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Osteoarthritis (OA) is a chronic progressive osteoarthropathy in the elderly. Osteoclast activation plays a crucial role in the occurrence of subchondral bone loss in early OA. However, the specific mechanism of osteoclast differentiation in OA remains unclear. In our study, gene expression profiles related to OA disease progression and osteoclast activation were screened from the Gene Expression Omnibus (GEO) repository. GEO2R and Funrich analysis tools were employed to find differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses demonstrated that chemical carcinogenesis, reactive oxygen species (ROS), and response to oxidative stress were mainly involved in osteoclast differentiation in OA subchondral bone. Furthermore, fourteen DEGs that are associated with oxidative stress were identified. The first ranked differential gene, heme oxygenase 1 (HMOX1), was selected for further validation. Related results showed that osteoclast activation in the pathogenesis of OA subchondral bone is accompanied by the downregulation of HMOX1. Carnosol was revealed to inhibit osteoclastogenesis by targeting HMOX1 and upregulating the expression of antioxidant protein in vitro. Meanwhile, carnosol was found to alleviate the severity of OA by inhibiting the activation of subchondral osteoclasts in vivo. Our research indicated that the activation of osteoclasts due to subchondral bone redox dysplasia may serve as a significant pathway for the advancement of OA. Targeting HMOX1 in subchondral osteoclasts may offer novel insights for the treatment of early OA.

Aggregation-Induced Emission CN-Based Nanoparticles to Alleviate Hypoxic Liver Fibrosis via Triggering HSC Ferroptosis and Enhancing Photodynamic Therapy.

Hypoxia can lead to liver fibrosis and severely limits the efficacy of photodynamic therapy (PDT). Herein, carbon nitride (CN)-based hybrid nanoparticles (NPs) VPSGCNs@TSI for light-driven water splitting were utilized to solve this problem. CNs were doped with selenide glucose (Se-glu) to enhance their red/NIR region absorption. Then, vitamin A-poly(ethylene glycol) (VA-PEG) fragments and aggregation-induced emission (AIE) photosensitizers TSI were introduced into Se-glu-doped CN NPs (VPSGCNs) to construct VPSGCNs@TSI NPs. The introduction of VA-PEG fragments enhanced the targeting of the NPs to activated hepatic stellate cells (HSCs) and reduced their toxicity to ordinary liver cells. VPSGCN units could trigger water splitting to generate O2 under 660 nm laser irradiation, improve the hypoxic environment of the fibrosis site, downregulate HIF-1α expression, and activate HSC ferroptosis via the HIF-1α/SLC7A11 pathway. In addition, generated O2 could also increase the reactive oxygen species (ROS) production of TSI units in a hypoxic environment, thereby completely reversing hypoxia-triggered PDT resistance to enhance the PDT effect. The combination of water-splitting materials and photodynamic materials showed a 1 + 1 > 2 effect in increasing oxygen levels in liver fibrosis, promoting ferroptosis of activated HSCs and reversing PDT resistance caused by hypoxia.

Partial Discharge Signal Pattern Recognition of Composite Insulation Defects in Cross-Linked Polyethylene Cables.

To investigate the pattern recognition of complex defect types in XLPE (cross-linked polyethylene) cable partial discharges and analyze the effectiveness of identifying partial discharge signal patterns, this study employs the variational mode decomposition (VMD) algorithm alongside entropy theories such as power spectrum entropy, fuzzy entropy, and permutation entropy for feature extraction from partial discharge signals of composite insulation defects. The mean power spectrum entropy (PS), mean fuzzy entropy (FU), mean permutation entropy (PE), as well as the permutation entropy values of IMF2 and IMF13 (Pe) are selected as the characteristic quantities for four categories of partial discharge signals associated with composite defects. Six hundred samples are selected from the partial discharge signals of each type of compound defect, amounting to a total of 2400 samples for the four types of compound defects combined. Each sample comprises five feature values, which are compiled into a dataset. A Snake Optimization Algorithm-optimized Support Vector Machine (SO-SVM) model is designed and trained, using the extracted features from cable partial discharge datasets as case examples for recognizing cable partial discharge signals. The identification outcomes from the SO-SVM model are then compared with those from conventional learning models. The results demonstrate that for partial discharge signals of XLPE cable composite insulation defects, the SO-SVM model yields better identification results than traditional learning models. In terms of recognition accuracy, for scratch and water ingress defects, SO-SVM improves by 14.00% over BP (Back Propagation) neural networks, by 5.66% over GA-BP (Genetic Algorithm-Back Propagation), and by 12.50% over SVM (support vector machine). For defects involving metal impurities and scratches, SO-SVM improves by 13.39% over BP, 9.34% over GA-BP, and 12.56% over SVM. For defects with metal impurities and water ingress, SO-SVM shows enhancements of 13.80% over BP, 9.47% over GA-BP, and 13.97% over SVM. Lastly, for defects combining metal impurities, water ingress, and scratches, SO-SVM registers increases of 11.90% over BP, 9.59% over GA-BP, and 12.05% over SVM.

