One-stop detection of anterior cruciate ligament injuries on magnetic resonance imaging using deep learning with multicenter validation.

Background: Anterior cruciate ligament (ACL) injuries are closely associated with knee osteoarthritis (OA). However, diagnosing ACL injuries based on knee magnetic resonance imaging (MRI) has been subjective and time-consuming for clinical doctors. Therefore, we aimed to devise a deep learning (DL) model leveraging MRI to enable a comprehensive and automated approach for the detection of ACL injuries. Methods: A retrospective study was performed extracting data from the Osteoarthritis Initiative (OAI). A total of 1,589 knees (comprising 1,443 intact, 90 with partial tears, and 56 with full tears) were enrolled to construct the classification model. This one-stop detection pipeline was developed using a tailored YOLOv5m architecture and a ResNet-18 convolutional neural network (CNN) to facilitate tasks based on sagittal 2-dimensional (2D) intermediate-weighted fast spin-echo sequence at 3.0T. To ensure the reliability and robustness of the classification system, it was subjected to external validation across 3 distinct datasets. The accuracy, sensitivity, specificity, and the mean average precision (mAP) were utilized as the evaluation metric for the model performance by employing a 5-fold cross-validation approach. The radiologist's interpretations were employed as the reference for conducting the evaluation. Results: The localization model demonstrated an accuracy of 0.89 and a sensitivity of 0.93, achieving a mAP score of 0.96. The classification model demonstrated strong performance in detecting intact, partial tears, and full tears at the optimal threshold on the internal dataset, with sensitivities of 0.941, 0.833, and 0.929, specificities of 0.925, 0.947, and 0.991, and accuracies of 0.940, 0.941, and 0.989, respectively. In comparison, on a subset consisting of 171 randomly selected knees from the OAI, the radiologists demonstrated a sensitivity ranging between 0.660 and 1.000, specificity ranging between 0.691 and 1.000, and accuracy ranging between 0.689 and 1.000. On a subset consisting of 170 randomly selected knees from the Chinese dataset, the radiologists exhibited a sensitivity ranging between 0.711 and 0.948, specificity ranging between 0.768 and 0.977, and accuracy ranging between 0.683 and 0.917. After retraining, the model achieved sensitivities ranging between 0.630 and 0.961, specificities ranging between 0.860 and 0.961, and accuracies ranging between 0.832 and 0.951, respectively, on the external validation dataset. Conclusions: The proposed model utilizing knee MRI showcases robust performance in the domains of ACL localization and classification.

Bioinformatics Analysis of Hub Genes in Craniofacial Microsomia Combined With Congenital Heart Disease.

OBJECTIVE: The primary objective of this study was to investigate potential mechanisms and explore hub genes of craniofacial microsomia (CFM) patients associated with congenital heart defects (CHD). METHODS: Initially, the authors acquired target gene data related to CFM and congenital cardiac anomalies. Subsequently, the authors established a protein-protein interaction (PPI) network. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and molecular complex detection were conducted using Metascape. Finally, the authors hub genes were screened by the cytoHubba plugin. RESULTS: A total of 43 CFM genes and 120 optimal CHD candidate genes were selected. The PPI networks for pathogenic genes contained 163 nodes and 1179 edges. Functional enrichment analysis largely focused on tissue formation and development. Five modules were identified from the PPI network, and 7 hub genes were screened out. The genes most relevant to CFM associated with congenital cardiac anomalies pathogenesis included fibroblast growth factor 3, GATA binding protein 3, nuclear factor of activated T cells 1, histone cell cycle regulator, EPAS1, mitogen-activated protein kinase 1, and CRK like proto-oncogene, adaptor protein. CONCLUSIONS: This study identified some significant hub genes, pathways, and modules of CFM associated with CHD by bioinformatics analyses. Our findings indicate that gene subfamilies fibroblast growth factor 3, GATA binding protein 3, nuclear factor of activated T cells 1, histone cell cycle regulator, EPAS1, mitogen-activated protein kinase 1, and CRK like proto-oncogene, adaptor protein may have had significant involvement in both CFM and CHD.

Qualitative Immunoglobulin Deficiency Causes Bacterial Infections in Patients with STAT1 Gain-of-Function Mutations.

