Manipulation of Exchange Bias in Two-Dimensional van der Waals Ferromagnet Near Room Temperature.

As a host for exchange bias (EB), van der Waals (vdW) magnetic materials have exhibited intriguing and distinct functionalities from conventional magnetic materials. The EB in most vdW systems is far below room temperature, which poses a challenge for practical applications. Here, by using Kerr microscopy, we demonstrate a record-high blocking temperature that approaches room temperature and a huge positive EB field that nears 2 kOe at 100 K in naturally oxidized two-dimensional (2D) vdW ferromagnetic Fe3GaTe2 nanoflakes. Moreover, we realized a reversible manipulation of both the presence/absence and positive/negative signs of EB via a training magnetic field without multiple field cooling processes. Thus, our study clearly reveals the robust, sizable, and sign-tunable EB in vdW magnetic materials up to near room temperature, thereby establishing Fe3GaTe2 as an emerging room-temperature-operating vdW material and paving the way for designing practical 2D spintronic devices.

Shoutai Wan treatment upregulates the expression of TNFAIP3 and improves T cell immune tolerance at maternal-fetal interface.

Shoutai Wan (STW) is a traditional Chinese medicine formula used to treat various conditions. The objective of this study was to evaluate the impact of STW on the abortion rate in the URSA mouse model and elucidate its underlying molecular mechanisms. Female CBA/J mice were mated with male DBA/2 mice to establish the URSA model. Network pharmacological analysis was employed to investigate the potential molecular mechanisms of STW. Hematoxylin-eosin staining, immunofluorescence, and ELISA were performed to examine placental microenvironmental changes, protein expression related to TNFAIP3 and the NF-κB signaling pathway. Treatment with STW reduced the abortion rate in URSA model mice and improved trophoblast development. TNFAIP3 was identified as a potential target of STW for treating URSA, as STW enhanced TNFAIP3 protein expression while decreasing IL-6 and TNF-α secretion in the placenta. Moreover, STW upregulated TNFAIP3 protein expression and Foxp3 mRNA levels, increased the production of anti-inflammatory cytokines such as IL-10 and TGF-ß1, and decreased p-NF-κB expression in CD4+ cells at the placenta. The findings of this study indicate that STW treatment reduces the abortion rate in the URSA mouse model. These effects are likely mediated by increased TNFAIP3 expression and decreased NF-κB signaling pathway activity at the maternal-fetal interface. These molecular changes may contribute to the regulation of T cell immunity and immune tolerance during pregnancy.

A Shape-Consistent Deep-Learning Segmentation Architecture for Low-Quality and High-Interference Myocardial Contrast Echocardiography.

OBJECTIVE: Myocardial contrast echocardiography (MCE) plays a crucial role in diagnosing ischemia, infarction, masses and other cardiac conditions. In the realm of MCE image analysis, accurate and consistent myocardial segmentation results are essential for enabling automated analysis of various heart diseases. However, current manual diagnostic methods in MCE suffer from poor repeatability and limited clinical applicability. MCE images often exhibit low quality and high noise due to the instability of ultrasound signals, while interference structures can further disrupt segmentation consistency. METHODS: To overcome these challenges, we proposed a deep-learning network for the segmentation of MCE. This architecture leverages dilated convolutions to capture high-scale information without sacrificing positional accuracy and modifies multi-head self-attention to enhance global context and ensure consistency, effectively overcoming issues related to low image quality and interference. Furthermore, we also adapted the cascade application of transformers with convolutional neural networks for improved segmentation in MCE. RESULTS: In our experiments, our architecture achieved the best Dice score of 84.35% for standard MCE views compared with that of several state-of-the-art segmentation models. For non-standard views and frames with interfering structures (mass), our models also attained the best Dice scores of 83.33% and 83.97%, respectively. CONCLUSION: These studies proved that our architecture is of excellent shape consistency and robustness, which allows it to deal with segmentation of various types of MCE. Our relatively precise and consistent myocardial segmentation results provide fundamental conditions for the automated analysis of various heart diseases, with the potential to discover underlying pathological features and reduce healthcare costs.

Quaternary phosphonium AIEgens nanoparticles as innovative agents for developing latent fingerprints.

