DNA PAMPs as Molecular Tools for the cGAS-STING Signaling Pathways.

Beyond its role as the bearer of genetic material, DNA also plays a crucial role in the activation phase of innate immunity. Pathogen recognition receptors (PRRs) and their homologs, pathogen-associated molecular patterns (PAMPs), form the foundation for driving innate immune activation and the induction of immune responses during infection. In the context of DNA viruses or bacterial infections, specific DNA sequences are recognized and bound by DNA sensors, marking the DNA as a PAMP for host recognition and subsequent activation of innate immunity. The primary DNA sensor pathway known to date is cGAS-STING, which can induce Type I interferons (IFN) and innate immune responses against viruses and bacteria. Additionally, the cGAS-STING pathway has been identified to mediate functions in autophagy and senescence. Herein, we introduce methods for using DNA PAMPs as molecular tools to study the role of cGAS-STING and its signaling pathway in regulating innate immunity, both in vitro and in vivo.

Identifying RNA Sensors in Antiviral Innate Immunity.

The innate immune system plays a pivotal role in pathogen recognition and the initiation of innate immune responses through its Pathogen Recognition Receptors (PRRs), which detect Pathogen-Associated Molecular Patterns (PAMPs). Nucleic acids, including RNA and DNA, are recognized as particularly significant PAMPs, especially in the context of viral pathogens. During RNA virus infections, specific sequences in the viral RNA mark it as non-self, enabling host recognition through interactions with RNA sensors, thereby triggering innate immunity. Given that some of the most lethal viruses are RNA viruses, they pose a severe threat to human and animal health. Therefore, understanding the immunobiology of RNA PRRs is crucial for controlling pathogen infections, particularly RNA virus infections. In this chapter, we will introduce a "pull-down" method for identifying RIG-I-like receptors, related RNA helicases, Toll-like receptors, and other RNA sensors.

In vivo imaging of alkaline phosphatase in lipid metabolic diseases with a photoacoustic probe.

Lipid metabolic diseases have become an important challenge to global public health. Along with lifestyle changes, the incidence of obesity, diabetes and other metabolic syndromes is on the rise, and the number of patients with fatty liver disease is also increasing. Therefore, it is particularly important to develop effective lipid imaging strategies to monitor and manage fatty liver disease. Herein, based on the essential role of alkaline phosphatase (ALP) in both AS and OB, in vivo imaging of ALP was achieved in two lipid metabolic diseases models with a photoacoustic (PA) probe phosphorylated hemicyanine (P-Hcy). After being triggered by ALP, P-Hcy responded in different modalities including absorbance, fluorescence and, most significantly, PA-reporting. Notably, the PA signal showed the reliable linear correlation to the ALP level within the range of 0-800 U/L. The probe P-Hcy exhibited the advantages including high sensitivity, high selectivity, and steadiness in required biological conditions. The intracellular imaging results ensured that P-Hcy could visualize the ALP level in the foam cells induced from mouse mononuclear macrophages. In the healthy and lipid metabolic diseases models, P-Hcy was able to distinguish well between a lipid metabolic disease model and a healthy mouse model by photoacoustic imaging. By combining the ALP detection with P-Hcy in PA/fluorescence modality and traditional techniques such as blood biochemical testing and immunohistochemically staining, more potential strategy to accurately diagnose lipid metabolic diseases in the pre-clinical trials might be developed in future.

Associations between serum cystatin C and fall reports in an Elderly population.

Fall is common in the elderly, and chronic kidney disease is considered a major risk factor. Serum creatinine (Cre) and cystatin C (Cys C) are commonly used biomarkers for renal function, while the ratio of Cre to Cys C, known as the sarcopenia index (SI), provides insights into muscle health. This study investigates the relationships between Cre, Cys C, estimated glomerular filtration rates (eGFR), SI, and self-reported falls using National Health and Nutrition Examination Survey (NHANES) data. We included 4,272 older adults with eGFR > 30mL/min/1.73m2 from NHANES (1999 to 2004) and divided them into the fall and non-fall groups based on the questionnaires. Correlations were assessed using restricted cubic spline, weighted generalized linear regression models. Multi-factor logistic regression analysis identified serum Cys C as significantly associated with falls (all participants: OR 1.16, 95% CI: 1.09 to 1.23, p < 0.001; participants with eGFR > 75 mL/min/1.73m2: OR 1.17, 95% CI: 1.05 to 1.30, p < 0.001,). In contrast, Cre and eGFR were not significant after adjustments; SI showed marginal significance (p = 0.045). Cys C is significantly associated with fall risk in older adults, demonstrating a positive linear relationship with self-reported falls.

