Neuregulin-1 immunoreactivity in peripheral plasma is associated with rs6982890 polymorphism-mediated psychotic symptoms in schizophrenia.

OBJECTIVES: Neuregulin 1 (NRG1) is a risk gene for schizophrenia and involved in neurodevelopment and synaptic plasticity. Polymorphisms in NRG1 may affect psychotic symptoms in schizophrenia. This study investigated the effects of the single nucleotide polymorphism (SNP) rs6982890 on peripheral plasma NRG1 immunoreactivity, clinical symptoms and cognitive functions in schizophrenia patients. MATERIAL AND METHODS: We recruited subjects from the Han population of northern China from 2010 to 2022. We first genotyped and analyzed 6 NRG1 SNPS in 1304 patients with schizophrenia and 871 healthy controls. Then, 91 patients with schizophrenia and 40 healthy controls were selected to detect the peripheral plasma NRG1 immunoreactivity by ELISA. Among them, 84 patients were divided into rs6982890 genotypes to analyze the correlation between NRG1 immunoreactivity and clinical symptoms. RESULTS: Rs6982890 allelic frequencies were statistically significant between patients and controls. Baseline peripheral plasma NRG1 immunoreactivity in patients were significantly lower than controls. NRG1 immunoreactivity in patients were significantly increased after 8 weeks of antipsychotic treatment and significantly correlated with clinical symptoms and cognitive function. Genotyping of patients with SNP rs6982890 indicated NRG1 immunoreactivity in CC genotype increased significantly after treatment, while CT genotype had no significant change. Baseline NRG1 immunoreactivity with the CT genotype were significantly higher than CC genotype. CONCLUSIONS: NRG1 SNP rs6982890 is significantly associated with schizophrenia in the Han population of northern China, and it may affect the effect of antipsychotic drug treatment by regulating the peripheral plasma NRG1 immunoreactivity.

Predicting Long-Term Outcome of Prolonged Disorder of Consciousness in Children Through Machine Learning Based on Conventional Structural Magnetic Resonance Imaging.

BACKGROUND: The prognosis of prolonged disorders of consciousness (pDoC) in children has consistently posed a formidable challenge in clinical decision-making. OBJECTIVE: This study aimed to develop a machine learning (ML) model based on conventional structural magnetic resonance imaging (csMRI) to predict outcomes in children with pDoC. METHODS: A total of 196 children with pDoC were included in this study. Based on the consciousness states 1 year after brain injury, the children were categorized into either the favorable prognosis group or the poor prognosis group. They were then randomly assigned to the training set (n = 138) or the test set (n = 58). Semi-quantitative visual assessments of brain csMRI were conducted and Least Absolute Shrinkage and Selection Operator regression was used to identify significant features predicting outcomes. Based on the selected features, support vector machine (SVM), random forests (RF), and logistic regression (LR) were used to develop csMRI, clinical, and csMRI-clinical-merge models, respectively. Finally, the performances of all models were evaluated. RESULTS: Seven csMRI features and 4 clinical features were identified as important predictors of consciousness recovery. All models achieved satisfactory prognostic performances (all areas under the curve [AUCs] >0.70). Notably, the csMRI model developed using the SVM exhibited the best performance, with an AUC, accuracy, sensitivity, and specificity of 0.851, 0.845, 0.844, and 0.846, respectively. CONCLUSIONS: A csMRI-based prediction model for the prognosis of children with pDoC was developed, showing potential to predict recovery of consciousness 1 year after brain injury and is worth popularizing in clinical practice.

Characterization of ACTN4 as a novel antiviral target against SARS-CoV-2.

The various mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pose a substantial challenge in mitigating the viral infectivity. The identification of novel host factors influencing SARS-CoV-2 replication holds potential for discovering new targets for broad-spectrum antiviral drugs that can combat future viral mutations. In this study, potential host factors regulated by SARS-CoV-2 infection were screened through different high-throughput sequencing techniques and further identified in cells. Subsequent analysis and experiments showed that the reduction of m6A modification level on ACTN4 (Alpha-actinin-4) mRNA leads to a decrease in mRNA stability and translation efficiency, ultimately inhibiting ACTN4 expression. In addition, ACTN4 was demonstrated to target nsp12 for binding and characterized as a competitor for SARS-CoV-2 RNA and the RNA-dependent RNA polymerase complex, thereby impeding viral replication. Furthermore, two ACTN4 agonists, YS-49 and demethyl-coclaurine, were found to dose-dependently inhibit SARS-CoV-2 infection in both Huh7 cells and K18-hACE2 transgenic mice. Collectively, this study unveils the pivotal role of ACTN4 in SARS-CoV-2 infection, offering novel insights into the intricate interplay between the virus and host cells, and reveals two potential candidates for future anti-SARS-CoV-2 drug development.