MIF inhibition attenuates intervertebral disc degeneration by reducing nucleus pulposus cell apoptosis and inflammation.

Nucleus pulposus cells (NPCs) apoptosis and inflammation are the extremely critical factors of intervertebral disc degeneration (IVDD). Nevertheless, the underlying procedure remains mysterious. Macrophage migration inhibitory factor (MIF) is a cytokine that promotes inflammation and has been demonstrated to have a significant impact on apoptosis and inflammation. For this research, we employed a model of NPCs degeneration stimulated by lipopolysaccharides (LPS) and a rat acupuncture IVDD model to examine the role of MIF in vitro and in vivo, respectively. Initially, we verified that there was a significant rise of MIF expression in the NP tissues of individuals with IVDD, as well as in rat models of IVDD. Furthermore, this augmented expression of MIF was similarly evident in degenerated NPCs. Afterwards, it was discovered that ISO-1, a MIF inhibitor, effectively decreased the quantity of cells undergoing apoptosis and inhibited the release of inflammatory molecules (TNF-α, IL-1ß, IL-6). Furthermore, it has been shown that the PI3K/Akt pathway plays a vital part in the regulation of NPCs degeneration by MIF. Ultimately, we showcased that the IVDD process was impacted by the MIF inhibitor in the rat model. In summary, our experimental results substantiate the significant involvement of MIF in the degeneration of NPCs, and inhibiting MIF activity can effectively mitigate IVDD.

Cerebral 18F-FDG PET/CT Metabolism as Diagnostic Signature for Central Nervous System Toxicity After Immune Checkpoint Blockade Cancer Treatment.

Our aim was to investigate probable biomarkers specific to immune-related central nervous system toxicity (CNST) in cancer patients treated with immune checkpoint inhibitors (ICI) by analysis of 18F-FDG PET/CT images. Methods: Cancer patients receiving ICI treatment were enrolled in a multicenter observational study that analyzed regional metabolic changes before and during CNST onset from January 2020 to February 2022. In 1:1 propensity score-matched pairs, the regional SUVmean of each bilateral brain lobe of CNST patients (CNST+) was compared with that of patients who had central nervous system infections (CNSIs) and patients without CNST or CNSI (CNST-). In a validation cohort, patients were recruited from February 2022 to July 2023 and followed up for 24 wk after the start of ICI. Early changes in regional SUVmean at 5-6 wk after therapy initiation were evaluated for ability to predict later CNST onset. Results: Of 6,395 ICI-treated patients, 2,387 underwent prognostic 18F-FDG PET/CT and 125 of the scanned patients had CNST (median time from ICI treatment to onset, 9 wk; quartile range, 2-23 wk). Regional 18F-FDG PET/CT SUVmean changes were higher in CNST+ than in CNST- patients (117 patient pairs) but were lower than in CNSI patients (50 pairs). Differentiating analysis reached an area under the curve (AUC) of 0.83 (95% CI, 0.78-0.88) for CNST+ versus CNST- and of 0.80 (95% CI, 0.72-0.89) for CNST+ versus CNSI. Changes in SUVmean were also higher before CNST onset than for CNST- (60 pairs; AUC, 0.74; 95% CI, 0.66-0.83). In a validation cohort of 2,878 patients, preonset changes in SUVmean reached an AUC of 0.86 (95% CI, 0.79-0.94) in predicting later CNST incidence. Conclusion: Brain regional hypermetabolism could be detected during and before CNST clinical onset. CNST may be a distinct pathologic entity versus brain infections defined by 18F-FDG PET/CT brain scans. Regional SUV differences may be translated into early diagnostic tools based on moderate differentiating accuracy in our study.