Bcwf regulates the white petal color in pak choi [Brassica campestris (syn. Brassica rapa) ssp. chinensis].

Flower color is important in determining the ornamental value of Brassica species. However, our knowledge about the regulation of flower color in pak choi [Brassica campestris (syn. Brassica rapa) ssp. chinensis] is limited. In this study, we investigated the molecular mechanism underlying white flower traits in pak choi by analyzing a genetic population with white and yellow flowers. Our genetic analysis revealed that the white trait is controlled by a single recessive gene called Bcwf. Through BSA-Seq and fine mapping, we identified a candidate gene, BraC02g039450.1, which is similar to Arabidopsis AtPES2 involved in carotenoid ester synthesis. Sequence analysis showed some mutations in the promoter region of Bcwf in white flowers. Tobacco transient assay confirmed that these mutations reduce the promoter's activity, leading to downregulation of Bcwf expression in white flowers. Furthermore, the silencing of Bcwf in pak choi resulted in lighter petal color and reduced carotenoid content. These findings provide new insights into the molecular regulation of white flower traits in pak choi and highlight the importance of Bcwf in petal coloring and carotenoid accumulation.

Carvedilol to prevent hepatic decompensation of cirrhosis in patients with clinically significant portal hypertension stratified by new non-invasive model (CHESS2306).

Background & Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvedilol-treating cohort. Results: In the meta-analysis with six studies (n = 819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new "CSPH risk" model. In the HVPG cohort (n = 151), the new model accurately predicted CSPH with cutoff values of 0 and -0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n = 1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <-0.68 (low-risk), -0.68 to 0 (medium-risk), and >0 (high-risk). In the carvedilol-treated cohort, patients with high-risk CSPH treated with carvedilol (n = 81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n = 613 before propensity score matching [PSM], n = 162 after PSM). Conclusions: Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

SCCNAInfer: a robust and accurate tool to infer the absolute copy number on scDNA-seq data.

MOTIVATION: Copy number alterations (CNAs) play an important role in disease progression, especially in cancer. Single-cell DNA sequencing (scDNA-seq) facilitates the detection of CNAs of each cell that is sequenced at a shallow and uneven coverage. However, the state-of-the-art CNA detection tools based on scDNA-seq are still subject to genome-wide errors due to the wrong estimation of the ploidy. RESULTS: We developed SCCNAInfer, a computational tool that utilizes the subclonal signal inside the tumor cells to more accurately infer each cell's ploidy and CNAs. Given the segmentation result of an existing CNA detection method, SCCNAInfer clusters the cells, infers the ploidy of each subclone, refines the read count by bin clustering, and accurately infers the CNAs for each cell. Both simulated and real datasets show that SCCNAInfer consistently improves upon the state-of-the-art CNA detection tools such as Aneufinder, Ginkgo, SCOPE and SeCNV. AVAILABILITY AND IMPLEMENTATION: SCCNAInfer is freely available at https://github.com/compbio-mallory/SCCNAInfer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Entropy drives the ligand recognition in G-protein-coupled receptor subtypes.