Mechanism study of serum extracellular nano-vesicles miR-412-3p targeting regulation of TEAD1 in promoting malignant biological behavior of sub-centimeter lung nodules.

OBJECTIVE: To investigate the impact and potential mechanisms of serum extracellular nano-vesicles (sEVs) miR-412-3p released from sub-centimeter lung nodules with a diameter of ⩽ 10 mm on the malignant biological function of micro-nodular lung cancer (mnLC). METHODS: A total of 87 participants were included and divided into a mnLC group (n= 30), a benign lung nodule (BLN) group (n= 27), and a healthy people control group (n= 30). Transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA) and Western blot (WB) were used to measure the morphological characteristics and surface markers of sEVs. In vitro analysis, real-time quantitative polymerase chain reaction (RT-qPCR), CCK-8 cell proliferation assay, clone formation assay, Transwell, stem cell sphere-forming assay, and WB assay were conducted to verify the effect of miR-412-3p/TEAD1 signaling axis on the biological function of lung cancer cells through, respectively. Further validation was conducted using the serum sEVs of the participants. RESULTS: The expression level of sEVs-miR-412-3p in the mnLC group was significantly higher than that in the BLN and healthy groups (P< 0.01). In lung cancer cell lines, miR-412-3p can negatively regulate the targeted gene TEAD1. The miR-412-3p/TEAD1 signaling axis is involved in promoting the EMT signaling pathway and regulating the malignant biological functions of lung cancer cell proliferation, migration, and stemness (P< 0.05). In addition, sEVs in the mnLC group significantly promoted lung cancer cell proliferation, migration, and stemness compared to the BLN and healthy groups, inhibited the expression of E-cadherin and TEAD1 in lung cancer cells, and promoted the expression of N-cadherin and Vimentin (P< 0.05). CONCLUSION: sEVs-miR-412-3p could promote the biological process of EMT, and lead to the occurrence of malignant biological behavior in sub-centimeter lung nodules. This provides evidence for the miR-412-3p/TEAD1 signaling axis as a potential therapeutic target for mnLC.

Towards efficient and accurate prediction of freeway accident severity using two-level fuzzy comprehensive evaluation.

Accurately predicting freeway accident severity is crucial for accident prevention, road safety, and emergency rescue services in intelligent freeway systems. However, current research lacks the required precision, hindering the effective implementation of freeway rescue. In this paper, we efficiently address this challenge by categorizing influencing factors into two levels: human and non-human, further subdivided into 6 and 36 categories, respectively. Furthermore, based on the above factors, an efficient and accurate Freeway Accident Severity Prediction (FASP) method is developed by using the two-level fuzzy comprehensive evaluation. The factor and evaluation sets are determined by calculating the fuzzy evaluation matrix of a single factor. The weight matrix is calculated through the entropy method to compute the final evaluation matrix. Based on the maximum membership principle, the severity of the freeway accident is predicted. Finally, based on the experiments conducted with the traffic accident datasets in China and the US, it is shown that FASP is able to accurately predict the severity of freeway traffic accidents with thorough considerations and low computational cost. It is noted that FASP is the first attempt to achieve freeway accident severity prediction using the two-level fuzzy comprehensive evaluation method to the best of our knowledge.

Alterations of brain structural and functional connectivity networks topology and decoupling in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease.