Catalytic Oxidation of Chlorobenzene over Amorphous Manganese-Chromium Catalysts Supported by UiO-66-Derived ZrOx.

The development of efficient catalysts with longevity to remove chlorobenzene is challenging due to Cl poisoning. Herein, a series of Mn-Cr/ZrOx catalysts supported by Zr-based metal-organic framework (UiO-66)-derived ZrOx was prepared and investigated for chlorobenzene (CB) catalytic oxidation. MnCr/ZrOx-M prepared via a wet impregnation method presented an amorphous structure, indicating the homogeneous dispersion of Cr and Mn, which improved acid and redox properties. 40Mn7Cr3/ZrOx-M exhibited the best catalytic activity for chlorobenzene oxidation with T90 of 293 °C, which is mainly due to the strong interaction between manganese and chromium promoted by the large specific surface area of the ZrOx support. Furthermore, 40Mn7Cr3/ZrOx-M presented excellent stability for chlorobenzene oxidation.

The Important Role of Preoperative D-Dimer in Constrictive Pericarditis.

Background: The impact of coagulation indicators on postoperative outcomes of patients with constrictive pericarditis undergoing pericardiectomy has been poorly investigated. This study aimed to assess the prognostic role of preoperative coagulation indicators in these patients. Methods: We retrospectively included 158 patients with constrictive pericarditis undergoing pericardiectomy. The diagnostic values of coagulation indicators for postoperative complications were evaluated by ROC curves. Patients were divided into two groups according to the cutoff value calculated by ROC curve. Postoperative outcomes were compared between the two groups. Logistic regression analysis was performed to identify risk factors of postoperative complications. Results: ROC curve showed that among different coagulation indicators, preoperative D-dimer (DD) level could effectively identify patients with postoperative complications (AUC 0.771, 95% CI 0.696-0.847, P < 0.001). Patients were divided into the low DD group and the high DD group. The comparison of postoperative outcomes suggested that high preoperative DD level was significantly associated with longer durations of vasoactive agents using (P = 0.018), intubation (P = 0.020), ICU stay (P = 0.008), chest drainage (P=0.004) and hospital stay (P = 0.002). Multivariable analysis showed that high preoperative DD level was the independent risk factor of postoperative complications (OR 6.892, 95% CI 2.604-18.235, P < 0.001). Conclusion: High preoperative DD level was significantly linked to poor postoperative outcomes and could provide an effective prediction ability for postoperative complications in patients with constrictive pericarditis.

Expanded Archaeal Genomes Shed New Light on the Evolution of Isoprenoid Biosynthesis.

Isoprenoids and their derivatives, essential for all cellular life on Earth, are particularly crucial in archaeal membrane lipids, suggesting that their biosynthesis pathways have ancient origins and play pivotal roles in the evolution of early life. Despite all eukaryotes, archaea, and a few bacterial lineages being known to exclusively use the mevalonate (MVA) pathway to synthesize isoprenoids, the origin and evolutionary trajectory of the MVA pathway remain controversial. Here, we conducted a thorough comparison and phylogenetic analysis of key enzymes across the four types of MVA pathway, with the particular inclusion of metagenome assembled genomes (MAGs) from uncultivated archaea. Our findings support an archaeal origin of the MVA pathway, likely postdating the divergence of Bacteria and Archaea from the Last Universal Common Ancestor (LUCA), thus implying the LUCA's enzymatic inability for isoprenoid biosynthesis. Notably, the Asgard archaea are implicated in playing central roles in the evolution of the MVA pathway, serving not only as putative ancestors of the eukaryote- and Thermoplasma-type routes, but also as crucial mediators in the gene transfer to eukaryotes, possibly during eukaryogenesis. Overall, this study advances our understanding of the origin and evolutionary history of the MVA pathway, providing unique insights into the lipid divide and the evolution of early life.