Achieving ligand subtype selectivity within highly homologous subtypes of G-protein-coupled receptor (GPCR) is critical yet challenging for GPCR drug discovery, primarily due to the unclear mechanism underlying ligand subtype selectivity, which hampers the rational design of subtype-selective ligands. Herein, we disclose an unusual molecular mechanism of entropy-driven ligand recognition in cannabinoid (CB) receptor subtypes, revealed through atomic-level molecular dynamics simulations, cryoelectron microscopy structure, and mutagenesis experiments. This mechanism is attributed to the distinct conformational dynamics of the receptor's orthosteric pocket, leading to variations in ligand binding entropy and consequently, differential binding affinities, which culminate in specific ligand recognition. We experimentally validated this mechanism and leveraged it to design ligands with enhanced or ablated subtype selectivity. One such ligand demonstrated favorable pharmacokinetic properties and significant efficacy in rodent inflammatory analgesic models. More importantly, it is precisely due to the high subtype selectivity obtained based on this mechanism that this ligand does not show addictive properties in animal models. Our findings elucidate the unconventional role of entropy in CB receptor subtype selectivity and suggest a strategy for rational design of ligands to achieve entropy-driven subtype selectivity for many pharmaceutically important GPCRs.

Carvedilol to prevent decompensation of cirrhosis in patients with clinically significant portal hypertension stratified by liver stiffness: study protocol for a randomied, double-blind, placebo-controlled, multicentre trial in China.

INTRODUCTION: Patients with clinically significant portal hypertension (CSPH) are recommended to be treated with non-selective beta-blockers (ie, carvedilol) to prevent the first hepatic decompensation event by the renewing Baveno VII consensus. CSPH is defined by hepatic venous pressure gradient (HVPG)≥10 mm Hg; however, the HVPG measurement is not widely adopted due to its invasiveness. Liver stiffness (LS)≥25 kPa can be used as a surrogate of HVPG≥10 mm Hg to rule in CSPH with 90% of the positive predicting value in majority aetiologies of patients. A compelling argument is existing for using LS≥25 kPa to diagnose CSPH and then to initiate carvedilol in patients with compensated cirrhosis, and about 5%-6% of patients under this diagnosis criteria may not be benefited from carvedilol and are at risk of lower heart rate and mean arterial pressure. Randomised controlled trial on the use of carvedilol to prevent liver decompensation in CSPH diagnosed by LS remains to elucidate. Therefore, we aimed to investigate if compensated cirrhosis patients with LS≥25 kPa may benefit from carvedilol therapy. METHODS AND ANALYSIS: This study is a randomised, double-blind, placebo-controlled, multicentre trial. We will randomly assign 446 adult compensated cirrhosis patients with LS≥25 kPa and without any previous decompensated event and without high-risk gastro-oesophageal varices. Patients are randomly divided into two groups, with 223 subjects in group A and 223 subjects in group B. Group A is a carvedilol intervention group, while group B is a placebo group. All patients in both groups will receive aetiology therapies and are followed up at an interval of 6 months. The 3-year incidences of decompensated events of cirrhosis-related and liver-related death are the primary outcome. The secondary outcomes include development of each complication of portal hypertension individually (ascites, variceal bleeding or overt hepatic encephalopathy), development of spontaneous bacterial peritonitis and other bacterial infections, development of new varices, growth of small varices to large varices, delta changes in LS and spleen stiffness, change in hepatic dysfunction assessed by Child-Pugh and model for end-stage liver disease score, change in platelet count, development of hepatocellular carcinoma, development of portal vein thrombosis and adverse events with a 3-year follow-up. A predefined interim analysis will be performed to ensure that the calculation is reasonable. ETHICS AND DISSEMINATION: The study protocol has been approved by the ethics committees of the Sixth People's Hospital of Shenyang (2023-05-003-01) and independent ethics committee for clinical research of Zhongda Hospital, affiliated to Southeast University (2023ZDSYLL433-P01). The results from this trial will be submitted for publication in peer-reviewed journals and will be presented at international conferences. TRIAL REGISTRATION NUMBER: ChiCTR2300073864.

Correlation between novel inflammatory markers and carotid atherosclerosis: A retrospective case-control study.