OBJECTIVE: To investigate the alteration in structural and functional connectivity networks (SCN and FCN) as well as their coupling in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and determine if these properties could serve as potential biomarkers for the disease. MATERIALS AND METHODS: In total of 32 children with MOGAD and 30 age- and sex-matched healthy controls (HC) were employed to construct the SCN and FCN, respectively. The graph-theoretical analyses of the global properties, node properties of the 90 brain nodes, and the structural-functional connectivity (SC-FC) coupling of the two networks were performed. The graph-theoretical properties that exhibited significant differences were analyzed using partial correlation analysis in conjunction with the clinical scales, including the expanded disability status scale (EDSS), modified Rankin scale (mRS), and pediatric cerebral performance category (PCPC) of the MOGAD group. Subsequently, a machine learning model was developed to discriminate between MOGAD and the HC group, aiming to explore the potential of these properties as biomarkers. RESULTS: The SCN of the MOGAD group exhibited aberrant global properties, including an increased characteristic path length (Lp) and a decreased global efficiency (Eg), along with reduced nodal properties such as degree centrality (Dc), nodal efficiency (Ne), and local efficiency in multiple nodes. The FCN of the MOGAD group only exhibited decreased Dc, Ne, and betweenness centrality in two nodes of nodal properties. Besides, MOGAD showed a significant decrease in SC-FC coupling compared to the HC group. The analysis of partial correlation revealed significant correlations between several properties and the scales of EDSS and mRS in the MOGAD group. The machine learning method was used to extract six features and establish the model, achieving a classification accuracy of 82.3% for MOGAD. CONCLUSIONS: Pediatric MOGAD showed a more pronounced impairment in the SCN along with decoupling of SC-FC. Both partial correlation analysis and discriminant modeling suggest that alterations in brain network properties have the potential as biomarkers for assessing brain damage in MOGAD.

Coronary artery wall contrast enhancement imaging impact on disease activity assessment in IgG4-RD: a direct marker of coronary involvement.

BACKGROUND: Coronary artery wall contrast enhancement (CE) has been applied to non-invasive visualization of changes to the coronary artery wall in systemic lupus erythematosus (SLE). This study investigated the feasibility of quantifying CE to detect coronary involvement in IgG4-related disease (IgG4-RD), as well as the influence on disease activity assessment. METHODS: A total of 93 subjects (31 IgG4-RD; 29 SLE; 33 controls) were recruited in the study. Coronary artery wall imaging was performed in a 3.0 T MRI scanner. Serological markers and IgG4-RD Responder Index (IgG4-RD-RI) scores were collected for correlation analysis. RESULTS: Coronary wall CE was observed in 29 (94 %) IgG4-RD patients and 22 (76 %) SLE patients. Contrast-to-noise ratio (CNR) and total CE area were significantly higher in patient groups compared to controls (CNR: 6.1 ± 2.7 [IgG4-RD] v. 4.2 ± 2.3 [SLE] v. 1.9 ± 1.5 [control], P < 0.001; Total CE area: 3.0 [3.0-6.6] v. 1.7 [1.5-2.6] v. 0.3 [0.3-0.9], P < 0.001). In the IgG4-RD group, CNR and total CE area were correlated with the RI (CNR: r = 0.55, P = 0.002; total CE area: r = 0.39, P = 0.031). RI´ scored considering coronary involvement by CE, differed significantly from RI scored without consideration of CE (RI v. RI´: 15 ± 6 v. 16 ± 6, P < 0.001). CONCLUSIONS: Visualization and quantification of CMR coronary CE by CNR and total CE area could be utilized to detect subclinical and clinical coronary wall involvement, which is prevalent in IgG4-RD. The potential inclusion of small and medium-sized vessel involvements in the assessment of disease activity in IgG4-RD is worthy of further investigation.

Target engagement and immunogenicity of an active immunotherapeutic targeting pathological α-synuclein: a phase 1 placebo-controlled trial.

Investigational therapeutics that target toxic species of α-synuclein (αSyn) aim to slow down or halt disease progression in patients with Parkinson's disease (PD). Here this 44-week, randomized, placebo-controlled, double-blind, single-center phase 1 study investigated safety, tolerability and immunogenicity of UB-312, an active immunotherapeutic targeting pathological αSyn, in patients with PD. The primary outcome measures were adverse event frequency and change in anti-αSyn antibody titers in blood and cerebrospinal fluid (CSF). Exploratory outcomes were changes in clinical scales and biomarker-based target engagement as measured by seed amplification assays. Twenty patients were randomized 7:3 (UB-312:placebo) into 300/100/100 µg or 300/300/300 µg (weeks 1, 5 and 13) intramuscular prime-boost dose groups. Safety was similar across groups; adverse events were mostly mild and transient. Two patients experienced three serious adverse events in total, one possibly treatment related; all resolved without sequalae. Anti-αSyn antibodies in serum from 12/13 and CSF from 5/13 patients who received three UB-312 doses confirmed immunogenicity. Mean serum titers (in log-dilution factor) increased from baseline by 1.398 and 1.354, and peaked at week 29 at 2.520 and 2.133, for 300/100/100 µg and 300/300/300 µg, respectively. CSF titers were 0 at baseline and were 0.182 and 0.032 at week 21, respectively. Exploratory analyses showed no statistical differences in clinical scales but a significant reduction of αSyn seeds in CSF of a subset of UB-312-treated patients. These data support further UB-312 development. ClinicalTrials.gov: NCT04075318 .