Rapid identification of lactic acid bacteria at species/subspecies level via ensemble learning of Ramanomes.

Rapid and accurate identification of lactic acid bacteria (LAB) species would greatly improve the screening rate for functional LAB. Although many conventional and molecular methods have proven efficient and reliable, LAB identification using these methods has generally been slow and tedious. Single-cell Raman spectroscopy (SCRS) provides the phenotypic profile of a single cell and can be performed by Raman spectroscopy (which directly detects vibrations of chemical bonds through inelastic scattering by a laser light) using an individual live cell. Recently, owing to its affordability, non-invasiveness, and label-free features, the Ramanome has emerged as a potential technique for fast bacterial detection. Here, we established a reference Ramanome database consisting of SCRS data from 1,650 cells from nine LAB species/subspecies and conducted further analysis using machine learning approaches, which have high efficiency and accuracy. We chose the ensemble meta-classifier (EMC), which is suitable for solving multi-classification problems, to perform in-depth mining and analysis of the Ramanome data. To optimize the accuracy and efficiency of the machine learning algorithm, we compared nine classifiers: LDA, SVM, RF, XGBoost, KNN, PLS-DA, CNN, LSTM, and EMC. EMC achieved the highest average prediction accuracy of 97.3% for recognizing LAB at the species/subspecies level. In summary, Ramanomes, with the integration of EMC, have promising potential for fast LAB species/subspecies identification in laboratories and may thus be further developed and sharpened for the direct identification and prediction of LAB species from fermented food.

CCP-GNN: Competitive Covariance Pooling for Improving Graph Neural Networks.

Graph neural networks (GNNs) have advanced graph classification tasks, where a global pooling to generate graph representations by summarizing node features plays a critical role in the final performance. Most of the existing GNNs are built with a global average pooling (GAP) or its variants, which however, take no full consideration of node specificity while neglecting rich statistics inherent in node features, limiting classification performance of GNNs. Therefore, this article proposes a novel competitive covariance pooling (CCP) based on observation of graph structures, i.e., graphs generally can be identified by a (small) key part of nodes. To this end, our CCP generates node-level second-order representations to explore rich statistics inherent in node features, which are fed to a competitive-based attention module for effectively discovering key nodes through learning node weights. Subsequently, our CCP aggregates node-level second-order representations in conjunction with node weights by summation to produce a covariance representation for each graph, while an iterative matrix normalization is introduced to consider geometry of covariances. Note that our CCP can be flexibly integrated with various GNNs (namely CCP-GNN) to improve the performance of graph classification with little computational cost. The experimental results on seven graph-level benchmarks show that our CCP-GNN is superior or competitive to state-of-the-arts. Our code is available at https://github.com/Jillian555/CCP-GNN.

Multiview Deep Subspace Clustering Networks.

Multiview subspace clustering aims to discover the inherent structure of data by fusing multiple views of complementary information. Most existing methods first extract multiple types of handcrafted features and then learn a joint affinity matrix for clustering. The disadvantage of this approach lies in two aspects: 1) multiview relations are not embedded into feature learning and 2) the end-to-end learning manner of deep learning is not suitable for multiview clustering. Even when deep features have been extracted, it is a nontrivial problem to choose a proper backbone for clustering on different datasets. To address these issues, we propose the multiview deep subspace clustering networks (MvDSCNs), which learns a multiview self-representation matrix in an end-to-end manner. The MvDSCN consists of two subnetworks, i.e., a diversity network (Dnet) and a universality network (Unet). A latent space is built using deep convolutional autoencoders, and a self-representation matrix is learned in the latent space using a fully connected layer. Dnet learns view-specific self-representation matrices, whereas Unet learns a common self-representation matrix for all views. To exploit the complementarity of multiview representations, the Hilbert-Schmidt independence criterion (HSIC) is introduced as a diversity regularizer that captures the nonlinear, high-order interview relations. Because different views share the same label space, the self-representation matrices of each view are aligned to the common one by universality regularization. The MvDSCN also unifies multiple backbones to boost clustering performance and avoid the need for model selection. Experiments demonstrate the superiority of the MvDSCN.