OBJECTIVE: Carotid atherosclerosis is a chronic inflammatory disease, which is a major cause of ischemic stroke. The purpose of this study was to analyze the relationship between carotid atherosclerosis and novel inflammatory markers, including platelet to lymphocyte ratio (PLR), neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), platelet to neutrophil ratio (PNR), neutrophil to lymphocyte platelet ratio (NLPR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI), in order to find the best inflammatory predictor of carotid atherosclerosis. METHOD: We included 10015 patients who underwent routine physical examinations at the physical examination center of our hospital from January 2016 to December 2019, among whom 1910 were diagnosed with carotid atherosclerosis. The relationship between novel inflammatory markers and carotid atherosclerosis was analyzed by logistic regression, and the effectiveness of each factor in predicting carotid atherosclerosis was evaluated by receiver operating characteristic (ROC) curve and area under the curve (AUC). RESULT: The level of PLR, LMR and PNR in the carotid atherosclerosis group were lower than those in the non-carotid atherosclerosis group, while NLR, NLPR, SII, SIRI and AISI in the carotid atherosclerosis group were significantly higher than those in the non-carotid atherosclerosis group. Logistic regression analysis showed that PLR, NLR, LMR, PNR, NLPR, SII, SIRI, AISI were all correlated with carotid atherosclerosis. The AUC value of NLPR was the highest, which was 0.67, the cut-off value was 0.78, the sensitivity was 65.8%, and the specificity was 57.3%. The prevalence rate of carotid atherosclerosis was 12.4% below the cut-off, 26.6% higher than the cut-off, and the prevalence rate increased by 114.5%. CONCLUSION: New inflammatory markers were significantly correlated with carotid atherosclerosis, among which NLPR was the optimum inflammatory marker to predict the risk of carotid atherosclerosis.

The impact of the stress hyperglycemia ratio on the risk of contrast-associated acute kidney injury in patients undergoing coronary angiography: a large real-world cohort study.

BACKGROUND: Contrast-associated acute kidney injury (CA-AKI) is an important complication in the perioperative period of coronary angiography (CAG). Dysglycemia is closely associated with the occurrence of CA-AKI. However, the association between stress hyperglycemia and CA-AKI in patients undergoing CAG remains unclear. The study aims to investigate the association of the stress hyperglycemia ratio (SHR) and CA-AKI under CAG in a large real-world cohort. METHODS: This was a retrospective observational study, and patients undergoing CAG were enrolled. SHR is calculated by dividing the random blood glucose with the estimated average glucose derived from the glycosylated hemoglobin (HbA1c), and subjects were divided into five groups according to SHR. The outcome was CA-AKI defined as an increase in serum creatinine of ≥ 0.3 mg/dL (26.5 µmol/L) or 1.5-fold higher than normal levels in 48 h. The association was assessed with logistic regression and restricted cubic spline analysis. RESULTS: In 19,965 participants (men: 73.3%, mean age: 63.1 ± 10.8 years) undergoing CAG, a total of 1,621 CA-AKI cases occurred. There were reverse J-shaped associations between the SHR and CA-AKI after adjustment for other confounding factors. Moreover, SHR improved the predictive effectiveness of the traditional Mehran score (AUC 0.65 vs 0.63, P < 0.001), a predictive model of CA-AKI in patients undergoing percutaneous coronary intervention. CONCLUSIONS: There were reverse J-shaped associations of SHR with CA-AKI risk among patients undergoing CAG, and the assessment of SHR before CAG may assist clinicians in identifying patients at higher risk of CA-AKI.

Phenotypic, Genomic, and Transcriptomic Heterogeneity in a Pancreatic Cancer Cell Line.

OBJECTIVE: To evaluate the suitability of the MIA PaCa-2 cell line for studying pancreatic cancer intratumor heterogeneity, we aim to further characterize the nature of MIA PaCa-2 cells' phenotypic, genomic, and transcriptomic heterogeneity. MATERIALS AND METHODS: MIA PaCa-2 single-cell clones were established through flow cytometry. For the phenotypic study, we quantified the cellular morphology, proliferation rate, migration potential, and drug sensitivity of the clones. The chromosome copy number and transcriptomic profiles were quantified using SNPa and RNA-seq, respectively. RESULTS: Four MIA PaCa-2 clones showed distinctive phenotypes, with differences in cellular morphology, proliferation rate, migration potential, and drug sensitivity. We also observed a degree of genomic variations between these clones in form of chromosome copy number alterations and single nucleotide variations, suggesting the genomic heterogeneity of the population, and the intrinsic genomic instability of MIA PaCa-2 cells. Lastly, transcriptomic analysis of the clones also revealed gene expression profile differences between the clones, including the uniquely regulated ITGAV , which dictates the morphology of MIA PaCa-2 clones. CONCLUSIONS: MIA PaCa-2 is comprised of cells with distinctive phenotypes, heterogeneous genomes, and differential transcriptomic profiles, suggesting its suitability as a model to study the underlying mechanisms behind pancreatic cancer heterogeneity.

