHODS: A comprehensive literature search was conducted in PubMed, the Cochrane Library, Web of Science, and Embase to identify relevant studies published up to October 5, 2022. The quality of the included articles was evaluated and, subsequently, a meta-analysis was conducted using Review Manager software to analyze the association between metabolites and RA. RESULTS: Forty nine studies met the inclusion criteria for the systematic review, and six of these studies were meta-analyzed to evaluate the association between 28 reproducible metabolites and RA. The results indicated that, compared to controls, the levels of histidine (RoM = 0.83, 95% CI = 0.79-0.88, I2 = 0%), asparagine (RoM = 0.83, 95% CI = 0.75-0.91, I2 = 0%), methionine (RoM = 0.82, 95% CI = 0.69-0.98, I2 = 85%), and glycine (RoM = 0.81, 95% CI = 0.67-0.97, I2 = 68%) were significantly lower in RA patients, while hypoxanthine levels (RoM = 1.14, 95% CI = 1.09-1.19, I2 = 0%) were significantly higher. CONCLUSION: This study identified histidine, methionine, asparagine, hypoxanthine, and glycine as significantly correlated with RA, thus offering the potential for the advancement of biomarker discovery and the elucidation of disease mechanisms in RA.

SaB-Net: Self-attention backward network for gastric tumor segmentation in CT images.

Gastric cancer is a significant contributor to cancer-related fatalities globally. The automated segmentation of gastric tumors has the potential to analyze the medical condition of patients and enhance the likelihood of surgical treatment success. However, the development of an automatic solution is challenged by the heterogeneous intensity distribution of gastric tumors in computed tomography (CT) images, the low-intensity contrast between organs, and the high variability in the stomach shapes and gastric tumors in different patients. To address these challenges, we propose a self-attention backward network (SaB-Net) for gastric tumor segmentation (GTS) in CT images by introducing a self-attention backward layer (SaB-Layer) to feed the self-attention information learned at the deep layer back to the shallow layers. The SaB-Layer efficiently extracts tumor information from CT images and integrates the information into the network, thereby enhancing the network's tumor segmentation ability. We employed datasets from two centers, one for model training and testing and the other for external validation. The model achieved dice scores of 0.8456 on the test set and 0.8068 on the external verification set. Moreover, we validated the model's transfer learning ability on a publicly available liver cancer dataset, achieving results comparable to state-of-the-art liver cancer segmentation models recently developed. SaB-Net has strong potential for assisting in the clinical diagnosis of and therapy for gastric cancer. Our implementation is available at https://github.com/TyrionJ/SaB-Net.

Terahertz Laser Pulse Boosts Interlayer Spin Transfer in Two-Dimensional van der Waals Magnetic Heterostructures.

Light-induced ultrafast dynamics in two-dimensional (2D) magnetic systems demonstrate substantial advancements in spintronics. Here, using the real-time time-dependent density functional theory (rt-TDDFT), we applied laser pulses with various frequencies, from terahertz (THz) to optical pulse, to systematically study the interlayer spin transfer dynamics in 2D van der Waals nonmagnetic-ferromagnetic heterostructures, including graphene-Fe3GeTe2 (Gr/FGT) and silicene-Fe3GeTe2 (Si/FGT). Our results demonstrate that low-frequency THz pulses are particularly effective in facilitating interlayer spin injection from the ferromagnetic FGT layers to the Si or Gr layers. On the contrary, high-frequency optical pulses exhibit a minimal influence on this process. Such an effect is attributed to the low-frequency THz pulses inducing in-phase oscillations of the electron charge density around atomic centers, leading to a highly efficient interlayer spin transfer. Our results provide a new insight into ultrafast THz radiation control intralayer spin transfer and magnetic proximity dynamics in the 2D limit.

Corrigendum: The effect of temperature on dengue virus transmission by Aedes mosquitoes.

[This corrects the article DOI: 10.3389/fcimb.2023.1242173.].

