Synergistic Strengthening Mechanisms of Dual-Phase (TiN+AlN) Reinforced Aluminum Matrix Composites Prepared by Laser Powder Bed Fusion.

Dual-phase reinforcing approach provides a novel and efficient strategy for the fabrication of advanced aluminum matrix composites (AMCs). The devisable and desirable performance could be achieved by tuning dual-phase reinforcing system. However, it is still challenging to design a dual-phase reinforcing system with synergistic strengthening effect, especially for the laser powder bed fusion (LPBF) characterized by nonequilibrium metallurgical process. In this work, we designed and fabricated dual-phase (TiN+AlN) particles (20 wt.%) reinforced pure Al by LPBF. The TiN and AlN can form a metastable ternary Ti1-xAlxN solid solution in the whole range of composition, which is a promising reinforcing phase for AMCs. We observed novel microstructure in laser-fabricated composites under the action of dual-phase (TiN+AlN) ceramic particles and laser melting process. A gradient layer is formed on the surface of TiN particles. This interfacial structure can act as an anchor for ceramic particles in the Al matrix, which is beneficial to achieve a strong interface bonding and good load transfer. Besides this gradient layer, uniformly dispersed Ti1-xAlxN nanoparticles were observed to precipitate, which can effectively hinder dislocation movement and refine grains. Furthermore, the pure Al and TiN/Al, AlN/Al composites were fabricated to compare and reveal the contributions of dual-phase (TiN+AlN) reinforcements. The tensile strength of the (TiN+AlN)/Al composite reach ∼254 MPa, improved by ∼75% and ∼81% compared with those of the TiN/Al and the AlN/Al composites, respectively. This novel microstructure about gradient layer and precipitated nanoparticles contributes to the high strengthening efficiency of the (TiN+AlN)/Al composite.

Correction: A novel nano delivery system targeting different stages of osteoclasts.

Correction for 'A novel nano delivery system targeting different stages of osteoclasts' by Bosong Zhang et al., Biomater. Sci., 2022, 10, 1821-1830, https://doi.org/10.1039/D2BM00076H.

Study of Acoustic Emission Signal Noise Attenuation Based on Unsupervised Skip Neural Network.

Acoustic emission (AE) technology, as a non-destructive testing methodology, is extensively utilized to monitor various materials' structural integrity. However, AE signals captured during experimental processes are often tainted with assorted noise factors that degrade the signal clarity and integrity, complicating precise analytical evaluations of the experimental outcomes. In response to these challenges, this paper introduces an unsupervised deep learning-based denoising model tailored for AE signals. It juxtaposes its efficacy against established methods, such as wavelet packet denoising, Hilbert transform denoising, and complete ensemble empirical mode decomposition with adaptive noise denoising. The results demonstrate that the unsupervised skip autoencoder model exhibits substantial potential in noise reduction, marking a significant advancement in AE signal processing. Subsequently, the paper focuses on applying this advanced denoising technique to AE signals collected during the tensile testing of steel fiber-reinforced concrete (SFRC), the tensile testing of steel, and flexural experiments of reinforced concrete beam, and it meticulously discusses the variations in the waveform and the spectrogram of the original signal and the signal after noise reduction. The results show that the model can also remove the noise of AE signals.

Genome-wide association study meta-analysis of neurofilament light (NfL) levels in blood reveals novel loci related to neurodegeneration.