Quaternary phosphonium salts, a significant category of organophosphorus compounds, have garnered substantial attention from chemists due to their wide range of applications across various research areas. These compounds are utilized in organic synthesis, catalysis, medicinal chemistry, natural materials, and coordination chemistry. Their versatility and effectiveness in these fields make them valuable tools in scientific research. Despite their extensive use in various applications, the potential of quaternary phosphonium compounds as fluorescent agents for revealing latent fingerprints (LFPs) remains largely unexplored, presenting an exciting opportunity for further research and development in forensic science. In this study, we designed molecules that combine the aggregation-induced emission (AIE) chromophore with triphenylphosphine to create a series of novel AIE amphiphiles, namely TPP1, TPP2, and TPP3. Through precise adjustment of the carbon chain length between the phenoxy group and the terminal triphenylphosphine, we were able to finely tune the nanostructures and hydrophobicity of the materials. TPP3 emerged as the optimal candidate, possessing the ideal particle size and hydrophobicity to effectively bind to LFPs, thus enabling efficient fingerprint visualization with enhanced fluorescence upon aggregation. Our findings introduce an innovative approach to fingerprint visualization, offering high selectivity, superior imaging of level 3 structures, and long-term effectiveness (up to 30 days). Additionally, TPP3's outstanding performance in imaging level 3 structures of LFPs is beneficial for analyzing incomplete LFPs and identifying individuals. By significantly improving the detection and analysis of LFPs, this approach ensures more accurate and reliable identification, making it invaluable for forensic investigations and security measures. The adaptability of these compounds to various fingerprint surfaces highlights their potential in diverse practical applications, enhancing their utility in both forensic science and security fields. This versatility allows for precise fingerprint visualization across different scenarios, making them a critical tool for advancing biometric and security technologies.

Controlled Reversible N-Terminal Modification of Peptides and Proteins.

A reversible modification strategy enables a switchable cage/decage process of proteins with an array of applications for protein function research. However, general N-terminal selective reversible modification strategies which present site selectivity are specifically limited. Herein, we report a general reversible modification strategy compatible with 20 canonical amino acids at the N-terminal site by the palladium-catalyzed cinnamylation of native peptides and proteins under biologically relevant conditions. This approach broadens the substrate adaptability of N-terminal modification of proteins and shows a potential impact on the more challenging protein substrates such as antibodies. In the presence of 1,3-dimethylbarbituric acid, palladium-catalyzed deconjugation released native peptides and proteins efficiently. Harnessing the reversible nature of this protocol, practical applications were demonstrated by precise function modulation of antibodies and traceless enrichment of the protein-of-interest for proteomics analysis. This novel on/off strategy working on the N-terminus will provide new opportunities in chemical biology and medicinal research.

Improving Nowcasting of Intense Convective Precipitation by Incorporating Dual-Polarization Radar Variables into Generative Adversarial Networks.

The nowcasting of strong convective precipitation is highly demanded and presents significant challenges, as it offers meteorological services to diverse socio-economic sectors to prevent catastrophic weather events accompanied by strong convective precipitation from causing substantial economic losses and human casualties. With the accumulation of dual-polarization radar data, deep learning models based on data have been widely applied in the nowcasting of precipitation. Deep learning models exhibit certain limitations in the nowcasting approach: The evolutionary method is prone to accumulate errors throughout the iterative process (where multiple autoregressive models generate future motion fields and intensity residuals and then implicitly iterate to yield predictions), and the "regression to average" issue of autoregressive model leads to the "blurring" phenomenon. The evolution method's generator is a two-stage model: In the initial stage, the generator employs the evolution method to generate the provisional forecasted data; in the subsequent stage, the generator reprocesses the provisional forecasted data. Although the evolution method's generator is a generative adversarial network, the adversarial strategy adopted by this model ignores the significance of temporary prediction data. Therefore, this study proposes an Adversarial Autoregressive Network (AANet): Firstly, the forecasted data are generated via the two-stage generators (where FURENet directly produces the provisional forecasted data, and the Semantic Synthesis Model reprocesses the provisional forecasted data); Subsequently, structural similarity loss (SSIM loss) is utilized to mitigate the influence of the "regression to average" issue; Finally, the two-stage adversarial (Tadv) strategy is adopted to assist the two-stage generators to generate more realistic and highly similar generated data. It has been experimentally verified that AANet outperforms NowcastNet in the nowcasting of the next 1 h, with a reduction of 0.0763 in normalized error (NE), 0.377 in root mean square error (RMSE), and 4.2% in false alarm rate (FAR), as well as an enhancement of 1.45 in peak signal-to-noise ratio (PSNR), 0.0208 in SSIM, 5.78% in critical success index (CSI), 6.25% in probability of detection (POD), and 5.7% in F1.