PURPOSES: STAT1 is a transduction and transcriptional regulator that functions within the classical JAK/STAT pathway. In addition to chronic mucocutaneous candidiasis, bacterial infections are a common occurrence in patients with STAT1 gain-of-function (GOF) mutations. These patients often exhibit skewing of B cell subsets; however, the impact of STAT1-GOF mutations on B cell-mediated humoral immunity remains largely unexplored. It is also unclear whether these patients with IgG within normal range require regular intravenous immunoglobulin (IVIG) therapy. METHODS: Eleven patients (harboring nine different STAT1-GOF mutations) were enrolled. Reporter assays and immunoblot analyses were performed to confirm STAT1 mutations. Flow cytometry, deep sequencing, ELISA, and ELISpot were conducted to assess the impact of STAT1-GOF on humoral immunity. RESULTS: All patients exhibited increased levels of phospho-STAT1 and total STAT1 protein, with two patients carrying novel mutations. In vitro assays showed that these two novel mutations were GOF mutations. Three patients with normal total IgG levels received regular IVIG infusions, resulting in effective control of bacterial infections. Four cases showed impaired affinity and specificity of pertussis toxin-specific antibodies, accompanied by reduced generation of class-switched memory B cells. Patients also had a disrupted immunoglobulin heavy chain (IGH) repertoire, coupled with a marked reduction in the somatic hypermutation frequency of switched Ig transcripts. CONCLUSION: STAT1-GOF mutations disrupt B cell compartments and skew IGH characteristics, resulting in impaired affinity and antigen-specificity of antibodies and recurrent bacterial infections. Regular IVIG therapy can control these infections in patients, even those with normal total IgG levels.

The impact of omitting confounders in parallel process latent growth curve mediation models: Three sensitivity analysis approaches.

Parallel process latent growth curve mediation models (PP-LGCMMs) are frequently used to longitudinally investigate the mediation effects of treatment on the level and change of outcome through the level and change of mediator. An important but often violated assumption in empirical PP-LGCMM analysis is the absence of omitted confounders of the relationships among treatment, mediator, and outcome. In this study, we analytically examined how omitting pretreatment confounders impacts the inference of mediation from the PP-LGCMM. Using the analytical results, we developed three sensitivity analysis approaches for the PP-LGCMM, including the frequentist, Bayesian, and Monte Carlo approaches. The three approaches help investigate different questions regarding the robustness of mediation results from the PP-LGCMM, and handle the uncertainty in the sensitivity parameters differently. Applications of the three sensitivity analyses are illustrated using a real-data example. A user-friendly Shiny web application is developed to conduct the sensitivity analyses.

A portable transistor immunosensor for fast identification of porcine epidemic diarrhea virus.

Widespread distribution of porcine epidemic diarrhea virus (PEDV) has led to catastrophic losses to the global pig farming industry. As a result, there is an urgent need for rapid, sensitive and accurate tests for PEDV to enable timely and effective interventions. In the present study, we develop and validate a floating gate carbon nanotubes field-effect transistor (FG CNT-FET)-based portable immunosensor for rapid identification of PEDV in a sensitive and accurate manner. To improve the affinity, a unique PEDV spike protein-specific monoclonal antibody is prepared by purification, and subsequently modified on FG CNT-FET sensor to recognize PEDV. The developed FET biosensor enables highly sensitive detection (LoD: 8.1 fg/mL and 100.14 TCID50/mL for recombinant spike proteins and PEDV, respectively), as well as satisfactory specificity. Notably, an integrated portable platform consisting of a pluggable FG CNT-FET chip and a portable device can discriminate PEDV positive from negative samples and even identify PEDV and porcine deltacoronavirus within 1 min with 100% accuracy. The portable sensing platform offers the capability to quickly, sensitively and accurately identify PEDV, which further points to a possibility of point of care (POC) applications of large-scale surveillance in pig breeding facilities.

The standardized training and assessment system for magnetically controlled capsule gastroscopy (with video).