Neurofilament light chain (NfL) levels in circulation have been established as a sensitive biomarker of neuro-axonal damage across a range of neurodegenerative disorders. Elucidation of the genetic architecture of blood NfL levels could provide new insights into molecular mechanisms underlying neurodegenerative disorders. In this meta-analysis of genome-wide association studies (GWAS) of blood NfL levels from eleven cohorts of European ancestry, we identify two genome-wide significant loci at 16p12 (UMOD) and 17q24 (SLC39A11). We observe association of three loci at 1q43 (FMN2), 12q14, and 12q21 with blood NfL levels in the meta-analysis of African-American ancestry. In the trans-ethnic meta-analysis, we identify three additional genome-wide significant loci at 1p32 (FGGY), 6q14 (TBX18), and 4q21. In the post-GWAS analyses, we observe the association of higher NfL polygenic risk score with increased plasma levels of total-tau, Aß-40, Aß-42, and higher incidence of Alzheimer's disease in the Rotterdam Study. Furthermore, Mendelian randomization analysis results suggest that a lower kidney function could cause higher blood NfL levels. This study uncovers multiple genetic loci of blood NfL levels, highlighting the genes related to molecular mechanism of neurodegeneration.

Genome-wide identification and expressional analysis of carotenoid cleavage oxygenase (CCO) gene family in Betula platyphylla under abiotic stress.

BACKGROUND: Carotenoid cleavage oxygenases (CCOs) are a group of enzymes that catalyze the oxidative cleavage of carotenoid molecules. These enzymes widely exist in plants, fungi, and certain bacteria, and are involved in various biological processes. It would be of great importance and necessity to identify CCO members in birch and characterize their responses upon abiotic stresses. RESULTS: A total of 16 BpCCOs, including 8 BpCCDs and 8 BpNCEDs were identified in birch, and phylogenetic tree analysis showed that they could be classified into six subgroups. Collinearity analysis revealed that BpCCOs have the largest number of homologous genes in Gossypium hirsutum and also have more homologous genes in other dicotyledons. In addition, promoter analysis revealed that the promoter regions of BpCCOs contained many abiotic stress-related and hormone-responsive elements. The results of qRT-PCR showed that most of the BpCCOs were able to respond significantly to ABA, PEG, salt and cold stresses. Finally, the prediction of the interacting proteins of BpCCOs by STRING revealed several proteins that may interact with BpCCOs and be involved in plant growth and development/abiotic stress processes, such as HEC1 (bHLH), ATABA1, ATVAMP714, etc. CONCLUSION: In this study, the CCO members were identified in birch in a genome-wide scale. These results indicate that BpCCO genes may play important roles in the abiotic stress responses of birch plants.

Quantification of heavy metal contamination and source in urban water sediments using a statistically determined geochemical baseline.

Geochemical baselines (GBs) play a crucial role in discerning natural variability from anthropogenic impacts on elemental composition within the environment. However, their applicability in quantifying the contribution of pollution sources to heavy metal contamination in sediments remains understudied. This research aimed to assess the degree of contamination and local pollution source attribution by leveraging geochemical baselines derived from statistical techniques, specifically the relative cumulative frequency (RCF) and 2σ-iterative (2σ-I) methods. In the urban water systems of Ma'anshan City, the major iron ore centre in eastern China, we observed concentration ranges of Cr, Cu, Ni, Pb and Zn in 36 sediment samples ranging from 66.89 to 352.08 mg/kg, 22.01 to 133.37 mg/kg, 22.66 to 50.80 mg/kg, 14.66to 264.37 mg/kg and 73.30 to 2707.46 mg/kg, respectively. RCF and 2σ-I techniques yielded similar GBs with no significant differences (p > 0.05). The geo-accumulation index and contamination factor analysis showed a sediment heavy metal accumulation rank of Zn > Pb > Cr > Cu > Ni. The contribution percentage of pollution sources varied with land functional type of watershed. For industry-influenced sediments, the contribution of local sources to Cr, Cu, Pb and Zn was significant, with shares of 43%-88%. Overall, this study highlights the valuable insights provided by GBs for effective management of urban aquatic environments.

A hybrid approach for modeling bicycle crash frequencies: Integrating random forest based SHAP model with random parameter negative binomial regression model.