Tumor­suppressive effects of Smad­ubiquitination regulator 2 in papillary thyroid carcinoma.

Smad-ubiquitination regulator 2 (SMURF2) functions as a homolog of E6AP carboxyl terminus-type E3 ubiquitin ligase to regulate cell cycle progression and tumor growth factor expression. SMURF2 has been revealed to function as a tumor suppressor in a number of cancers; however, its function in papillary thyroid carcinoma (PTC) remains largely unknown. Therefore, the aim of the present study was to investigate the function of SMURF2 in PTC. Reverse transcription-quantitative PCR and western blotting were used to detect cellular expression of SMURF2 in vitro. After increasing or inhibiting the expression of SMURF2, MTT was used to detect the effect on tumor cell proliferation and Transwell assays were used to detect the effect on tumor cell migration and invasion. Finally, ELISA was used to detect the effects on glucose and glutamine metabolism in tumor cells and the findings revealed that SMURF2 was downregulated in PTC tissues. Moreover, SMURF2 inhibited the proliferation, invasion and migration of PTC cells, and promoted their apoptosis. Finally, SMURF2 inhibited cell glycolysis and glutaminolysis and affected metabolism in the PTC cell line, TPC-1. Thus, the findings of the present study suggest that SMURF2 may be a potential target in the treatment of PTC.

Stabilization of Lattice Oxygen Evolution Reactions in Oxophilic Ce-Mediated Bi/BiCeO1.8H Electrocatalysts for Efficient Anion Exchange Membrane Water Electrolyzers.

The lattice oxygen mechanism (LOM) offers an efficient reaction pathway for oxygen evolution reactions (OERs) in energy storage and conversion systems. Owing to the involvement of active lattice oxygen enhancing electrochemical activity, addressing the structural and electrochemical stabilities of LOM materials is crucial. Herein, a heterostructure (Bi/BiCeO1.8H) containing abundant under-coordinated oxygen atoms having oxygen nonbonding states is synthesized by a simple electrochemical deposition method. Given the difference in reduction potentials between Bi and Ce, partially reduced Bi nanoparticles and surrounding under-coordinated oxygen atoms are generated in BiCeO1.8H. It is found that the lattice oxygen can be activated as a reactant of the OER when the valence state of Bi increases to Bi5+, leading to increased metal-oxygen covalency and that the oxophilic Ce3+/4+ redox couple can maintain the Bi nanoparticles and surrounding under-coordinated oxygen atoms by preventing over-oxidation of Bi. The anion exchange membrane water electrolyzer with Bi/BiCeO1.8H exhibits a low cell voltage of 1.79 V even at a high practical current density of 1.0 A cm-2. Furthermore, the cell performance remains significantly stable over 100 h with only a 2.2% increase in the initial cell voltage, demonstrating sustainable lattice oxygen redox.

RNF31 alleviates liver steatosis by promoting p53/BNIP3-related mitophagy in hepatocytes.