Role of long non-coding RNA TCONS_02443383 in regulating cell adhesion and peroxisome proliferator-activated receptor (PPAR) signaling genes in atherosclerosis: A New Zealand white rabbit model study.

OBJECTIVE: In this study, we performed RNA sequencing (RNA-seq) on the abdominal aorta tissue of New Zealand rabbits and investigated the potential association of lncRNA TCONS_02443383 with the development of AS through bioinformatics analysis of the sequencing data. The obtained results were further validated using quantitative real-time polymerase chain reaction (qRT-PCR). METHOD: We induced an AS model in New Zealand rabbits by causing balloon injury to the abdominal aorta vascular wall and administering a high-fat diet. We then upregulated the expression level of the lncRNA TCONS_02443383 by injecting lentiviral plasmids through the ear vein. RNA sequencing (RNA-seq) was performed on the abdominal aorta tissues. We conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway and Gene Ontology (GO) analyses. RESULT: The overexpression of the lncRNA TCONS_02443383 led to an upregulation of peroxisome proliferator-activated receptor (PPAR) signaling pathways as well as genes related to cell adhesion. CONCLUSION: The overexpression of the lncRNA TCONS_02443383 can inhibit the occurrence and development of AS by upregulating peroxisome proliferator-activated receptor (PPAR) signaling pathways and genes related to cell adhesion.

Revealing the impact of autophagy-related genes in rheumatoid arthritis: Insights from bioinformatics.

Background: Rheumatoid arthritis is a systemic inflammatory autoimmune disease that severely impacts physical and mental health. Autophagy is a cellular process involving the degradation of cellular components in lysosomes. However, from a bioinformatics perspective, autophagy-related genes have not been comprehensively elucidated in rheumatoid arthritis. Methods: In this study, we performed differential analysis of autophagy-related genes in rheumatoid arthritis patients using the GSE93272 dataset from the Gene Expression Omnibus database. Marker genes were screened by least absolute shrinkage and selection operator. Based on marker genes, we used unsupervised cluster analysis to elaborate different autophagy clusters, and further identified modules strongly associated with rheumatoid arthritis by weighted gene co-expression network analysis. In addition, we constructed four machine learning models, random forest model, support vector machine model, generalized linear model and extreme gradient boosting based on marker genes, and based on the optimal machine learning model, a nomogram model was constructed for distinguishing between normal individuals and rheumatoid arthritis patients. Finally, five external independent rheumatoid arthritis datasets were used for the validation of our results. Results: The results showed that autophagy-related genes had significant expression differences between normal individuals and osteoarthritis patients. Through least absolute shrinkage and selection operator screening, we identified 31 marker genes and found that they exhibited significant synergistic or antagonistic effects in rheumatoid arthritis, and immune cell infiltration analysis revealed significant changes in immune cell abundance. Subsequently, we elaborated different autophagy clusters (cluster 1 and cluster 2) using unsupervised cluster analysis. Next, further by weighted gene co-expression network analysis, we identified a brown module strongly associated with rheumatoid arthritis. In addition, we constructed a nomogram model for five marker genes (CDKN2A, TP53, ATG16L2, FKBP1A, and GABARAPL1) based on a generalized linear model (area under the curve = 1.000), and the predictive efficiency and accuracy of this nomogram model were demonstrated in the calibration curves, the decision curves and the five external independent datasets were validated. Conclusion: This study identified marker autophagy-related genes in rheumatoid arthritis and analyzed their impact on the disease, providing new perspectives for understanding the role of autophagy-related genes in rheumatoid arthritis and providing new directions for its individualized treatment.

[Mechanism of acupotomy on chondrocyte ferroptosis in rabbits with knee osteoarthritis based on HSPA5/GPX4 signaling pathway].