Flying Target Detection Technology Based on GNSS Multipath Signals.

In this study, a passive radar system that detects flying targets is developed in order to solve the problems associated with traditional flying target detection systems (i.e., their large size, high power consumption, complex systems, and poor battlefield survivability). On the basis of target detection, the system uses the multipath signal (which is usually eliminated as an error term in navigation and positioning), enhances it by supporting information, and utilizes the multi-source characteristics of ordinary omnidirectional global navigation satellite system (GNSS) signals. The results of a validation experiment showed that the system is able to locate a passenger airplane and obtain its flight trajectory using only one GNSS receiving antenna. The system is characterized by its light weight (less than 5 kg), low power consumption, simple system, good portability, low cost, and 24/7 and all-weather work. It can be installed in large quantities and has good prospects for development.

Preimplantation genetic testing as a means of preventing hereditary congenital myasthenic syndrome caused by RAPSN.

BACKGROUND: Congenital myasthenic syndrome is a heterogeneous group of inherited neuromuscular transmission disorders. Variants in RAPSN are a common cause of CMS, accounting for approximately 14%-27% of all CMS cases. Whether preimplantation genetic testing for monogenic disease (PGT-M) could be used to prevent the potential birth of CMS-affected children is unclear. METHODS: Application of WES (whole-exome sequencing) for carrier testing and guidance for the PGT-M in the absence of a genetically characterized index patient as well as assisted reproductive technology were employed to prevent the occurrence of birth defects in subsequent pregnancy. The clinical phenotypes of stillborn fetuses were also assessed. RESULTS: The family carried two likely pathogenic variants in RAPSN(NM_005055.5): c.133G>A (p.V45M) and c.280G>A (p.E94K). And the potential birth of CMS-affected child was successfully prevented, allowing the family to have offspring devoid of disease-associated variants and exhibiting a normal phenotype. CONCLUSION: This report constitutes the first documented case of achieving a CMS-free offspring through PGT-M in a CMS-affected family. By broadening the known variant spectrum of RAPSN in the Chinese population, our findings underscore the feasibility and effectiveness of PGT-M for preventing CMS, offering valuable insights for similarly affected families.

Factor structure and longitudinal invariance for the Chinese Mainland version of the Edinburgh postnatal depression scale during pregnancy.

BACKGROUND: There are inconsistent results on the Edinburgh Postnatal Depression Scale's (EPDS) factor structure and longitudinal invariance among different cultures. Furthermore, limited relevant studies in Chinese pregnant women exist. PURPOSE: To test the factor structure of the Chinese Mainland EPDS during pregnancy and conduct longitudinal invariance analyses. METHODS: A national multi-centre cohort study was conducted among 1207 pregnant women selected consecutively by convenience sampling from five hospitals in Zhuhai, Taiyuan, Haidian, Changchun, and Shenzhen in China between August 2015 and October 2016. Depression was measured by the EPDS during gestational weeks 10-13, 15-18, 23-25, 30-32 and 36-37, respectively.s RESULTS: Three factors with eigenvalues nearly larger than 1.0 were optimal for the Chinese Mainland EPDS, labelled "anxiety," "anhedonia," and "depression," and contained items 3-5, 1-2, and 6-10, respectively. The confirmatory factor analysis results of standardized root mean square residual (SRMR) = 0.034, root mean square error of approximation (RMSEA) = 0.049, comparative fit index (CFI) = 0.968, Tucker-Lewis index (TLI) = 0.954, and χ2, p < 0.05 indicated good fit. For the longitudinal invariance tests, the configural invariance was met, with the CFI and TLI both higher than 0.90 and the RMSEA lower than 0.08 (CFI = 0.919, TLI = 0.908, and RMSEA = 0.034). The metric-, scalar-, and strict invariances were met. CONCLUSIONS: The three-factor model of the Chinese Mainland EPDS is invariant in pregnancy, suggesting stability and comparability in identifying the women screened positive at different points during pregnancy and making the scale feasible to screen prenatal depression and anxiety simultaneously.