BACKGROUND AND AIM: To explore the feasibility of a standardized training and assessment system for magnetically controlled capsule gastroscopy (MCCG). METHODS: The results of 90 trainees who underwent the standardized training and assessment system of the MCCG at the First Affiliated Hospital of Xi'an Jiaotong University from May 2020 to November 2023 was retrospectively analyzed. The trainees were divided into three groups according to their medical backgrounds: doctor, nurse, and non-medical groups. The training and assessment system adopted the '7 + 2' mode, seven days of training plus two days of theoretical and operational assessment. The passing rates of theoretical, operational, and total assessment were the primary outcomes. Satisfaction and mastery of the MCCG was checked. RESULTS: Ninety trainees were assessed; theoretical assessment's passing rates in the three groups were 100%. The operational and total assessment passing rates were 100% (25/25), 97.92% (47/48), and 94.12% (16/17), for the doctor, nurse, and non-doctor groups respectively, with no significant difference (χ2 = 1.741, p = 0.419). No bleeding or perforation occurred during the procedure. Approximately, 96.00% (24/25), 95.83% (46/48), and 94.12% (16/17) of the doctor, nurse and non-medical groups anonymously expressed great satisfaction, respectively, without statistically significant difference (χ2 = 0.565, p = 1.000). The average follow-up time was 4-36 months, and 87 trainees (96.67%) had mastered the operation of the MCCG in daily work. CONCLUSIONS: Standardized training and assessment of magnetically controlled capsule endoscopists is effective and feasible. Additionally, a strict assessment system and long-term communication and learning can improve teaching effects.

Experimental research on the impact pressure of tidal bore fronts.

Tidal bore impact can be strong and destructive, placing estuarine infrastructures under great threat. However, there is a lack of research focusing on accurately estimating the impact pressure exerted by tidal bores. Herein new experiments were conducted to investigate the pressure of tidal bore fronts in a glass flume. Through analysis of instantaneous pressure of three forms of tidal bore, it was observed that the pressure fluctuation of weak and strong breaking bore fronts is characterized by impact pressure. The vertical distribution and maximum impact pressure of tidal bore were studied.The maximum impact pressure of breaking bore fronts appeared around 0.46 times height of it. The relationship between relative impact pressure and height of the tidal bore fronts was found to closely follow a normal probability density function. Through nonlinear regression analysis, an empirical equation was derived to calculate impact pressure, which was validated using observation data from the Qiantang River in China. This equation can be utilized to predict the impact pressure of tidal bore fronts and provide valuable support for estuarine engineering design.

Multi-omics reveal disturbance of glucose homeostasis in pregnant rats exposed to short-chain perfluorobutanesulfonic acid.

Perfluorobutanesulfonic acid (PFBS), a short-chain alternative to perfluorooctanesulfonic acid (PFOS), is widely used in various products and is increasingly present in environmental media and human bodies. Recent epidemiological findings have raised concerns about its potential adverse health effects, although the specific toxic mechanism remains unclear. This study aimed to investigate the metabolic toxicity of gestational PFBS exposure in maternal rats. Pregnant Sprague Dawley (SD) rats were randomly assigned to three groups and administered either 3% starch gel (control), 5, or 50 mg/kg bw·d PFBS. Oral glucose tolerance tests (OGTT) and lipid profiles were measured, and integrated omics analysis (transcriptomics and non-targeted metabolomics) was employed to identify changes in genes and metabolites and their relationships with metabolic phenotypes. The results revealed that rats exposed to 50 mg/kg bw·d PFBS exhibited a significant decrease in 1-h glucose levels and the area under the curve (AUC) of OGTT compared with the starch group. Transcriptomics analysis indicated significant alterations in gene expression related to cytochrome P450 exogenous metabolism, glutathione metabolism, bile acid secretion, tumor pathways, and retinol metabolism. Differentially expressed metabolites (DEMs) were enriched in pathways such as pyruvate metabolism, the glucagon signaling pathway, central carbon metabolism in cancer, and the citric acid cycle. Co-enrichment analysis and pairwise correlation analysis among genes, metabolites, and outcomes identified several differentially expressed genes (DEGs), including Gstm1, Kit, Adcy1, Gck, Ppp1r3c, Ppp1r3d, and DEMs such as fumaric acid, L-lactic acid, 4-hydroxynonenal, and acetylvalerenolic acid. These DEGs and DEMs may play a role in the modulation of glucolipid metabolic pathways. In conclusion, our results suggest that gestational exposure to PFBS may induce molecular perturbations in glucose homeostasis. These findings provide insights into the potential mechanisms contributing to the heightened risk of abnormal glucose tolerance associated with PFBS exposure.