To effectively capture and explain complex, nonlinear relationships within bicycle crash frequency data and account for unobserved heterogeneity simultaneously, this study proposes a new hybrid framework that combines the Random Forest-based SHapley Additive exPlanations (RF-SHAP) method with a random parameter negative binomial regression model (RPNB). First, four machine learning algorithms, including random forest (RF), support vector machine (SVM), gradient boosting machine (GBM), and Extreme Gradient Boosting (XGBoost), were compared for variable importance calculation. The RF algorithm, demonstrating the best performance, was selected and integrated into an interpretable machine learning-based method (i.e., RF-SHAP) to provide an interpretable measure of each variable's impact, which is critical for understanding the model's predictions results. Finally, the RF-SHAP method was combined with the RPNB model to explore individual-specific variations that influence crash frequency predictions. Using 288 traffic analysis zones (TAZs) in Greater London and various regional risk factors for bicycle crash frequency, the proposed framework was validated. The results indicate that the proposed framework demonstrates improved prediction accuracy and better factor interpretation in analyzing bicycle crash frequency. The model exhibits consistent Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values, indicating its reliable explanatory power. Furthermore, there is a significant improvement in the Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). This suggests that the proposed model effectively combines the explanatory power of statistical models with the forecasting powers of data-driven models. The interpretability of SHAP values, coupled with the causal insights from RPNB, provides policymakers with actionable information to develop targeted interventions.

Resting-state brain networks alterations in adolescents with Internet Gaming Disorder associate with cognitive control impairments.

Objective: Research indicates that cognitive control is compromised in individuals with internet gaming disorder (IGD). However, the neural mechanisms behind it are still unclear. This study aims to investigate alterations in resting-state brain networks in adolescents with IGD and the potential neurobiological mechanisms underlying cognitive dysfunction. Materials and methods: A total of 44 adolescent IGD subjects (male/female: 38/6) and 50 healthy controls (male/female: 40/10) were enrolled. Participants underwent demographic assessments, Young's Internet Addiction Scale, Barratt Impulsiveness Scale 11 Chinese Revised Version, the Chinese Adolescents' Maladaptive Cognitions Scale, exploratory eye movement tests, and functional magnetic resonance imaging (fMRI). FMRI data were analyzed using the GIFT software for independent component analysis, focusing on functional connectivity within and between resting-state brain networks. Results: In comparison to the control group, impulsivity in adolescent IGD subjects showed a positive correlation with the severity of IGD (r=0.6350, p < 0.001), linked to impairments in the Executive Control Network (ECN) and a decrease in functional connectivity between the Salience Network (SN) and ECN (r=0.4307, p=0.0021; r=-0.5147, p=0.0034). Decreased resting state activity of the dorsal attention network (DAN) was associated with attentional dysregulation of IGD in adolescents (r=0.4071, p=0.0017), and ECN increased functional connectivity with DAN. The degree of IGD was positively correlated with enhanced functional connectivity between the ECN and DAN (r=0.4283, p=0.0037). Conclusions: This research demonstrates that changes in the ECN and DAN correlate with heightened impulsivity and attentional deficits in adolescents with IGD. The interaction between cognitive control disorders and resting-state brain networks in adolescent IGD is related.

Cross-species single-cell spatial transcriptomic atlases of the cerebellar cortex.

The molecular and cellular organization of the primate cerebellum remains poorly characterized. We obtained single-cell spatial transcriptomic atlases of macaque, marmoset, and mouse cerebella and identified primate-specific cell subtypes, including Purkinje cells and molecular-layer interneurons, that show different expression of the glutamate ionotropic receptor Delta type subunit 2 (GRID2) gene. Distinct gene expression profiles were found in anterior, posterior, and vestibular regions in all species, whereas region-selective gene expression was predominantly observed in the granular layer of primates and in the Purkinje layer of mice. Gene expression gradients in the cerebellar cortex matched well with functional connectivity gradients revealed with awake functional magnetic resonance imaging, with more lobule-specific differences between primates and mice than between two primate species. These comprehensive atlases and comparative analyses provide the basis for understanding cerebellar evolution and function.