Quantum anomalous valley Hall effect in ferromagnetic MXenes with asymmetric functionalization.

The potential to detect and manipulate the valley degree of freedom within two-dimensional hexagonal lattices possessing both inversion asymmetry and time-reversal symmetry is theoretically feasible. Intrinsic ferrovalley polarization in MXenes could be induced by asymmetric surface functionalization to break their inversion symmetry and the presence of spin-orbital coupling ensures their time-reversal symmetry. Our results indicate that the ferromagnetic Cr2COF MXene with Janus functionalization becomes an intrinsic Chern insulator with large spin-valley polarization and belongs to the family of quantum anomalous valley Hall effect (QAVHE) materials, based on Berry curvature and edge state calculations. Applying chemical engineering of functionalization to magnetic MXenes allows us to tune the structure-property relationship in 2D layers to obtain desirable spin-valley coupling. Our theoretical insight into the QAVHE on magnetic MXenes with asymmetry functionalization provides a new opportunity for valleytronics and spintronics.

Lipidomics reveals the lipid metabolism disorders in Fructus Psoraleae-induced hepatotoxicity in rats with kidney-yin deficiency syndrome.

Fructus Psoraleae (FP), one of the important traditional Chinese medicines, is widely used in clinic and has been reported to be hepatotoxic. However, there is no report on the mechanism of FP-induced hepatotoxicity based on the theory of You Gu Wu Yun. In this study, plasma samples of rats with different kidney deficiency syndromes were investigated using a lipidomics approach based on UPLC/Q-TOF-MS technique. Firstly, multivariate statistical analysis, VIP value test, statistical test and other methods were used to find the lipid metabolites in the two syndrome model groups that were different from the normal group. The screening of differential lipid metabolites revealed that there were 12 biomarkers between the blank group and the kidney-yang deficiency model group as well as 16 differential metabolites between the kidney-yin deficiency model group, and finally a total of 17 relevant endogenous metabolites were identified, which could be used as differential lipid metabolites to distinguish between kidney-yin deficiency and kidney-yang deficiency evidence. Secondly, the relative content changes of metabolites in rats after administration of FP decoction were further compared to find the substances associated with toxicity after administration, and the diagnostic ability of the identified biomarkers was evaluated using a receiver operating characteristic curve (ROC). Results a total of 14 potential differential lipid metabolites, including LysoPC(20:0/0:0) and LysoPC(16:0/0:0), which may be related to hepatotoxicity in rats with kidney-yin deficiency syndrome were further screened, namely, the potential active lipid metabolites related to hepatotoxicity in rats induced by FP. Finally, cluster analysis, MetPA analysis and KEGG database were used to analyze metabolic pathways. It was discovered that the metabolism of glycerophospholipid and sphingolipid may be strongly related to the mechanism of hepatotoxicity brought on by FP. Overall, we described the lipidomics changes in rats treated with FP decoction and screened out 14 lipid metabolites related to hepatotoxicity in rats with kidney-yin deficiency, which served as a foundation for the theory of "syndrome differentiation and treatment" in traditional Chinese medicine and a guide for further investigation into the subsequent mechanism.

A meta-analysis of treatment for early-stage cervical cancer: open versus minimally invasive radical trachelectomy.