CircAKT3 alleviates postoperative cognitive dysfunction by stabilizing the feedback cycle of miR-106a-5p/HDAC4/MEF2C axis in hippocampi of aged mice.

Circular RNAs (circRNAs) have garnered significant attention in the field of neurodegenerative diseases including Alzheimer's diseases due to their covalently closed loop structure. However, the involvement of circRNAs in postoperative cognitive dysfunction (POCD) is still largely unexplored. To identify the genes differentially expressed between non-POCD (NPOCD) and POCD mice, we conducted the whole transcriptome sequencing initially in this study. According to the expression profiles, we observed that circAKT3 was associated with hippocampal neuronal apoptosis in POCD mice. Moreover, we found that circAKT3 overexpression reduced apoptosis of hippocampal neurons and alleviated POCD. Subsequently, through bioinformatics analysis, our data showed that circAKT3 overexpression in vitro and in vivo elevated the abundance of miR-106a-5p significantly, resulting in a decrease of HDAC4 protein and an increase of MEF2C protein. Additionally, this effect of circAKT3 was blocked by miR-106a-5p inhibitor. Interestingly, MEF2C could activate the transcription of miR-106a-5p promoter and form a positive feedback loop. Therefore, our findings revealed more potential modulation ways between circRNA-miRNA and miRNA-mRNA, providing different directions and targets for preclinical studies of POCD.

Efficacy of Dan'e Fukang Soft Extract in Moderate Ovarian Hyperstimulation Syndrome for Concurrent Treatment of Blood and Fluid Guided by the "Triple Prevention" Principle.

Objective: This study aimed to evaluate the therapeutic efficacy and safety of Dan'e Fukang soft extracts in moderate ovarian hyperstimulation syndrome (OHSS) for the simultaneous treatment of blood and fluid, guided by the traditional Chinese medicine principle of "triple prevention". Methods: This study conducted a retrospective analysis of clinical data from outpatients who underwent in vitro fertilization (IVF)/intracytoplasmic sperm injection embryo transfer (ICSI-ET). A total of 2245 cases were included and divided into a treatment group (1002 cases) and a control group (1243 cases). Patients in the treatment group were administered Dan'e Fukang soft extracts orally in addition to conventional Western medicine. Comparative assessments were made between the two groups on pelvic ascites volume, maximum ovary diameter, dysmenorrhea incidence post-oocyte retrieval, and safety indicators. Results: There were no statistically significant differences between the treatment group and the control group in terms of general characteristics or the levels of follicle-stimulating hormone (FSH), luteotropic hormone (LH), estradiol (E2), or progesterone (P) at the time of gonadotropin (Gn) initiation. The groups did not differ significantly when we compared the levels of LH, E2, or P on the day of human chorionic gonadotropin (hCG) injection and during ovarian hyperstimulation protocols (P > 0.05 for all indicators). The differences in the volume of pelvic ascites, the maximum ovarian diameter, and the incidence of dysmenorrhea after oocyte retrieval were statistically significant between the treatment group and the control group (P < 0.05 in both). There were no instances of adverse reactions in either group. Conclusion: Based on the traditional Chinese medicine principle of "triple prevention", the use of Dan'e Fukang soft extracts for the simultaneous treatment of blood and fluid in moderate OHSS significantly improved the absorption of pelvic ascites, promoted ovarian recovery, and reduced the incidence of dysmenorrhea after oocyte retrieval.

Self-induced electron attraction center formation with pyrophosphorylation strategy for photocatalytic hydrogen evolution.