Atypical familial hemophagocytic lymphohistiocytosis type 3 in children: A report of cases and literature review.

BACKGROUND: Familial hemophagocytic lymphohistiocytosis type 3 (FHL3) is caused by UNC13D variants. The clinical manifestations of FHL3 are highly diverse and complex. Some patients exhibit atypical or incomplete phenotypes, making accurate diagnosis difficult. Our study aimed to broaden the understanding of the atypical FHL3 clinical spectrum. METHODS: In our study, we analyzed in detail the clinical features of four Chinese patients with UNC13D variants. Additionally, we conducted a comprehensive review of the existing literature on previously reported atypical manifestations and summarized the findings. RESULTS: Two of our patients presented with muscle involvement, while the other two had hematological involvement; none of them met the diagnostic criteria for hemophagocytic lymphohistiocytosis (HLH). However, protein expression and functional analysis ultimately confirmed diagnostic criteria for FHL3 in all patients. From the literature we reviewed, many atypical FHL3 patients had neurological involvement, especially isolated neurological manifestations. At the same time, arthritis and hypogammaglobulinemia were also prone to occur. CONCLUSION: Our study highlights that the expression of the Munc13-4 protein may not fully indicate the pathogenicity of UNC13D variants, whereas CD107a analysis could be more sensitive for disease diagnosis. These findings contribute to a broader understanding of the FHL3 clinical spectrum and may offer new insights into the underlying pathogenesis of UNC13D variants. It is crucial to prioritize the timely and accurate diagnosis of atypical patients, as they may often be overlooked among individuals with rheumatic or hematological diseases.

Detecting mediation effects with the Bayes factor: Performance evaluation and tools for sample size determination.

Testing the presence of mediation effects is important in social science research. Recently, Bayesian hypothesis testing with Bayes factors (BFs) has become increasingly popular. However, the use of BFs for testing mediation effects is still under-studied, despite the growing literature on Bayesian mediation analysis. In this study, we systematically examine the performance of the BF for testing the presence versus absence of a mediation effect. Our results showed that the false and/or true positive rates of detecting mediation with the BF can be impacted by the prior specification, including the prior odds of the presence of each path (treatment-mediator path or mediator-outcome path) used in the design stage for data generation and in the analysis stage for calculating the BF of the mediation effect. Based on our examination, we developed an R function and a web application to determine sample sizes for testing mediation effects with the BF. Our study provides insights on the performance of the BF for testing mediation effects and adds to researchers' toolbox of sample size determination for mediation studies. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Knowledge graph and development hotspots of biochar as an emerging aquatic antibiotic remediator: A scientometric exploration based on VOSviewer and CiteSpace.

As an emerging material in the field of environmental remediation, biochar produced by carbonisation of organic solid waste has been widely used in the remediation of antibiotic wastewater due to its environmental friendliness and excellent adsorption properties. This study analyses the current literature in the field in a comprehensive and scientific manner using CiteSpace and VOSviewer technologies. Between 2011 and 2023, a total of 1162 papers were published in this domain, spanning three distinct stages: applied methods, mechanism investigation, and enhanced improvement. The results of keyword clustering indicate that the remediation of antibiotics complexed with multiple pollutants by biochar is the main research topic, followed by the remediation of antibiotics by biochar in combination with other technologies. Furthermore, drawing from current research hotspots in antibiotic remediation using biochar, this study identified the pivotal mechanisms involved: (1) The primary mechanisms by which raw biochar remediates antibiotics include π-π electron donor-acceptor interactions, hydrophobic interactions, electrostatic interactions, hydrogen-bonding, and pore filling. (2) Steam activation, acid/base, metal salt/metal oxide, and clay mineral modification can improve the physical/chemical properties of biochar, enhancing its adsorptive removal of antibiotics. (3) Biochar activated persulfate and degraded antibiotics via free radical pathways (SO4-•, •OH and O2-•) as well as non-free radical pathways (1O2 and electron transfer). In addition, the challenge and prospect of biochar engineering applications for antibiotic remediation lies in improving the main mechanism of antibiotic remediation by biochar. The prospective utilization of biochar in enhancing the remediation of antibiotic-related pollutants holds tremendous value for the future.

