[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.

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.

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.

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.

[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.

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.

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.

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.

Current progression in application of extracellular vesicles in central nervous system diseases.

Early diagnosis and pharmacological treatment of central nervous system (CNS) diseases has been a long-standing challenge for clinical research due to the presence of the blood-brain barrier. Specific proteins and RNAs in brain-derived extracellular vesicles (EVs) usually reflect the corresponding state of brain disease, and therefore, EVs can be used as diagnostic biomarkers for CNS diseases. In addition, EVs can be engineered and fused to target cells for delivery of cargo, demonstrating the great potential of EVs as a nanocarrier platform. We review the progress of EVs as markers and drug carriers in the diagnosis and treatment of neurological diseases. The main areas include visual imaging, biomarker diagnosis and drug loading therapy for different types of CNS diseases. It is hoped that increased knowledge of EVs will facilitate their clinical translation in CNS diseases.

Epigenetic addition of m5C to HBV transcripts promotes viral replication and evasion of innate antiviral responses.

Eukaryotic five-methylcytosine (m5C) is an important regulator of viral RNA splicing, stability, and translation. However, its role in HBV replication remains largely unknown. In this study, functional m5C sites are identified in hepatitis B virus (HBV) mRNA. The m5C modification at nt 1291 is not only indispensable for Aly/REF export factor (ALYREF) recognition to promote viral mRNA export and HBx translation but also for the inhibition of RIG-I binding to suppress interferon-ß (IFN-ß) production. Moreover, NOP2/Sun RNA methyltransferase 2 (NSUN2) catalyzes the addition of m5C to HBV mRNA and is transcriptionally downregulated by the viral protein HBx, which suppresses the binding of EGR1 to the NSUN2 promoter. Additionally, NSUN2 expression correlates with m5C modification of type I IFN mRNA in host cells, thus, positively regulating IFN expression. Hence, the delicate regulation of NSUN2 expression induces m5C modification of HBV mRNA while decreasing the levels of m5C in host IFN mRNA, making it a vital component of the HBV life cycle. These findings provide new molecular insights into the mechanism of HBV-mediated IFN inhibition and may inform the development of new IFN-α based therapies.

Levels of neuronal pentraxin 2 in plasma is associated with cognitive function in patients with schizophrenia.

RATIONALE: The precise diagnosis and treatment of cognitive impairment remains a major challenge in the field of schizophrenia (SCZ) research. Synaptic dysfunction and loss are thought to be closely related to the occurrence and development of SCZ and may be involved in cognitive dysfunction. OBJECTIVES: The purpose of this study was to investigate whether neuronal pentraxins (NPTXs) plays a role in the etiology of SCZ and provide evidence of its possible therapeutic value a new target for drug development. METHODS: We recruited 275 participants, of whom 148 were SCZ from psychiatric hospital and 127 healthy control (HC) subjects from communities. Plasma concentrations of NPTXs were measured in HC and SCZ at baseline and after 8 weeks of antipsychotic treatment. The MATRICS Cognitive Consensus Battery was used to evaluate cognitive function. Furthermore, the brain is parcellated into 246 subregions using the Brainnetome atlas, and we extracted regional white matter volumes from magnetic resonance images of the SCZ groups. RESULTS: Plasma NPTX2 levels were significantly lower in SCZ compared with HC subjects, but were significantly raised in SCZ after 8 weeks of antipsychotic treatment compared to baseline. In addition, baseline plasma NPTX2 levels were positively correlated with cognitive performance. CONCLUSIONS: These findings indicate that NPTX2 may reveal novel aspects of disease etiology and act as a promising target for new drug development.

VXX-401, a novel anti-PCSK9 vaccine, reduces LDL-C in cynomolgus monkeys.

Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of disease burden in the world and is highly correlated with chronic elevations of LDL-C. LDL-C-lowering drugs, such as statins or monoclonal antibodies against proprotein convertase subtilisin/kexin type 9 (PCSK9), are known to reduce the risk of cardiovascular diseases; however, statins are associated with limited efficacy and poor adherence to treatment, whereas PCSK9 inhibitors are only prescribed to a "high-risk" patient population or those who have failed other therapies. Based on the proven efficacy and safety profile of existing monoclonal antibodies, we have developed a peptide-based vaccine against PCSK9, VXX-401, as an alternative option to treat hypercholesterolemia and prevent ASCVD. VXX-401 is designed to trigger a safe humoral immune response against PCSK9, resulting in the production of endogenous antibodies and a subsequent 30-40% reduction in blood LDL-C. In this article, VXX-401 demonstrates robust immunogenicity and sustained serum LDL-C-lowering effects in nonhuman primates. In addition, antibodies induced by VXX-401 bind to human PCSK9 with high affinity and block the inhibitory effect of PCSK9 on LDL-C uptake in a hepatic cell model. A repeat-dose toxicity study conducted in nonhuman primates under good laboratory practices toxicity indicated a suitable safety and tolerability profile, with injection site reactions being the main findings. As a promising safe and effective LDL-C-lowering therapy, VXX-401 may represent a broadly accessible and convenient option to treat hypercholesterolemia and prevent ASCVD.

Aberrant brain intra- and internetwork functional connectivity in children with Prader-Willi syndrome.

PURPOSE: Prader-Willi syndrome (PWS) suffers from brain functional reorganization and developmental delays during childhood, but the underlying neurodevelopmental mechanism is unclear. This paper aims to investigate the intra- and internetwork functional connectivity (FC) changes, and their relationships with developmental delays in PWS children. METHODS: Resting-state functional magnetic resonance imaging datasets of PWS children and healthy controls (HCs) were acquired. Independent component analysis was used to acquire core resting-state networks (RSNs). The intra- and internetwork FC patterns were then investigated. RESULTS: In terms of intranetwork FC, children with PWS had lower FC in the dorsal attention network, the auditory network, the medial visual network (VN) and the sensorimotor network (SMN) than HCs (FWE-corrected, p < 0.05). In terms of internetwork FC, PWS children had decreased FC between the following pairs of regions: posterior default mode network (DMN) and anterior DMN; posterior DMN and SMN; SMN and posterior VN and salience network and medial VN (FDR-corrected, p < 0.05). Partial correlation analyses revealed that the intranetwork FC patterns were positively correlated with developmental quotients in PWS children, while the internetwork FC patterns were completely opposite (p < 0.05). Intranetwork FC patterns showed an area under the receiver operating characteristic curve of 0.947, with a sensitivity of 96.15% and a specificity of 81.25% for differentiating between PWS and HCs. CONCLUSION: Impaired intra- and internetwork FC patterns in PWS children are associated with developmental delays, which may result from neural pathway dysfunctions. Intranetwork FC reorganization patterns can discriminate PWS children from HCs. REGISTRATION NUMBER ON THE CHINESE CLINICAL TRAIL REGISTRY: ChiCTR2100046551.

The Function, Underlying Mechanism and Clinical Potential of Exosomes in Colorectal Cancer.

Colorectal cancer (CRC) is a lethal malignancy worldwide. Exosomes are extracellular vesicles derived from the endosomal pathway of nearly all cells and can be found in body fluids. They can be considered an intercellular system in the human body that can mediate near- and long-distance intercellular communication due to their features and functions. Investigations have revealed that exosomes are participated in different processes, physiologically and pathologically, especially in cancer. However, the clinical value of exosomes and their mechanisms of action in CRC are unclear and have not been systematically assessed. The purpose of this review is to discuss how exosomes play a role in the occurrence and development of CRC, with a particular focus on the functions and underlying mechanisms of tumor-derived exosomes as well as non-tumor-derived exosomes. We also describe the evidence that exosomes can be used as diagnostic and prognostic markers for CRC. In addition, the possibilities of exosomes in CRC clinical transformation are also discussed.

Imaging cellular forces with photonic crystals.

Current techniques for visualizing and quantifying cellular forces have limitations in live cell imaging, throughput, and multi-scale analysis, which impede progress in cell force research and its practical applications. We developed a photonic crystal cellular force microscopy (PCCFM) to image vertical cell forces over a wide field of view (1.3 mm ⨯ 1.0 mm, a 10 ⨯ objective image) at high speed (about 20 frames per second) without references. The photonic crystal hydrogel substrate (PCS) converts micro-nano deformations into perceivable color changes, enabling in situ visualization and quantification of tiny vertical cell forces with high throughput. It enabled long-term, cross-scale monitoring from subcellular focal adhesions to tissue-level cell sheets and aggregates.