Examination of nonlinear associations between pulse pressure index and incident prediabetes susceptibility: a 5-year retrospective cohort investigation.

Prediabetes and related complications constitute significant public health burdens globally. As an indicator closely associated with abnormal glucose metabolism and atherosclerosis, the utility of Pulse Pressure Index (PPI) as a prediabetes risk marker has not been explored. We performed a retrospective cohort analysis to investigate this putative association between PPI and prediabetes hazard. Our analysis encompassed 183,517 Chinese adults ≥ 20 years registered within the Rich Healthcare Group 2010-2016. PPI was defined as (systolic blood pressure - diastolic blood pressure)/systolic blood pressure. The relationship between PPI and prediabetes risk was assessed via Cox proportional hazards regression modeling. Non-linearity evaluations applied cubic spline fitting approaches alongside smooth curve analysis. Inflection points of PPI concerning prediabetes hazard were determined using two-piecewise Cox models. During a median follow-up of 3 years (2.17-3.96 years), new-onset prediabetes was documented in 20,607 patients (11.23%). Multivariate regression analysis showed that PPI was an independent risk factor for prediabetes, and the risk of prediabetes increased by 0.6% for every 1% increase in PPI (Hazard Ratio [HR]: 1.006, 95% Confidence Interval [CI] 1.004-1.008, P < 0.001). This association was non-significant for PPI ≤ 37.41% yet exhibited a sharp upsurge when PPI surpassed 37.41% (HR: 1.013, 95% CI 1.005-1.021, P = 0.0029). Our analysis unveils a positive, non-linear association between PPI and future prediabetes risk. Within defined PPI ranges, this relationship is negligible but dramatically elevates beyond identified thresholds.

Predicting prognosis outcomes of primary central nervous system lymphoma with high-dose methotrexate-based chemotherapeutic treatment using lipidomics.

Background: Primary central nervous system lymphoma (PCNSL) is a rare extranodal lymphomatous malignancy which is commonly treated with high-dose methotrexate (HD-MTX)-based chemotherapy. However, the prognosis outcome of HD-MTX-based treatment cannot be accurately predicted using the current prognostic scoring systems, such as the Memorial Sloan-Kettering Cancer Center (MSKCC) score. Methods: We studied 2 cohorts of patients with PCNSL and applied lipidomic analysis to their cerebrospinal fluid (CSF) samples. After removing the batch effects and features engineering, we applied and compared several classic machine-learning models based on lipidomic data of CSF to predict the relapse of PCNSL in patients who were treated with HD-MTX-based chemotherapy. Results: We managed to remove the batch effects and get the optimum features of each model. Finally, we found that Cox regression had the best prediction performance (AUC = 0.711) on prognosis outcomes. Conclusions: We developed a Cox regression model based on lipidomic data, which could effectively predict PCNSL patient prognosis before the HD-MTX-based chemotherapy treatments.

Targeting mitochondrial quality control: new therapeutic strategies for major diseases.