A subject-specific unsupervised deep learning method for quantitative susceptibility mapping using implicit neural representation.

Quantitative susceptibility mapping (QSM) is an MRI-based technique that estimates the underlying tissue magnetic susceptibility based on phase signal. Deep learning (DL)-based methods have shown promise in handling the challenging ill-posed inverse problem for QSM reconstruction. However, they require extensive paired training data that are typically unavailable and suffer from generalization problems. Recent model-incorporated DL approaches also overlook the non-local effect of the tissue phase in applying the source-to-field forward model due to patch-based training constraint, resulting in a discrepancy between the prediction and measurement and subsequently suboptimal QSM reconstruction. This study proposes an unsupervised and subject-specific DL method for QSM reconstruction based on implicit neural representation (INR), referred to as INR-QSM. INR has emerged as a powerful framework for learning a high-quality continuous representation of the signal (image) by exploiting its internal information without training labels. In INR-QSM, the desired susceptibility map is represented as a continuous function of the spatial coordinates, parameterized by a fully-connected neural network. The weights are learned by minimizing a loss function that includes a data fidelity term incorporated by the physical model and regularization terms. Additionally, a novel phase compensation strategy is proposed for the first time to account for the non-local effect of tissue phase in data consistency calculation to make the physical model more accurate. Our experiments show that INR-QSM outperforms traditional established QSM reconstruction methods and the compared unsupervised DL method both qualitatively and quantitatively, and is competitive against supervised DL methods under data perturbations.

The Tandem Nitrate and CO2 Reduction for Urea Electrosynthesis: Role of Surface N-Intermediates in CO2 Capture and Activation.

Electrochemical reduction of CO2 and nitrate offers a promising avenue to produce valuable chemicals through the using of greenhouse gas and nitrogen-containing wastewater. However, the generally proposed reaction pathway of concurrent CO2 and nitrate reduction for urea synthesis requires the catalysts to be both efficient in both CO2 and nitrate reduction, thus narrowing the selection range of suitable catalysts. Herein, we demonstrate a distinct mechanism in urea synthesis, a tandem NO3 - and CO2 reduction, in which the surface amino species generated by nitrate reduction play the role to capture free CO2 and subsequent initiate its activation. When using the TiO2 electrocatalyst derived from MIL-125-NH2, it intrinsically exhibits low activity in aqueous CO2 reduction, however, in the presence of both nitrate and CO2, this catalyst achieves an excellent urea yield rate of 43.37 mmol ⋅ g-1 ⋅ h-1 and a Faradaic efficiency of 48.88 % at -0.9 V vs. RHE in a flow cell. Even at a low CO2 level of 15 %, the Faradaic efficiency of urea synthesis remains robust at 42.33 %. The tandem reduction procedure was further confirmed by in situ spectroscopies and theoretical calculations. This research provides new insights into the selection and design of electrocatalysts for urea synthesis.

Association between multiple-heavy-metal exposures and systemic immune inflammation in a middle-aged and elderly Chinese general population.

BACKGROUND: Exposure to heavy metals alone or in combination can promote systemic inflammation. The aim of this study was to investigate potential associations between multiple plasma heavy metals and markers of systemic immune inflammation. METHODS: Using a cross-sectional study, routine blood tests were performed on 3355 participants in Guangxi, China. Eight heavy metal elements in plasma were determined by inductively coupled plasma mass spectrometry. Immunoinflammatory markers were calculated based on peripheral blood WBC and its subtype counts. A generalised linear regression model was used to analyse the association of each metal with the immunoinflammatory markers, and the association of the metal mixtures with the immunoinflammatory markers was further assessed using weighted quantile sum (WQS) regression. RESULTS: In the single-metal model, plasma metal Fe (log10) was significantly negatively correlated with the levels of immune-inflammatory markers SII, NLR and PLR, and plasma metal Cu (log10) was significantly positively correlated with the levels of immune-inflammatory markers SII and PLR. In addition, plasma metal Mn (log10 conversion) was positively correlated with the levels of immune inflammatory markers NLR and PLR. The above associations remained after multiple corrections. In the mixed-metal model, after WQS regression analysis, plasma metal Cu was found to have the greatest weight in the positive effects of metal mixtures on SII and PLR, while plasma metals Mn and Fe had the greatest weight in the positive effects of metal mixtures on NLR and LMR, respectively. In addition, blood Fe had the greatest weight in the negative effects of the metal mixtures for SII, PLR and NLR. CONCLUSION: Plasma metals Cu and Mn were positively correlated with immunoinflammatory markers SII, NLR and PLR. While plasma metal Fe was negatively correlated with immunoinflammatory markers SII, NLR, and PLR.