BACKGROUND: In previous systematic reviews, meta-analysis was lacking, resulting in the statistical difference between the data of different surgeries being impossible to judge. This meta-analysis aims to contrast the fertility results and cancer outcomes between open and minimally invasive surgery. METHOD: We systematically searched databases including PubMed, Embase, Cochrane, and Scopus to collect studies that included open and minimally invasive radical trachelectomy. A random-effect model calculated the weighted average difference of each primary outcome via Review Manager V.5.4. RESULT: Eight studies (1369 patients) were incorporated into our study. For fertility results, the Open group excels MIS group in pregnancies-Third trimester delivery [OR = 2.68; 95% CI (1.29, 5.59); P = 0.008]. Nevertheless, there is no statistical difference in clinical pregnancy, miscarriage, and second-trimester rate. Concerning cancer outcomes, no difference was detected in the overall survival [OR = 1.56; 95% CI (0.70, 3.45); P = 0.27] and recurrence [OR = 0.63; 95% CI (0.35, 1.12); P = 0.12]. Concerning surgery-related outcomes, the comprehensive effects revealed that the estimated blood loss of the Open group was higher than that of the MIS group[MD = 139.40; 95% CI (79.05, 199.75); P < 0.0001]. However, there was no difference between the postoperative complication rate in the two groups [OR = 1.52; 95% CI (0.89, 2.60); P = 0.12]. CONCLUSION: This meta-analysis suggested that the fertility result of the Open group may be better than the MIS group, while the MIS group has better surgery-related outcomes. Owing to the poor cases of our study, a more robust conclusion requires more relevant articles in the future. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022352999.

The effect of temperature on dengue virus transmission by Aedes mosquitoes.

Dengue is prevalent in tropical and subtropical regions. As an arbovirus disease, it is mainly transmitted by Aedes aegypti and Aedes albopictus. According to the previous studies, temperature is closely related to the survival of Aedes mosquitoes, the proliferation of dengue virus (DENV) and the vector competence of Aedes to transmit DENV. This review describes the correlations between temperature and dengue epidemics, and explores the potential reasons including the distribution and development of Aedes mosquitoes, the structure of DENV, and the vector competence of Aedes mosquitoes. In addition, the immune and metabolic mechanism are discussed on how temperature affects the vector competence of Aedes mosquitoes to transmit DENV.

Effect of heat treatment on the physical stability, interfacial composition and protein-lipid co-oxidation of whey protein isolate-stabilised O/W emulsions.

This work aimed to investigate the effects of heat treatments at different temperatures (60, 70 and 90 °C, expressed as HT-60, HT-70 and HT-90) on interfacial composition and protein-lipid co-oxidation in whey protein isolate (WPI)-stabilised O/W emulsions during storage. Compared with control group, all heated emulsions exhibited weaker physical stability over 10 days of storage, which verified by the increased droplet size, as well as decreased adsorbed protein levels and absolute ζ-potential values. Moreover, proteins recovered from the HT-90 emulsion showed the highest fluorescence intensity and red-shift of the maximum emission wavelength, indicating partial unfolding of the protein structure. Meanwhile, severe changes in protein structure were also observed in the HT-70 and HT-90 emulsions, which clearly verified by the degradation of bovine serum albumin, α-lactalbumin and ß-lactoglobulin. Furthermore, HT-70 and HT-90 emulsions showed lower levels of lipid hydroperoxides and thiobarbituric acid reactive substances. In contrast, the recovered proteins were subject to severe oxidative stress as indicated by carbonyl and N'-formyl-L-kynurenine. Hierarchical cluster and correlation analysis implied that the process of protein-lipid co-oxidation is inevitable, but it can be retarded by heat treatment. Our results clearly revealed the relevance among heat treatment, interfacial adsorption property, and the protein-lipid co-oxidation of O/W emulsions.

TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma.