Mitochondria play a crucial role in maintaining the normal physiological state of cells. Hence, ensuring mitochondrial quality control is imperative for the prevention and treatment of numerous diseases. Previous reviews on this topic have however been inconsistencies and lack of systematic organization. Therefore, this review aims to provide a comprehensive and systematic overview of mitochondrial quality control and explore the possibility of targeting the same for the treatment of major diseases. This review systematically summarizes three fundamental characteristics of mitochondrial quality control, including mitochondrial morphology and dynamics, function and metabolism, and protein expression and regulation. It also extensively examines how imbalances in mitochondrial quality are linked to major diseases, such as ischemia-hypoxia, inflammatory disorders, viral infections, metabolic dysregulations, degenerative conditions, and tumors. Additionally, the review explores innovative approaches to target mitochondrial quality control, including using small molecule drugs that regulate critical steps in maintaining mitochondrial quality, nanomolecular materials designed for precise targeting of mitochondria, and novel cellular therapies, such as vesicle therapy and mitochondrial transplantation. This review offers a novel perspective on comprehending the shared mechanisms underlying the occurrence and progression of major diseases and provides theoretical support and practical guidance for the clinical implementation of innovative therapeutic strategies that target mitochondrial quality control for treating major diseases.

Nomogram for predicting the risk of anxiety and depression in patients with non-mild burns.

BACKGROUND: Post-burn anxiety and depression affect considerably the quality of life and recovery of patients; however, limited research has demonstrated risk factors associated with the development of these conditions. AIM: To predict the risk of developing post-burn anxiety and depression in patients with non-mild burns using a nomogram model. METHODS: We enrolled 675 patients with burns who were admitted to The Second Affiliated Hospital, Hengyang Medical School, University of South China between January 2019 and January 2023 and met the inclusion criteria. These patients were randomly divided into development (n = 450) and validation (n = 225) sets in a 2:1 ratio. Univariate and multivariate logistic regression analyses were conducted to identify the risk factors associated with post-burn anxiety and depression diagnoses, and a nomogram model was constructed. RESULTS: Female sex, age < 33 years, unmarried status, burn area ≥ 30%, and burns on the head, face, and neck were independent risk factors for developing post-burn anxiety and depression in patients with non-mild burns. The nomogram model demonstrated predictive accuracies of 0.937 and 0.984 for anxiety and 0.884 and 0.923 for depression in the development and validation sets, respectively, and good predictive performance. Calibration and decision curve analyses confirmed the clinical utility of the nomogram. CONCLUSION: The nomogram model predicted the risk of post-burn anxiety and depression in patients with non-mild burns, facilitating the early identification of high-risk patients for intervention and treatment.

A Comprehensive Analysis of LYAR in Colorectal Cancer: Prognostic Marker and Therapeutic Target.

Background: Colorectal cancer (CRC) is a major global health challenge with a need for new biomarkers and therapeutic targets. This work aimed to investigate the biological mechanisms and clinical value of Ly1 antibody reactive (LYAR) in CRC. Methods: We analyzed LYAR mRNA expression across multiple public databases, including genotype-tissue expression, gene expression omnibus, Oncomine, and the cancer genome atlas, alongside in-house immunohistochemical data to evaluate LYAR protein expression in CRC and non-CRC colorectal tissues. Gene set enrichment analysis (GSEA) was used to elucidate LYAR's biological functions, and its impact on the tumor immune microenvironment was assessed using CIBERSORT, ESTIMATE, and single-cell RNA sequencing techniques. In addition, LYAR's association with clinicopathological features and patient prognosis was explored, and its influence on drug sensitivity was investigated using the Connectivity Map database. Results: LYAR was significantly upregulated in CRC tissues compared with non-CRC colorectal counterparts, associated with altered immune cell composition and enhanced RNA processing, splicing, and cell cycle regulation. High LYAR expression correlated with poor disease-free and overall survival, underscoring its prognostic value. GSEA revealed LYAR's involvement in critical cellular processes and pathways, including DNA repair, cell cycle, and mTORC1 signaling. Correlation analysis identified genes positively and negatively associated with LYAR, leading to the discovery of temsirolimus and WYE-354, mTOR inhibitors, as potential therapeutic agents for CRC. Furthermore, LYAR expression predicted increased sensitivity to cetuximab in RAS wild-type metastatic CRC, indicating its utility as a biomarker for treatment responsiveness. Conclusions: LYAR's upregulation in CRC highlights its potential as a biomarker for prognosis and therapeutic targeting, offering insights into CRC pathology and suggesting new avenues for treatment optimization.

2,2'-Bisdinitromethyl-5,5'-bistetrazole: A High-Performance, Multi-Nitro Energetic Material with Excellent Oxygen Balance.