Spatiotemporal encoding MRI in a portable low-field system.

PURPOSE: Demonstrate the potential of spatiotemporal encoding (SPEN) MRI to deliver largely undistorted 2D, 3D, and diffusion weighted images on a 110 mT portable system. METHODS: SPEN's quadratic phase modulation was used to subsample the low-bandwidth dimension of echo planar acquisitions, delivering alias-free images with an enhanced immunity to image distortions in a laboratory-built, low-field, portable MRI system lacking multiple receivers. RESULTS: Healthy brain images with different SPEN time-bandwidth products and subsampling factors were collected. These compared favorably to EPI acquisitions including topup corrections. Robust 3D and diffusion weighted SPEN images of diagnostic value were demonstrated, with 2.5 mm isotropic resolutions achieved in 3 min scans. This performance took advantage of the low specific absorption rate and relative long TEs associated with low-field MRI. CONCLUSION: SPEN MRI provides a robust and advantageous fast acquisition approach to obtain faithful 3D images and DWI data in low-cost, portable, low-field systems without parallel acceleration.

Exciton polariton condensation from bound states in the continuum at room temperature.

Exciton-polaritons (polaritons) resulting from the strong exciton-photon interaction stimulates the development of novel low-threshold coherent light sources to circumvent the ever-increasing energy demands of optical communications1-3. Polaritons from bound states in the continuum (BICs) are promising for Bose-Einstein condensation owing to their theoretically infinite quality factors, which provide prolonged lifetimes and benefit the polariton accumulations4-7. However, BIC polariton condensation remains limited to cryogenic temperatures ascribed to the small exciton binding energies of conventional material platforms. Herein, we demonstrated room-temperature BIC polariton condensation in perovskite photonic crystal lattices. BIC polariton condensation was demonstrated at the vicinity of the saddle point of polariton dispersion that generates directional vortex beam emission with long-range coherence. We also explore the peculiar switching effect among the miniaturized BIC polariton modes through effective polariton-polariton scattering. Our work paves the way for the practical implementation of BIC polariton condensates for integrated photonic and topological circuits.

A bibliometric and visual analysis of cognitive function in bipolar disorder from 2012 to 2022.

INTRODUCTION: Bipolar disorder (BD) is a chronic psychiatric disorder that combines hypomania or mania and depression. The study aims to investigate the research areas associated with cognitive function in bipolar disorder and identify current research hotspots and frontier areas in this field. METHODOLOGY: Publications related to cognitive function in BD from 2012 to 2022 were searched on the Web of Science Core Collection (WoSCC) database. VOSviewer, CiteSpace, and Scimago Graphica were used to conduct this bibliometric analysis. RESULTS: A total of 989 articles on cognitive function in BD were included in this review. These articles were mainly from the United States, China, Canada, Spain and the United Kingdom. Our results showed that the journal "Journal of Affective Disorders" published the most articles. Apart from "Biploar disorder" and "cognitive function", the terms "Schizophrenia", "Meta analysis", "Rating scale" were also the most frequently used keywords. The research on cognitive function in bipolar disorder primarily focused on the following aspects: subgroup, individual, validation and pathophysiology. CONCLUSIONS: The current concerns and hotspots in the filed are: "neurocognitive impairment", "subgroup", "1st degree relative", "mania", "individual" and "validation". Future research is likely to focus on the following four themes: "Studies of the bipolar disorder and cognitive subgroups", "intra-individual variability", "Validation of cognitive function tool" and "Combined with pathology or other fields".

Associations of Heavy Metals with Cognitive Function: An Epigenome-Wide View of DNA Methylation and Mediation Analysis.