BACKGROUND AND OBJECTIVES: The pathological diagnosis of renal cell carcinoma is crucial for treatment. Currently, the multi-instance learning method is commonly used for whole-slide image classification of renal cell carcinoma, which is mainly based on the assumption of independent identical distribution. But this is inconsistent with the need to consider the correlation between different instances in the diagnosis process. Furthermore, the problem of high resource consumption of pathology images is still urgent to be solved. Therefore, we propose a new multi-instance learning method to solve this problem. METHODS: In this study, we proposed a hybrid multi-instance learning model based on the Transformer and the Graph Attention Network, called TGMIL, to achieve whole-slide image of renal cell carcinoma classification without pixel-level annotation or region of interest extraction. Our approach is divided into three steps. First, we designed a feature pyramid with the multiple low magnifications of whole-slide image named MMFP. It makes the model incorporates richer information, and reduces memory consumption as well as training time compared to the highest magnification. Second, TGMIL amalgamates the Transformer and the Graph Attention's capabilities, adeptly addressing the loss of instance contextual and spatial. Within the Graph Attention network stream, an easy and efficient approach employing max pooling and mean pooling yields the graph adjacency matrix, devoid of extra memory consumption. Finally, the outputs of two streams of TGMIL are aggregated to achieve the classification of renal cell carcinoma. RESULTS: On the TCGA-RCC validation set, a public dataset for renal cell carcinoma, the area under a receiver operating characteristic (ROC) curve (AUC) and accuracy of TGMIL were 0.98±0.0015,0.9191±0.0062, respectively. It showcased remarkable proficiency on the private validation set of renal cell carcinoma pathology images, attaining AUC of 0.9386±0.0162 and ACC of 0.9197±0.0124. Furthermore, on the public breast cancer whole-slide image test dataset, CAMELYON 16, our model showed good classification performance with an accuracy of 0.8792. CONCLUSIONS: TGMIL models the diagnostic process of pathologists and shows good classification performance on multiple datasets. Concurrently, the MMFP module efficiently diminishes resource requirements, offering a novel angle for exploring computational pathology images.

Ultrafast Laser Pulse Induced Transient Ferrimagnetic State and Spin Relaxation Dynamics in Two-Dimensional Antiferromagnets.

We employ real-time time-dependent density functional theory (rt-TDDFT) and ab initio nonadiabatic molecular dynamics (NAMD) to systematically investigate the ultrafast laser pulses induced spin transfer and relaxation dynamics of two-dimensional (2D) antiferromagnetic-ferromagnetic (AFM/FM) MnPS3/MnSe2 van der Waals heterostructures. We demonstrate that laser pulses can induce a ferrimagnetic (FiM) state in the AFM MnPS3 layer within tens of femtoseconds and maintain it for subpicosecond time scale before reverting to the AFM state. We identify the mechanism in which the asymmetric optical intersite spin transfer (OISTR) effect occurring within the sublattices of the AFM and FM layers drives the interlayer spin-selective charge transfer, leading to the transition from AFM to FiM state. Furthermore, the unequal electron-phonon coupling of spin-up and spin-down channels of AFM spin sublattice causes an inequivalent spin relaxation, in turn extending the time scale of the FiM state. These findings are essential for designing novel optical-driven ultrafast 2D magnetic switches.

Siglec-9 acts as an immune-checkpoint molecule on macrophages in glioblastoma, restricting T-cell priming and immunotherapy response.

Neoadjuvant immune-checkpoint blockade therapy only benefits a limited fraction of patients with glioblastoma multiforme (GBM). Thus, targeting other immunomodulators on myeloid cells is an attractive therapeutic option. Here, we performed single-cell RNA sequencing and spatial transcriptomics of patients with GBM treated with neoadjuvant anti-PD-1 therapy. We identified unique monocyte-derived tumor-associated macrophage subpopulations with functional plasticity that highly expressed the immunosuppressive SIGLEC9 gene and preferentially accumulated in the nonresponders to anti-PD-1 treatment. Deletion of Siglece (murine homolog) resulted in dramatically restrained tumor development and prolonged survival in mouse models. Mechanistically, targeting Siglece directly activated both CD4+ T cells and CD8+ T cells through antigen presentation, secreted chemokines and co-stimulatory factor interactions. Furthermore, Siglece deletion synergized with anti-PD-1/PD-L1 treatment to improve antitumor efficacy. Our data demonstrated that Siglec-9 is an immune-checkpoint molecule on macrophages that can be targeted to enhance anti-PD-1/PD-L1 therapeutic efficacy for GBM treatment.