Quantifying the heterogeneity impact of risk factors on regional bicycle crash frequency: A hybrid approach of clustering and random parameter model.

The existence of internal and external heterogeneity has been established by numerous studies across various fields, including transportation and safety analysis. The findings from these studies underscore the complexity of crash data and the multifaceted nature of risk factors involved in accidents. However, most studies consider the effects of unobserved heterogeneity from one perspective -- either within clusters (internal) or between clusters (external) -- and do not investigate the biases from both simultaneously on crash frequency analysis. To fill this gap, this study proposes a hybrid approach combining latent class cluster analysis with the random parameter negative binomial regression model (LCA-RPNB) to explore the association between risk factors and bicycle crash frequency. First, the bicycle crash data is categorized into three clusters using LCA based on crash features such as gender, trip purposes, weather, and light conditions. Then, the separated crash frequency models for different clusters and the overall model are developed based on RPNB using regional factors of crash locations as independent variables and the crash frequency of different clusters respectively as dependent variables. The hybrid approach enables a comprehensive examination of internal and external heterogeneities among bicycle crash frequency factors simultaneously. Results suggest that the proposed hybrid approach exhibits superior fitting and predictive performance compared to the model only considers the effects of unobserved heterogeneity from one perspective with the lower values of Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). This approach can help policymakers and urban planners to design more effective safety interventions by understanding the distinct needs of different bicyclist clusters and the specific factors that contribute to crash risk in each group.

The study on 4D culture system of squamous cell carcinoma of tongue.

Traditional cell culture methods often fail to accurately replicate the intricate microenvironments crucial for studying specific cell growth patterns. In our study, we developed a 4D cell culture model-a precision instrument comprising an electromagnet, a force transducer, and a cantilever bracket. The experimental setup involves placing a Petri dish above the electromagnet, where gel beads encapsulating magnetic nanoparticles and tongue cancer cells are positioned. In this model, a magnetic force is generated on the magnetic nanoparticles in the culture medium to drive the gel to move and deform when the magnet is energized, thereby exerting an external force on the cells. This setup can mimic the microenvironment of tongue squamous cell carcinoma CAL-27 cells under mechanical stress induced by tongue movements. Electron microscopy and rheological analysis were performed on the hydrogels to confirm the porosity of alginate and its favorable viscoelastic properties. Additionally, Calcein-AM/PI staining was conducted to verify the biosafety of the hydrogel culture system. It mimics the microenvironment where tongue squamous cell carcinoma CAL-27 cells are stimulated by mechanical stress during tongue movement. Electron microscopy and rheological analysis experiments were conducted on hydrogels to assess the porosity of alginate and its viscoelastic properties. Calcein-AM/PI staining was performed to evaluate the biosafety of the hydrogel culture system. We confirmed that the proliferation of CAL-27 tongue squamous cells significantly increased with increased matrix stiffness after 5 d as assessed by MTT. After 15 d of incubation, the tumor spheroid diameter of the 1%-4D group was larger than that of the hydrogel-only culture. The Transwell assay demonstrated that mechanical stress stimulation and increased matrix stiffness could enhance cell aggressiveness. Flow cytometry experiments revealed a decrease in the number of cells in the resting or growth phase (G0/G1 phase), coupled with an increase in the proportion of cells in the preparation-for-division phase (G2/M phase). RT-PCR confirmed decreased expression levels of P53 and integrinß3 RNA in the 1%-4D group after 21 d of 4D culture, alongside significant increases in the expression levels of Kindlin-2 and integrinαv. Immunofluorescence assays confirmed that 4D culture enhances tissue oxygenation and diminishes nuclear aggregation of HIF-1α. This device mimics the microenvironment of tongue cancer cells under mechanical force and increased matrix hardness during tongue movement, faithfully reproducing cell growthin vivo, and offering a solid foundation for further research on the pathogenic matrix of tongue cancer and drug treatments.