OBJECTIVE: To observe the effect of acupotomy on heat shock protein A family member 5 (HSPA5)/glutathione peroxidase 4 (GPX4) signaling pathway in the chondrocytes of the rabbits with knee osteoarthritis (KOA) and explore the mechanism of acupotomy on chondrocyte ferroptosis in KOA. METHODS: Twenty-seven New Zealand rabbits were randomly divided into a normal group, a model group and an acupotomy group, with 9 rabbits in each group. The left hind limb was fixed by the modified Videman method for 6 weeks to establish KOA model. After modeling, acupotomy was given in the acupotomy group, once a week and for consecutive 3 weeks. Using Lequesne MG score, the local symptoms, physical signs and functions of knee joint were evaluated. With HE staining and saffrane-solid green staining adopted, the morphology of chondrocytes and cartilage tissue was observed. Under transmission electron microscope, the mitochondrial structure of chondrocytes was observed. The iron content of cartilage tissue was detected by iron ion kit. The mitochondrial membrane potential (Δψm) and the reactive oxygen species (ROS) level in cartilage tissue were determined by flow cytometry, and the mitochondrial damage rate was calculated. The mRNA expression of HSPA5, GPX4, type Ⅱ collagen α1 chain (COL2A1), matrix metalloproteinases (MMP) 3 and MMP13 was detected by the real-time quantitative PCR; and the protein expression of HSPA5, GPX4, type Ⅱ collagen (COL-Ⅱ), MMP3 and MMP13 was detected by Western blot. The mean flourscence intensity of HSPA5 and GPX4 in cartilage tissue was determined by immunofluorescence. RESULTS: Before intervention, compared with the normal group, the Lequesne MG scores were increased in the model group and the acupotomy group (P<0.01). After intervention, the Lequesne MG score in the acupotomy group was decreased when compared with that in the model group. In comparison with that in the normal group, the number of chondrocytes was reduced and the cells were disarranged; the layers of cartilage structure were unclear, the tide lines disordered and blurred; the mitochondria were wrinkled and the mitochondrial crista decreased or even disappeared in the model group. Compared with the model group, the number of chondrocytes was increased, the layers of cartilage structure were clear, the tide lines recovered, the number of mitochondria elevated, with normal structure and more crista in the acupotomy group. The iron content of cartilage tissue was increased (P<0.01), the Δψm of chondrocytes was declined, the mitochondrial damage rate was increased (P<0.01), the average fluorescence intensity of ROS was increased (P<0.01); the mRNA and corresponding protein expression of HSPA5, GPX4 and COL2A1 was decreased (P<0.01), the mRNA and protein expression of MMP3 and MMP13 was increased (P<0.01) and the average fluorescence intensity of HSPA5, GPX4 was decreased (P<0.01) in the model group when compared with those in the normal group. Compared with the model group, the iron content in cartilage tissue was reduced (P<0.01), the Δψm of chondrocytes was increased, the mitochondrial damage rate was decreased (P<0.01), and the average fluorescence intensity of ROS was decreased (P<0.01); the mRNA and corresponding protein expression of HSPA5, GPX4 and COL2A1 was higher (P<0.01), and the mRNA and protein expression of MMP3 and MMP13 was lower, and the average fluorescence intensity of HSPA5, GPX4 was increased (P<0.01) in the acupotomy group. CONCLUSION: Acupotomy can alleviate cartilage injury of KOA rabbits, and its mechanism may be related to the regulation of HSPA5/GPX4 signaling pathway to maintain iron homeostasis in articular cartilage, thus inhibiting chondrocyte ferroptosis and relieving extracellular matrix degradation.

NSUN2 mediates distinct pathways to regulate enterovirus 71 replication.

Increasing evidences suggest that the methyltransferase NSUN2 catalyzes 5-methylcytosine (m5C) modifications on viral RNAs, which are essential for the replication of various viruses. Despite the function of m5C deposition is well characterized, other potential roles of NSUN2 in regulating viral replication remain largely unknown. In this study, the m5C modified residues catalyzed by NSUN2 on enterovirus 71 (EV71) RNAs were mapped. NSUN2, along with m5C modifications, played multiple roles during the EV71 life cycle. Functional m5C modified nucleotides increased the translational efficiency and stability of EV71 RNAs. Additionally, NSUN2 was found to target the viral protein VP1 for binding and promote its stability by inhibiting the ubiquitination. Furthermore, both viral replication and pathogenicity in mice were largely attenuated when functional m5C residues were mutated. Taken together, this study characterizes distinct pathways mediated by NSUN2 in regulating EV71 replication, and highlights the importance of its catalyzed m5C modifications on EV71 RNAs for the viral replication and pathogenicity.

SPG21, a potential oncogene targeted by miR-128-3p, amplifies HBx-induced carcinogenesis and chemoresistance via activation of TRPM7-mediated JNK pathway in hepatocellular carcinoma.