OBJECTIVE: Exposure to heavy metals has been reported to be associated with impaired cognitive function, but the underlying mechanisms remain unclear. This pilot study aimed to identify key heavy metal elements associated with cognitive function and further explore the potential mediating role of metal-related DNA methylation. METHODS: Blood levels of arsenic, cadmium, lead, copper, manganese, and zinc and genome-wide DNA methylations were separately detected in peripheral blood in 155 older adults. Cognitive function was evaluated using the Mini-Mental State Examination (MMSE). Least absolute shrinkage and selection operator penalized regression and Bayesian kernel machine regression were used to identify metals associated with cognitive function. An epigenome-wide association study examined the DNA methylation profile of the identified metal, and mediation analysis investigated its mediating role. RESULTS: The MMSE scores showed a significant decrease of 1.61 (95% confidence interval [CI]: -2.64, -0.59) with each 1 standard deviation increase in ln-transformed arsenic level; this association was significant in multiple-metal models and dominated the overall negative effect of 6 heavy metal mixture on cognitive function. Seventy-three differentially methylated positions were associated with blood arsenic (p < 1.0 × 10-5). The methylation levels at cg05226051 (annotated to TDRD3) and cg18886932 (annotated to GAL3ST3) mediated 24.8% and 25.5% of the association between blood arsenic and cognitive function, respectively (all p < 0.05). INTERPRETATION: Blood arsenic levels displayed a negative association with the cognitive function of older adults. This finding shows that arsenic-related DNA methylation alterations are critical partial mediators that may serve as potential biomarkers for further mechanism-related studies. ANN NEUROL 2024.

Mitochondria-mediated ferroptosis induced by CARD9 ablation prevents MDSCs-dependent antifungal immunity.

BACKGROUND: Caspase Recruitment Domain-containing protein 9 (CARD9) expressed in myeloid cells has been demonstrated to play an antifungal immunity role in protecting against disseminated candidiasis. Hereditary CARD9 ablation leads to fatal disseminated candidiasis. However, the myeloid cell types and molecular mechanisms implicated in CARD9 protecting against disseminated candidiasis remain wholly elusive. METHODS: The role of CARD9 ablation in exacerbating disseminated candidiasis was determined in vivo and in vitro. The molecular mechanism by which CARD9 ablation promotes acute kidney injury in disseminated candidiasis was identified by RNA-sequencing analysis. The expression of mitochondrial proteins and ferroptosis-associated proteins were measured by Quantitative real-time PCR and western blot. RESULTS: CARD9 ablation resulted in a reduced proportion of myeloid-derived suppressor cells (MDSCs) and a substantially lower expression of solute carrier family 7 member 11 (SLC7A11) in the kidneys, which increased susceptibility to acute kidney injury and renal ferroptosis during disseminated Candida tropicalis (C. tropicalis) infection. Moreover, CARD9-deficient MDSCs were susceptible to ferroptosis upon stimulation with C. tropicalis, which was attributed to augmented mitochondrial oxidative phosphorylation (OXPHOS) caused by reduced SLC7A11 expression. Mechanistically, C-type lectin receptors (CLRs)-mediated recognition of C. tropicalis promoted the expression of SLC7A11 which was transcriptionally manipulated by the Syk-PKCδ-CARD9-FosB signaling axis in MDSCs. FosB enhanced SLC7A11 transcription by binding to the promoter of SLC7A11 in MDSCs stimulated with C. tropicalis. Mitochondrial OXPHOS, which was negatively regulated by SLC7A11, was responsible for inducing ferroptosis of MDSCs upon C. tropicalis stimulation. Finally, pharmacological inhibition of mitochondrial OXPHOS or ferroptosis significantly increased the number of MDSCs in the kidneys to augment host antifungal immunity, thereby attenuating ferroptosis and acute kidney injury exacerbated by CARD9 ablation during disseminated candidiasis. CONCLUSIONS: Collectively, our findings show that CARD9 ablation enhances mitochondria-mediated ferroptosis in MDSCs, which negatively regulates antifungal immunity. We also identify mitochondria-mediated ferroptosis in MDSCs as a new molecular mechanism of CARD9 ablation-exacerbated acute kidney injury during disseminated candidiasis, thus targeting mitochondria-mediated ferroptosis is a novel therapeutic strategy for acute kidney injury in disseminated candidiasis.