Natriuretic peptide receptor-C perturbs mitochondrial respiration in white adipose tissue.

Natriuretic peptide receptor-C (NPR-C) is highly expressed in adipose tissues and regulates obesity-related diseases; however, the detailed mechanism remains unknown. In this research, we aimed to explore the potential role of NPR-C in cold exposure and high-fat/high-sugar (HF/HS) diet-induced metabolic changes, especially in regulating white adipose tissue (WAT) mitochondrial function. Our findings showed that NPR-C expression, especially in epididymal WAT (eWAT), was reduced after cold exposure. Global Npr3 (gene encoding NPR-C protein) deficiency led to reduced body weight, increased WAT browning, thermogenesis, and enhanced expression of genes related to mitochondrial biogenesis. RNA-sequencing of eWAT showed that Npr3 deficiency enhanced the expression of mitochondrial respiratory chain complex genes and promoted mitochondrial oxidative phosphorylation in response to cold exposure. In addition, Npr3 KO mice were able to resist obesity induced by HF/HS diet. Npr3 knockdown in stromal vascular fraction (SVF)-induced white adipocytes promoted the expression of proliferator-activated receptor gamma coactivator 1α (PGC1α), uncoupling protein one (UCP1), and mitochondrial respiratory chain complexes. Mechanistically, NPR-C inhibited cGMP and calcium signaling in an NPR-B-dependent manner but suppressed cAMP signaling in an NPR-B-independent manner. Moreover, Npr3 knockdown induced browning via AKT and p38 pathway activation, which were attenuated by Npr2 knockdown. Importantly, treatment with the NPR-C-specific antagonist, AP-811, decreased WAT mass and increased PGC-1α, UCP1, and mitochondrial complex expression. Our findings reveal that NPR-C deficiency enhances mitochondrial function and energy expenditure in white adipose tissue, contributing to improved metabolic health and resistance to obesity.

Integrating viruses into soil food web biogeochemistry.

The soil microbiome is recognized as an essential component of healthy soils. Viruses are also diverse and abundant in soils, but their roles in soil systems remain unclear. Here we argue for the consideration of viruses in soil microbial food webs and describe the impact of viruses on soil biogeochemistry. The soil food web is an intricate series of trophic levels that span from autotrophic microorganisms to plants and animals. Each soil system encompasses contrasting and dynamic physicochemical conditions, with labyrinthine habitats composed of particles. Conditions are prone to shifts in space and time, and this variability can obstruct or facilitate interactions of microorganisms and viruses. Because viruses can infect all domains of life, they must be considered as key regulators of soil food web dynamics and biogeochemical cycling. We highlight future research avenues that will enable a more robust understanding of the roles of viruses in soil function and health.

Intelligent diagnosis of Kawasaki disease from real-world data using interpretable machine learning models.

OBJECTIVE: This study aimed to leverage real-world electronic medical record data to develop interpretable machine learning models for diagnosis of Kawasaki disease while also exploring and prioritizing the significant risk factors. METHODS: A comprehensive study was conducted on 4087 pediatric patients at the Children's Hospital of Chongqing, China. The study collected demographic data, physical examination results, and laboratory findings. Statistical analyses were performed using IBM SPSS Statistics, Version 26.0. The optimal feature subset was used to develop intelligent diagnostic prediction models based on the Light Gradient Boosting Machine, Explainable Boosting Machine (EBM), Gradient Boosting Classifier (GBC), Fast Interpretable Greedy-Tree Sums, Decision Tree, AdaBoost Classifier, and Logistic Regression. Model performance was evaluated in three dimensions: discriminative ability via receiver operating characteristic curves, calibration accuracy using calibration curves, and interpretability through SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-Agnostic Explanations). RESULTS: In this study, Kawasaki disease was diagnosed in 2971 participants. Analysis was conducted on 31 indicators, including red blood cell distribution width and erythrocyte sedimentation rate. The EBM model demonstrated superior performance relative to other models, with an area under the curve of 0.97, second only to the GBC model. Furthermore, the EBM model exhibited the highest calibration accuracy and maintained its interpretability without relying on external analytical tools such as SHAP and LIME, thus reducing interpretation biases. Platelet distribution width, total protein, and erythrocyte sedimentation rate were identified by the model as significant predictors for the diagnosis of Kawasaki disease. CONCLUSION: This study used diverse machine learning models for early diagnosis of Kawasaki disease. The findings demonstrated that interpretable models such as EBM outperformed traditional machine learning models in terms of both interpretability and performance. Ensuring consistency between predictive models and clinical evidence is crucial for the successful integration of artificial intelligence into real-world clinical practice.