PURPOSE: Chronic hepatitis B virus (HBV) infection is the primary risk factor for the malignant progression of hepatocellular carcinoma (HCC). It has been reported that HBV X protein (HBx) possesses oncogenic properties, promoting hepatocarcinogenesis and chemoresistance. However, the detailed molecular mechanisms are not fully understood. Here, we aim to investigate the effects of miR-128-3p/SPG21 axis on HBx-induced hepatocarcinogenesis and chemoresistance. METHODS: The expression of SPG21 in HCC was determined using bioinformatics analysis, quantitative real-time PCR (qRT-PCR), western blotting, and immunohistochemistry (IHC). The roles of SPG21 in HCC were elucidated through a series of in vitro and in vivo experiments, including real-time cellular analysis (RTCA), matrigel invasion assay, and xenograft mouse model. Pharmacologic treatment and flow cytometry were performed to demonstrate the potential mechanism of SPG21 in HCC. RESULTS: SPG21 expression was elevated in HCC tissues compared to adjacent non-tumor tissues (NTs). Moreover, higher SPG21 expression correlated with poor overall survival. Functional assays revealed that SPG21 fostered HCC tumorigenesis and invasion. MiR-128-3p, which targeted SPG21, was downregulated in HCC tissues. Subsequent analyses showed that HBx amplified TRPM7-mediated calcium influx via miR-128-3p/SPG21, thereby activating the c-Jun N-terminal kinase (JNK) pathway. Furthermore, HBx inhibited doxorubicin-induced apoptosis by engaging the JNK pathway through miR-128-3p/SPG21. CONCLUSION: The study suggested that SPG21, targeted by miR-128-3p, might be involved in enhancing HBx-induced carcinogenesis and doxorubicin resistance in HCC via the TRPM7/Ca2+/JNK signaling pathway. This insight suggested that SPG21 could be recognized as a potential oncogene, offering a novel perspective on its role as a prognostic factor and a therapeutic target in the context of HCC.

[Assessment of Microplastic Pollution and Estimation of Annual Emission Volume in the Dongshan Canal of Yichang City].

Microplastics, as an emerging pollutant, have garnered global attention. Urban areas are key hotspots for the generation of microplastic pollution, whereas urban water bodies act as vital conduits for the dissemination of microplastics to other freshwater environments. In this study, the Dongshan Canal in the urban area of Yichang City was selected as the research subject. Through field sampling, microscopic observation, and Fourier infrared spectroscopy analysis conducted in July and October 2022, the occurrence characteristics and potential pollution sources of microplastics in the water body of the Dongshan Canal were identified and analyzed. The ecological risk and annual emission volume of microplastics in the water body were quantitatively assessed using the risk index (H), pollution load index (PLI) model, and proportional flow method. The results indicated that the average abundances of microplastics in the surface water of the Dongshan Canal were (7 295±1 051) n·m-3 (July) and (5 145±762.6) n·m-3 (October). Fibrous microplastics (27.63%-63.23%), microplastics with a size of <0.5 mm (75.68%-96.2%), and colored microplastics (22.73%-61.83%) dominated the samples, with PE (30.1%) and PET (26.33%) being the predominant materials. The assessment results from the two models classified the ecological risk index of the Dongshan Canal as class Ⅲ, whereas the overall pollution load fell into class I, with certain sampling points reaching class Ⅱ. Estimates revealed that the Dongshan Canal transports approximately 3.37 t of microplastics to the Yangtze River annually. Overall, the microplastic pollution level in the Dongshan Canal of Yichang City could be considered moderate, with potential sources of pollution including laundry wastewater, personal care products, and plastic waste.

[Occurrence Characteristics of Microplastics in Multi-environmental Media and Bellamya aeruginosa of Manao River].