Revealing the impact of TOX3 on osteoarthritis: insights from bioinformatics.

Osteoarthritis, a prevalent long-term condition of the joints, primarily impacts older individuals, resulting in discomfort, restrictions in mobility, and a decrease in overall well-being. Although Osteoarthritis is widely spread, there is a lack of successful interventions to stop the advancement of the condition. Numerous signaling pathways have been emphasized in recent research on Osteoarthritis, yet the diagnostic significance of numerous genes has not been investigated. To identify genes that were expressed differently in osteoarthritis, we utilized the Gene Expression Omnibus database. To identify marker genes, we built machine learning models including Least Absolute Shrinkage and Selection Operator and Random Forest. We categorized Osteoarthritis samples and performed immune cell infiltration analysis based on the expression patterns of these characteristic genes. Both the Least Absolute Shrinkage and Selection Operator and Random Forest models selected six marker genes (TOX3, ARG1, CST7, RERGL, COL11A1, NCRNA00185) out of a total of 17 differentially expressed genes. The osteoarthritis samples were categorized into two groups, namely a high expression group and a low expression group, based on the median levels of TOX3 expression. Comparative analysis of these groups identified 85 differentially expressed genes, showing notable enrichment in pathways related to lipid metabolism in the group with high expression. Analysis of immune cell infiltration revealed noticeable differences in immune profiles among the two groups. The group with high expression of TOX3 showed a notable increase in Mast cells and Type II IFN Response, whereas B cells, Cytolytic activity, Inflammation-promoting cells, NK cells, pDCs, T cell co-inhibition, Th1 cells, and Th2 cells were significantly decreased. We constructed a ceRNA network for TOX3, revealing 57 lncRNAs and 18 miRNAs involved in 57 lncRNA-miRNA interactions, and 18 miRNA-mRNA interactions with TOX3. Validation of TOX3 expression was confirmed using an external dataset (GSE29746), revealing a notable increase in Osteoarthritis samples. In conclusion, our study presents a comprehensive analysis identifying TOX3 as a potential feature gene in Osteoarthritis. The distinct immune profiles and involvement in fat metabolism pathways associated with TOX3 expression suggest its significance in Osteoarthritis pathogenesis. The study establishes a basis for comprehending the intricate correlation between characteristic genes and Osteoarthritis, as well as for the formulation of individualized therapeutic approaches.

Classification of Myelin Oligodendrocyte Glycoprotein Antibody-Related Disease and Its Mimicking Acute Demyelinating Syndromes in Children Using MRI-Based Radiomics: From Lesion to Subject.

RATIONALE AND OBJECTIVES: To develop MRI-based radiomics models from the lesion level to the subject level and assess their value for differentiating myelin oligodendrocyte glycoprotein antibody-related disease (MOGAD) from non-MOGAD acute demyelinating syndromes in pediatrics. MATERIALS AND METHODS: 66 MOGAD and 66 non-MOGAD children were assigned to the training set (36/35), internal test set (14/16), and external test set (16/15), respectively. At the lesion level, five single-sequence models were developed alongside a fusion model (combining these five sequences). The radiomics features of each lesion were quantified as the lesion-level radscore (LRS) using the best-performing model. Subsequently, a lesion-typing function was employed to classify lesions into two types (MOGAD-like or non-MOGAD-like), and the average LRS of the predominant type lesions in each subject was considered as the subject-level radscore (SRS). Based on SRS, a subject-level model was established and compared to both clinical models and radiologists' assessments. RESULTS: At the lesion level, the fusion model outperformed the five single-sequence models in distinguishing MOGAD and non-MOGAD lesions (0.867 and 0.810 of area under the curve [AUC] in internal and external testing, respectively). At the subject level, the SRS model showed superior performance (0.844 and 0.846 of AUC in internal and external testing, respectively) compared to clinical models and radiologists' assessments for distinguishing MOGAD and non-MOGAD. CONCLUSION: MRI-based radiomics models have potential clinical value for identifying MOGAD from non-MOGAD. The fusion model and SRS model can distinguish between MOGAD and non-MOGAD at the lesion level and subject level, respectively, providing a differential diagnosis method for these two diseases.