BACKGROUND & AIMS: Non-alcoholic fatty liver disease (NAFLD) is one of the liver illnesses that may be affected by mitophagy, which is the selective removal of damaged mitochondria. RNF31, an E3 ubiquitin ligase, is carcinogenic in many malignancies. However, the influence of RNF31 on mitochondrial homeostasis and NAFLD development remains unknown. METHODS: Oleic-palmitic acid treated hepatocytes and high-fat diet (HFD)-fed mice were established to observe the effect of RNF31 on hepatocyte mitophagy and steatosis. Mitophagy processes were comprehensively assessed by mt-Keima fluorescence imaging, while global changes in hepatic gene expression were measured by RNA-seq. RESULTS: The present study discovered a reduction in RNF31 expression in lipotoxic hepatocytes with mitochondrial dysfunction. The observed decrease in RNF31 expression was associated with reduced mitochondrial membrane potential, disturbed mitophagy, and increased steatosis. Additionally, the findings indicated that RNF31 is a pivotal factor in the initiation of mitophagy and the facilitation of mitochondrial homeostasis, resulting in a decrease in steatosis in lipotoxic hepatocytes. Mechanistically, RNF31 enhanced p53 ubiquitination and subsequent proteasomal degradation. Down-regulation of p53 led to increased expression of the mitophagy receptor protein BCL2 and adenovirus E1B 19 kDa-interacting protein 3 (BNIP3), thereby promoting mitophagy in hepatocytes. Furthermore, it was demonstrated that the transportation of RNF31 via small extracellular vesicles derived from mesenchymal stem cells (referred to as sEV) had a substantial influence on reducing hepatic steatosis and restoring liver function in HFD-fed mice. CONCLUSIONS: The findings highlight RNF31's essential role in the regulation of mitochondrial homeostasis in hepatocytes, emphasizing its potential as a therapeutic target for NAFLD.

A comparative study of 11 non-linear regression models highlighting autoencoder, DBN, and SVR, enhanced by SHAP importance analysis in soybean branching prediction.

To explore a robust tool for advancing digital breeding practices through an artificial intelligence-driven phenotype prediction expert system, we undertook a thorough analysis of 11 non-linear regression models. Our investigation specifically emphasized the significance of Support Vector Regression (SVR) and SHapley Additive exPlanations (SHAP) in predicting soybean branching. By using branching data (phenotype) of 1918 soybean accessions and 42 k SNP (Single Nucleotide Polymorphism) polymorphic data (genotype), this study systematically compared 11 non-linear regression AI models, including four deep learning models (DBN (deep belief network) regression, ANN (artificial neural network) regression, Autoencoders regression, and MLP (multilayer perceptron) regression) and seven machine learning models (e.g., SVR (support vector regression), XGBoost (eXtreme Gradient Boosting) regression, Random Forest regression, LightGBM regression, GPs (Gaussian processes) regression, Decision Tree regression, and Polynomial regression). After being evaluated by four valuation metrics: R2 (R-squared), MAE (Mean Absolute Error), MSE (Mean Squared Error), and MAPE (Mean Absolute Percentage Error), it was found that the SVR, Polynomial Regression, DBN, and Autoencoder outperformed other models and could obtain a better prediction accuracy when they were used for phenotype prediction. In the assessment of deep learning approaches, we exemplified the SVR model, conducting analyses on feature importance and gene ontology (GO) enrichment to provide comprehensive support. After comprehensively comparing four feature importance algorithms, no notable distinction was observed in the feature importance ranking scores across the four algorithms, namely Variable Ranking, Permutation, SHAP, and Correlation Matrix, but the SHAP value could provide rich information on genes with negative contributions, and SHAP importance was chosen for feature selection. The results of this study offer valuable insights into AI-mediated plant breeding, addressing challenges faced by traditional breeding programs. The method developed has broad applicability in phenotype prediction, minor QTL (quantitative trait loci) mining, and plant smart-breeding systems, contributing significantly to the advancement of AI-based breeding practices and transitioning from experience-based to data-based breeding.

Hierarchically Interconnected 3D Catalyst Structure of Porous Multi-Metal Oxide Nanofibers for High-Performance Li-O2 Batteries.

Non-aqueous lithium-oxygen batteries (LOBs) have emerged as a promising candidate due to their high theoretical energy density and eco-friendly cathode reaction materials. However, LOBs still suffer from high overpotential and poor cycling stability resulting from difficulties in the decomposition of discharge reaction Li2O2 products. Here, a 3D open network catalyst structure is proposed based on highly-thin and porous multi-metal oxide nanofibers (MMONFs) developed by a facile electrospinning approach coupled with a heat treatment process. The developed hierarchically interconnected 3D porous MMONFs catalyst structure with high specific surface area and porosity shows the enhanced electrochemical reaction kinetics associated with Li2O2 formation and decomposition on the cathode surface during the charge and discharge processes. The uniquely assembled cathode materials with MMONFs exhibit excellent electrochemical performance with energy efficiency of 82% at a current density of 50 mA g-1 and a long-term cycling stability over 100 cycles at 200 mA g-1 with a cut-off capacity of 500 mAh g-1. Moreover, the optimized cathode materials exhibit a remarkable energy density of 1013 Wh kg-1 at the 100th discharge and charge cycle, which is nearly four times higher than that of C/NMC721, which has the highest energy density among the cathode materials currently used in electric vehicles.