Genome-wide identification and expression analysis of the U-box E3 ubiquitin ligase gene family related to bacterial wilt resistance in tobacco (Nicotiana tabacum L.) and eggplant (Solanum melongena L.).

The E3 enzyme in the UPS pathway is a crucial factor for inhibiting substrate specificity. In Solanaceae, the U-box E3 ubiquitin ligase has a complex relationship with plant growth and development, and plays a pivotal role in responding to various biotic and abiotic stresses. The analysis of the U-box gene family in Solanaceae and its expression profile under different stresses holds significant implications. A total of 116 tobacco NtU-boxs and 56 eggplant SmU-boxs were identified based on their respective genome sequences. Phylogenetic analysis of U-box genes in tobacco, eggplant, tomato, Arabidopsis, pepper, and potato revealed five distinct subgroups (I-V). Gene structure and protein motifs analysis found a high degree of conservation in both exon/intron organization and protein motifs among tobacco and eggplant U-box genes especially the members within the same subfamily. A total of 15 pairs of segmental duplication and 1 gene pair of tandem duplication were identified in tobacco based on the analysis of gene duplication events, while 10 pairs of segmental duplication in eggplant. It is speculated that segmental duplication events are the primary driver for the expansion of the U-box gene family in both tobacco and eggplant. The promoters of NtU-box and SmU-box genes contained cis-regulatory elements associated with cellular development, phytohormones, environment stress, and photoresponsive elements. Transcriptomic data analysis shows that the expression levels of the tobacco and eggplant U-box genes in different tissues and various abiotic stress conditions. Using cultivar Hongda of tobacco and cultivar Yanzhi of eggplant as materials, qRT-PCR analysis has revealed that 15 selected NtU-box genes and 8 SmU-box may play important roles in response to pathogen Ras invasion both in tobacco and eggplant.

Calcium homeostasis and endometriosis: A Mendelian randomization study.

Background: Previous observational studies have investigated the correlation between calcium homeostasis modulator levels and endometriosis risk. Yet, the genetic association between body calcium homeostasis and endometriosis risk remains to be elucidated. Methods: Four tiers of Mendelian randomization (MR) analysis were conducted, as follows: (1) single univariate MR and (2) multivariate MR to evaluate the correlation between calcium homeostasis regulators and endometriosis; (3) inverse MR to probe the influence of endometriosis on body calcium homeostasis; (4) two-sample MR to scrutinize the connection between calcium levels and endometriosis categories. Results: The two-sample MR analysis unveiled a robust positive correlation between genetically inferred calcium levels and endometriosis risk (IVW: OR = 1.15, 95 % CI: 1.02-1.29, p = 0.018). The MVMR analysis corroborated that the positive correlation of calcium levels with endometriosis persisted after adjusting for 25(OH)D and PTH. The inverse MR analysis disclosed a significant association between endometriosis and 25(OH)D (ß = 0.01, 95 % CI: 0.00-0.02, p = 0.007) and calcium (ß = 0.02, 95 % CI: 0.00-0.04, p = 0.035). The two-sample MR analysis further demonstrated that calcium levels were positively linked solely to endometriosis of uterus (i.e. adenomyosis, IVW: OR = 1.23, 95 % CI: 1.01-1.49, p = 0.038), with no evidence of a influence on other endometriosis categories. Conclusions: This study, employing various types of MR, offers some genetic evidence for the relationship between calcium homeostasis and endometriosis, augmenting the current comprehension of the complex association between the two and suggesting that calcium levels are a risk factor for endometriosis. These findings provide a unique genetic perspective that may spur further investigation and may inform future strategies for managing patients with endometriosis.