Microplastic pollution poses threats to aquatic ecosystems and human health. In this study, in order to investigate the characteristics of microplastic occurrence in different environmental media, the abundance, particle size, shape, color, and composition types of microplastics in the water column, sediment, riparian zone soil, and the benthic snail Bellamya aeruginosa of the Manao River were analyzed using field sampling, microscopic observation, and Fourier infrared spectroscopy. The results showed that the average abundance of microplastics in the surface water of the Manao River was (5.9±0.26) n·L-1; the abundance of microplastics in the upper sediment (by dry weight) was (1.35±0.1) n·g-1, and that in the lower sediment (by dry weight) was (0.93±0.12) n·g-1. The abundance of microplastics in the near riparian zone soil (by dry weight) was (0.68±0.16) n·g-1, and that in the far riparian zone soil (by dry weight) was (0.69±0.14) n·g-1, and the abundance of microplastics in the B. aeruginosa was (2.06±0.25) n·g-1. The analysis results showed that the abundance of microplastics in the upper and lower sediments were positively correlated; the abundance of microplastics in B. aeruginosa was positively correlated with the abundance of microplastics in the upper and lower sediments, respectively; and the abundance of microplastics in the near and far riparian zone soils were also correlated. Most of the microplastics within each environmental medium and B. aeruginosa were <0.1 mm in size, mainly in the form of fibers and fragments, mainly blue and black in color, and mainly composed of polypropylene (PP) and polyethylene (PE). It was found that microplastics in riparian zone soils mainly originated from the fragmentation and decomposition of agricultural plastic films. The results of this study shed light on the accumulation of microplastics in macrobenthic organisms through the investigation of microplastics in multi-environmental media and in the B. aeruginosa, which helps us to understand the potential ecological risk of microplastics in a comprehensive manner.

Interpretable and Intuitive Machine Learning Approaches for Predicting Disability Progression in Relapsing-Remitting Multiple Sclerosis Based on Clinical and Gray Matter Atrophy Indicators.

RATIONALE AND OBJECTIVES: To investigate whether clinical and gray matter (GM) atrophy indicators can predict disability in relapsing-remitting multiple sclerosis (RRMS) and to enhance the interpretability and intuitiveness of a predictive machine learning model. MATERIALS AND METHODS: 145 and 50 RRMS patients with structural MRI and at least 1-year follow-up Expanded Disability Status Scale (EDSS) results were retrospectively enrolled and placed in the discovery and external test cohorts, respectively. Six clinical and radiomics feature-based machine learning classifiers were trained and tested to predict disability progression in the discovery cohort and validated in the external test set. Partial dependence plot (PDP) analysis and a Shiny web application were conducted to enhance the interpretability and intuitiveness. RESULTS: In the discovery cohort, 98 patients had disability stability, and 47 patients were classified as having disability progression. In the external test set, 35 patients were disability stable, and 15 patients had disability progression. Models trained with both clinical and radiomics features (area under the curve (AUC), 0.725-0.950) outperformed those trained with clinical (AUC, 0.600-0.740) or radiomics features only (AUC, 0.615-0.945). Among clinical+ radiomics feature models, the logistic regression (LR) classifier-based model performed best, with an AUC of 0.950. Only the radiomics feature-only models were applied in the external test set due to the data collection problem and showed fair performance, with AUCs ranging from 0.617 to 0.753. PDP analysis showed that female patients and those with lower volume, surface area, and symbol digit modalities test (SDMT) scores; greater mean curvature and age; and no disease modifying therapy (DMT) had increased probabilities of disease progression. Finally, a Shiny web application (https://lauralin1104.shinyapps.io/LRshiny/) was developed to calculate the risk of disability progression. CONCLUSION: Interpretable and intuitive machine learning approaches based on clinical and GM atrophy indicators can help physicians predict disability progression in RRMS patients for clinical decision-making and patient management.

Aberrant white matter microstructure detected by automatic fiber quantification in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease.

BACKGROUND AND OBJECTIVES: Myelin oligodendrocyte glycoprotein antibody-associated diseases (MOGAD) is an idiopathic inflammatory demyelinating disorder in children, for which the precise damage patterns of the white matter (WM) fibers remain unclear. Herein, we utilized diffusion tensor imaging (DTI)-based automated fiber quantification (AFQ) to identify patterns of fiber damage and to investigate the clinical significance of MOGAD-affected fiber tracts. METHODS: A total of 28 children with MOGAD and 31 healthy controls were included in this study. The AFQ approach was employed to track WM fiber with 100 equidistant nodes defined along each tract for statistical analysis of DTI metrics in both the entire and nodal manner. The feature selection method was used to further screen significantly aberrant DTI metrics of the affected fiber tracts or segments for eight common machine learning (ML) to evaluate their potential in identifying MOGAD. These metrics were then correlated with clinical scales to assess their potential as imaging biomarkers. RESULTS: In the entire manner, significantly reduced fractional anisotropy (FA) was shown in the left anterior thalamic radiation, arcuate fasciculus, and the posterior and anterior forceps of corpus callosum in MOGAD (all p < 0.05). In the nodal manner, significant DTI metrics alterations were widely observed across 37 segments in 10 fiber tracts (all p < 0.05), mainly characterized by decreased FA and increased radial diffusivity (RD). Among them, 14 DTI metrics in seven fiber tracts were selected as important features to establish ML models, and satisfactory discrimination of MOGAD was obtained in all models (all AUC > 0.85), with the best performance in the logistic regression model (AUC = 0.952). For those features, the FA of left cingulum cingulate and the RD of right inferior frontal-occipital fasciculus were negatively and positively correlated with the expanded disability status scale (r = -0.54, p = 0.014; r = 0.43, p = 0.03), respectively. CONCLUSION: Pediatric MOGAD exhibits extensive WM fiber tract aberration detected by AFQ. Certain fiber tracts exhibit specific patterns of DTI metrics that hold promising potential as biomarkers.