Autoimmune Glial Fibrillary Acidic Protein Astrocytopathy Is Associated with HLA-A*3303 and HLA-DPB1*0501.

We determined the genetic association between specific human leucocyte antigen (HLA) loci and autoimmune glial fibrillary acidic protein (GFAP) astrocytopathy. Our results showed that autoimmune GFAP astrocytopathy was associated with HLA-A*3303 (odds ratio [OR] = 2.02, 95% confidence interval [CI] = 1.32-3.06, p = 0.00072, padj. = 0.046) and HLA-DBP1*0501 (OR = 0.51, 95% CI = 0.36-0.71, p = 0.000048, padj. = 0.0062). Moreover, HLA-A*3303 carriers with the disease had a longer hospital stay (p = 0.0005) than non-carriers. This study for the first time provides evidence for a role of genetic factor in the development of autoimmune GFAP astrocytopathy. ANN NEUROL 2024;95:901-906.

Association of plasma homocysteine with peripheral arterial disease in the hypertensive adults: A cross-sectional study.

Increased plasma homocysteine (Hcy) has been identified as one of the important risk factors for cardiovascular disease. However, the association between plasma Hcy and peripheral artery disease (PAD) is still controversial. This study aimed to investigate the association between plasma Hcy and PAD and the potential modifier factors in Chinese hypertensive adults. A total of 25 300 hypertensive patients aged 18 years or older were included in the analysis in this cross-sectional study. The outcome was PAD, which defined as an ankle-brachial index ≤0.90 in either limb. Multiple logistic regression was used to analyze the relationship between plasma Hcy and PAD. The median plasma Hcy was 14.00 (interquartile range: 11.60-17.80) µmol/L. There was a significant positive association between plasma Hcy and PAD (per SD increment; OR: 1.13; 95% CI: 1.06-1.19). Patients in the upper plasma Hcy tertile (≥16.16 µmol/L) were associated with a 53% increased risk of PAD compared with patients in the lower tertile (<12.33 µmol/L) after adjustment for multiple potential confounders. Subgroup analyses showed the association between Hcy and PAD was robust among various strata. Among Chinese adults with hypertension, plasma Hcy is an independent risk factor for PAD. This finding may improve the risk stratification of PAD.

Elimination of Random Mixed Noise in ECG Using Convolutional Denoising Autoencoder With Transformer Encoder.

Electrocardiogram (ECG) signals frequently encounter diverse types of noise, such as baseline wander (BW), electrode motion (EM) artifacts, muscle artifact (MA), and others. These noises often occur in combination during the actual data acquisition process, resulting in erroneous or perplexing interpretations for cardiologists. To suppress random mixed noise (RMN) in ECG with less distortion, we propose a Transformer-based Convolutional Denoising AutoEncoder model (TCDAE) in this study. The encoder of TCDAE is composed of three stacked gated convolutional layers and a Transformer encoder block with a point-wise multi-head self-attention module. To obtain minimal distortion in both time and frequency domains, we also propose a frequency weighted Huber loss function in training phase to better approximate the original signals. The TCDAE model is trained and tested on the QT Database (QTDB) and MIT-BIH Noise Stress Test Database (NSTDB), with the training data and testing data coming from different records. All the metrics perform the most robust in overall noise and separate noise intervals for RMN removal compared with the baseline methods. We also conduct generalization tests on the Icentia11k database where the TCDAE outperforms the state-of-the-art models, with a 55% reduction of the false positives in R peak detection after denoising. The TCDAE model approximates the short-term and long-term characteristics of ECG signals and has higher stability even under extreme RMN corruption. The memory consumption and inference speed of TCDAE are also feasible for its deployment in clinical applications.