Bistetrazoles are highly sought after for developing innovative high-energy density materials. The 1,1'-substituted bistetrazoles, exemplified by TKX-50, have outstanding performance. However, the research of high-perfomance 2,2'-substituted bistetrazoles remains limited. In this work, dinitromethyl groups were introduced into bistetrazole structures as 2,2'-substituted bistetrazoles (BDBTZ), which was extensively characterized through NMR, thermal analysis, and single crystal X-ray diffraction, exhibiting excellent oxygen balance, moderate sensitivity, acceptable thermal stability, high crystal density, and excellent detonation performance.

Symbiotic biofilms formed by Clostridioides difficile and bacteroides thetaiotaomicron in the presence of vancomycin.

Vancomycin (VAN) treatment in Clostridioides difficile infection (CDI) suffers from a relatively high rate of recurrence, with a variety of reasons behind this, including biofilm-induced recurrent infections. C. difficile can form monophyletic or symbiotic biofilms with other microbes in the gut, and these biofilms protect C. difficile from being killed by antibiotics. In this study, we analyzed the ecological relationship between Bacteroides thetaiotaomicron and C. difficile and their formation of symbiotic biofilm in the VAN environment. The production of symbiotic biofilm formed by C. difficile and B. thetaiotaomicron was higher than that of C. difficile and B. thetaiotaomicron alone in the VAN environment. In symbiotic biofilms, C. difficile was characterized by increased production of the toxin protein TcdA and TcdB, up-regulation of the expression levels of the virulence genes tcdA and tcdB, enhanced bacterial cell swimming motility and c-di-GMP content, and increased adhesion to Caco-2 cells. The scanning electron microscope (SEM) combined with confocal laser scanning microscopy (CLSM) results indicated that the symbiotic biofilm was elevated in thickness, dense, and had an increased amount of mixed bacteria, while the fluorescence in situ hybridization (FISH) probe and plate colony counting results further indicated that the symbiotic biofilm had a significant increase in the amount of C. difficile cells, and was able to better tolerate the killing of the simulated intestinal fluid. Taken together, C. difficile and B. thetaiotaomicron become collaborative in the VAN environment, and targeted deletion or attenuation of host gut B. thetaiotaomicron content may improve the actual efficacy of VAN in CDI treatment.

Hydrogen sulfide produced by the gut microbiota impairs host metabolism via reducing GLP-1 levels in male mice.

Dysbiosis of the gut microbiota has been implicated in the pathogenesis of metabolic syndrome (MetS) and may impair host metabolism through harmful metabolites. Here, we show that Desulfovibrio, an intestinal symbiont enriched in patients with MetS, suppresses the production of the gut hormone glucagon-like peptide 1 (GLP-1) through the production of hydrogen sulfide (H2S) in male mice. Desulfovibrio-derived H2S is found to inhibit mitochondrial respiration and induce the unfolded protein response in intestinal L cells, thereby hindering GLP-1 secretion and gene expression. Remarkably, blocking Desulfovibrio and H2S with an over-the-counter drug, bismuth subsalicylate, improves GLP-1 production and ameliorates diet-induced metabolic disorder in male mice. Together, our study uncovers that Desulfovibrio-derived H2S compromises GLP-1 production, shedding light on the gut-relayed mechanisms by which harmful microbiota-derived metabolites impair host metabolism in MetS and suggesting new possibilities for treating MetS.

TP53 and KMT2D mutations associated with worse prognosis in peripheral T-cell lymphomas.

There are limited studies on mutation profiling for Peripheral T-cell lymphomas (PTCL) in the Chinese population. We retrospectively analyzed the clinical and genetic landscape of 66 newly diagnosed Chinese patients. Targeted next-generation sequencing (NGS) was performed for tissues from these patients. At least one mutation was detected in 60 (90.9%) patients, with a median number of 3 (0-7) mutations, and 32 (48.5%) cases detected with more than 4 mutations. The genes with higher mutation frequencies were TET2, RHOA, DNMT3A, IDH2, TP53, STAT3, and KMT2D respectively. When mutant genes are classified by functional group, the most prevalent mutations are related to epigenetics and signal transduction. IPI ≥2, PIT ≥2, and failure to achieve partial remission (PR) were factors for inferior progression-free survival (PFS) and overall survival (OS). Multivariate analysis showed TP53 was an adverse factor for PFS (HR, 3.523; 95% CI, 1.262-9.835; p = 0.016), and KMT2D was an adverse factor for OS (HR, 10.097; 95% CI, 1.000-101.953; p = 0.048). Mutation profiling could help differentiate distinct types of PTCL and serve as a useful tool for determining treatment options and prognoses.