IGF2BP3 participates in the pathogenesis of recurrent spontaneous abortion by regulating ferroptosis.

The aberrant invasive capability of trophoblast cells is widely acknowledged as a primary mechanism underlying RSA. Recently, IGF2BP3 has been implicated in various cancers due to its influence on cellular invasion and migration. However, whether IGF2BP3 involve in the occurrence of RSA and the specific functions it assumes in the development of RSA remain elusive. In our study, we firstly collected villous tissues from RSA and those with normal pregnancies individuals to performed Protein sequencing and then detected the expression of IGF2BP3 through Western blot, qRT-PCR and immunohistochemistry. Secondly, we analyzed the single-cell data (GSE214607) to assess the expression of IGF2BP3 in invasive EVT trophoblasts. Thirdly, we utilized lentivirus technology to establish HTR-8/SVneo cell lines with stable IGF2BP3 knockdown and RNA-seq analysis was employed to investigate the GO functional pathway enrichment of IGF2BP3. Meanwhile, the effect of IGF2BP3 knockdown on trophoblast cells apoptosis, migration, and ferroptosis was evaluated through functional experiments. Additionally, LPS-induced abortion animal model was constructed to evaluate IGF2BP3 expression in placental tissues. A significant downregulation of IGF2BP3 was observed in the villous tissues of RSA patient, a finding corroborated by subsequent single cell sequencing results. Furthermore, it suggested that IGF2BP3 may be involved in the migration and apoptotic processes of trophoblast cells. Mechanistic research indicated that IGF2BP3 knockdown could compromise GPX4 mRNA stability, leading to the promotion of ferroptosis. Finally, our investigation observed the down-regulation of IGF2BP3 expression in placental villous tissues of an LPS-induced abortion animal model. Our findings revealed that IGF2BP3 was downregulated in the villous tissues of RSA patients. Mechanically, down-regulation of IGF2BP3 may induce RSA by promoting GPX4-mediated ferroptosis and inhibiting trophoblast invasion and migration. Our study may provide new targets and research directions for the pathogenesis of RSA.

Baicalein suppresses Coxsackievirus B3 replication by inhibiting caspase-1 and viral protease 2A.

Myocarditis is an inflammatory disease of the cardiac muscle and one of the primary causes of dilated cardiomyopathy. Group B coxsackievirus (CVB) is one of the leading causative pathogens of viral myocarditis, which primarily affects children and young adults. Due to the lack of vaccines, the development of antiviral medicines is crucial to controlling CVB infection and the progression of myocarditis. In this study, we investigated the antiviral effect of baicalein, a flavonoid extracted from Scutellaria baicaleinsis. Our results demonstrated that baicalein treatment significantly reduced cytopathic effect and increased cell viability in CVB3-infected cells. In addition, significant reductions in viral protein 3D, viral RNA, and viral particles were observed in CVB3-infected cells treated with baicalein. We found that baicalein exerted its inhibitory effect in the early stages of CVB3 infection. Baicalein also suppressed viral replication in the myocardium and effectively alleviated myocarditis induced by CVB3 infection. Our study revealed that baicalein exerts its antiviral effect by inhibiting the activity of caspase-1 and viral protease 2A. Taken together, our findings demonstrate that baicalein has antiviral activity against CVB3 infection and may serve as a potential therapeutic option for the myocarditis caused by enterovirus infection.