Radiomics derived from T2-FLAIR: the value of 2- and 3-classification tasks for different lesions in multiple sclerosis.

Background: White matter (WM) lesions can be classified into contrast enhancement lesions (CELs), iron rim lesions (IRLs), and non-iron rim lesions (NIRLs) based on different pathological mechanism in relapsing-remitting multiple sclerosis (RRMS). The application of radiomics established by T2-FLAIR to classify WM lesions in RRMS is limited, especially for 3-class classification among CELs, IRLs, and NIRLs. Methods: A total of 875 WM lesions (92 CELs, 367 IRLs, 416 NIRLs) were included in this study. The 2-class classification was only performed between IRLs and NIRLs. For the 2- and 3-class classification tasks, all the lesions were randomly divided into training and testing sets with a ratio of 8:2. We used least absolute shrinkage and selection operator (LASSO), reliefF algorithm, and mutual information (MI) for feature selection, then eXtreme gradient boosting (XGBoost), random forest (RF), and support vector machine (SVM) were used to establish discrimination models. Finally, the area under the curve (AUC), accuracy, sensitivity, specificity, and precision were used to evaluate the performance of the models. Results: For the 2-class classification model, LASSO classifier with RF model showed the best discrimination performance with the AUC of 0.893 (95% CI: 0.838-0.942), accuracy of 0.813, sensitivity of 0.833, specificity of 0.781, and precision of 0.851. However, the 3-class classification model of LASSO with XGBoost displayed the highest performance with the AUC of 0.920 (95% CI: 0.887-0.950), accuracy of 0.796, sensitivity of 0.839, specificity of 0.881, and precision of 0.846. Conclusions: Radiomics models based on T2-FLAIR images have the potential for discriminating among CELs, IRLs, and NIRLs in RRMS.

NS1-mediated enhancement of MVC transcription and replication promoted by KAT5/H4K12ac.

Histone modifications function in both cellular and viral gene expression. However, the roles of acetyltransferases and histone acetylation in parvoviral infection remain poorly understood. In the current study, we found the histone deacetylase (HDAC) inhibitor, trichostatin A (TSA), promoted the replication and transcription of parvovirus minute virus of canines (MVC). Notably, the expression of host acetyltransferases KAT5, GTF3C4, and KAT2A was increased in MVC infection, as well as H4 acetylation (H4K12ac). KAT5 is not only responsible for H4K12ac but also crucial for viral replication and transcription. The viral nonstructural protein NS1 interacted with KAT5 and enhanced its expression. Further study showed that Y44 in KAT5, which may be tyrosine-phosphorylated, is indispensable for NS1-mediated enhancement of KAT5 and efficient MVC replication. The data demonstrated that NS1 interacted with KAT5, which resulted in an enhanced H4K12ac level to promote viral replication and transcription, implying the epigenetic addition of H4K12ac in viral chromatin-like structure by KAT5 is vital for MVC replication.IMPORTANCEParvoviral genomes are chromatinized with host histones. Therefore, histone acetylation and related acetyltransferases are required for the virus to modify histones and open densely packed chromatin structures. This study illustrated that histone acetylation status is important for MVC replication and transcription and revealed a novel mechanism that the viral nonstructural protein NS1 hijacks the host acetyltransferase KAT5 to enhance histone acetylation of H4K12ac, which relies on a potential tyrosine phosphorylation site, Y44 in KAT5. Other parvoviruses share a similar genome organization and coding potential and may adapt a similar strategy for efficient viral replication and transcription.