Co-pyrolysis Behavior of Coal and Biomass: Synergistic Effect and Kinetic Analysis.

Co-pyrolysis of coal and biomass is an efficient way to utilize resources. This study investigates the co-pyrolysis behavior and kinetics of coal and biomass using thermogravimetric analysis (TGA) and TG-FTIR. Co-pyrolysis of coal and biomass exhibits a synergistic effect. When the biomass is 25%, the weight loss increases, showing a positive synergistic effect. When the biomass is 50%, it exhibits a negative synergistic effect. Increasing the heating rate can promote the generation of a synergistic effect. Co-pyrolysis involves two central pyrolysis stages: stage III (250-380 °C) and stage IV (380-550 °C). Friedman, FWO, KAS, and STA methods are used to calculate the activation energy for stages III and IV. The activation energy (E α) for co-pyrolysis is higher than that for coal or biomass pyrolysis alone. A positive synergistic effect is observed in stage III, while a negative synergistic effect is noted in stage IV. The master curve method determines an accurate reaction order (n) and pre-exponential factor (A) value of Coal75-Bio25. In stage III, E α = 238.81 kJ/mol, n = 2.4, A = 1.30 × 1021 s-1. In stage IV, E α = 37 8.01 kJ/mol, n = 4.0, A = 1.10 × 1027 s-1. The kinetic parameters in stage IV are significantly higher than those in stage III. TG-FTIR is used to analyze the synergistic effect of co-pyrolysis. Compared with coal and biomass pyrolysis separately, the Coal75-Bio25 pyrolysis process releases less CO2 and more CH4. These findings support the synergistic effect of coal and biomass during co-pyrolysis.

Clinical Implications of Acute Stent Mal-Apposition in the Left Main Coronary Artery.

Background: Intravascular ultrasound (IVUS) has been utilized to determine acute stent mal-apposition (ASM) after percutaneous coronary intervention (PCI) in the left main coronary artery (LMCA). However, the clinical consequences of this finding remain uncertain. This research aimed to evaluate the clinical implications of ASM in the LMCA using IVUS. Methods: In this study, 408 patients who underwent successful drug-eluting stent (DES) implantation in the LMCA were evaluated. We analyzed the prevalence and characteristics of ASM and its correlation with clinical outcomes. ASM is characterized by stent struts that are not in immediate proximity to the intimal surface of the vessel wall after initial stent deployment. Results: The observed incidence of LMCA-ASM post-successful PCI was 26.2%, both per patient and per lesion. Lesions with LMCA-ASM had a longer stent diameter, larger stent areas, and larger lumen areas compared to those without LMCA-ASM (4.0 ± 0.5 vs. 3.7 ± 0.4 mm, p < 0.001; 9.8 ± 2.0 vs. 9.0 ± 1.6 mm 2 , p < 0.001; 12.3 ± 1.9 vs. 10.1 ± 2.1 mm 2 , p < 0.001, respectively). The mean external elastic membrane (EEM) area (odds ratio (OR): 1.418 [95% confidence interval (CI): 1.295-1.556]; p < 0.001) emerged as an independent predictor of LMCA-ASM. During the observation period, LMCA-ASM did not display any association with device-oriented clinical endpoints (DoCE), which included cardiac death, target vessel-induced myocardial infarction (MI), stent thrombosis, and target lesion revascularization (TLR). Moreover, the DoCE incidence exhibited no significant disparity between patients with or without ASM (13.1 vs. 6.0%, p = 0.103). Conclusions: While LMCA-ASM was a not uncommon finding post-PCI, it did not correlate with adverse cardiac events in the present study.