An integral approach towards augmenting the performance of photocatalytic hydrogen production lies in the induction of charge transfer mediators within the material matrix itself, thereby facilitating swift and efficient charge transfer processes. Here, CoTiO3 is induced to grow its electronic attraction center, CoP3, through a high-temperature phosphatization strategy. CoP3 acts as the active reduction site for the hydrogen evolution reaction and enhances the photocatalytic performance of the pristine catalyst. Compared with pure CoTiO3, the PCTO7 hybrid catalyst with the electronic attraction center CoP3 exhibits a superior photocatalytic performance and good stability. Experimental results show that the hydrogen evolution performance of the PCTO7 hybrid catalyst reaches 56.52 µmol, which is 78 times higher than that of the single catalyst CoTiO3 (0.72 µmol). These results demonstrate that the hybrid catalyst with the self-induced electronic attraction center has a higher light absorption capacity, faster charge carrier dynamics and improved photogenerated charge carrier separation and transfer than pure CoTiO3, resulting in excellent redox capability. DFT calculations provide evidence supporting the topological metal properties of CoP3 as the electron sink center. This study provides a feasible approach for enhancing the photocatalytic performance of a pristine catalyst employing a high-temperature phosphatization-induced electron sink center.

Thiolutin, a selective NLRP3 inflammasome inhibitor, attenuates cyclophosphamide-induced impairment of sperm and fertility in mice.

OBJECTIVE: The activation of the NLRP3 inflammasome has been implicated in male infertility. Our study aimed to investigate the therapeutic role of Thiolutin (THL), an inhibitor of the NLRP3 inflammasome, on oligoasthenospermia (OA) and to elucidate its mechanisms. MATERIALS AND METHODS: Semen from 50 OA and 20 healthy males were analyzed to assess the sperm quality and levels of inflammatory markers. Their correlation was determined using Pearson's correlation coefficient. The BALB/c mice were intraperitoneal injected by cyclophosphamide at 60 mg/kg/day for five days to induce OA, followed by a two-week treatment with THL or L-carnitine. Reproductive organ size and H&E staining were determined to observe the organ and seminiferous tubule morphology. ELISA and western blotting were utilized to measure sex hormone levels, inflammatory markers, and NLRP3 inflammasome levels. Furthermore, male and female mice were co-housed to observe pregnancy success rates. RESULTS: OA patients exhibited a decrease in sperm density and motility compared to healthy individuals, along with elevated levels of IL-1ß, IL-18 and NLRP3 inflammasome. In vivo, THL ameliorated OA-induced atrophy of reproductive organs, hormonal imbalance, and improved sperm density, motility, spermatogenesis and pregnancy success rates with negligible adverse effects on weight or liver-kidney function. THL also demonstrated to be able to inhibit the activation of NLRP3 inflammasome and associated proteins in OA mice. DISCUSSION: THL can improve sperm quality and hormonal balance in OA mice through the inhibition of NLRP3 inflammasome activation. Thus, THL holds promising potential as a therapeutic agent for OA.

ADAM8 silencing suppresses the migration and invasion of fibroblast-like synoviocytes via FSCN1/MAPK cascade in osteoarthritis.

OBJECTIVE: Osteoarthritis (OA) is a degenerative joint disease that affects elderly populations worldwide, causing pain and disability. Alteration of the fibroblast-like synoviocytes (FLSs) phenotype leads to an imbalance in the synovial inflammatory microenvironment, which accelerates the progression of OA. Despite this knowledge, the specific molecular mechanisms of the synovium that affect OA are still unclear. METHODS: Both in vitro and in vivo experiments were undertaken to explore the role of ADAM8 playing in the synovial inflammatory of OA. A small interfering RNA (siRNA) was targeting ADAM8 to intervene. High-throughput sequencing was also used. RESULTS: Our sequencing analysis revealed significant upregulation of the MAPK signaling cascade and ADAM8 gene expression in IL-1ß-induced FLSs. The in vitro results demonstrated that ADAM8 blockade inhibited the invasion and migration of IL-1ß-induced FLSs, while also suppressing the expression of related matrix metallomatrix proteinases (MMPs). Furthermore, our study revealed that inhibiting ADAM8 weakened the inflammatory protein secretion and MAPK signaling networks in FLSs. Mechanically, it revealed that inhibiting ADAM8 had a significant effect on the expression of migration-related signaling proteins, specifically FSCN1. When siADAM8 was combined with BDP-13176, a FSCN1 inhibitor, the migration and invasion of FLSs was further inhibited. These results suggest that FSCN1 is a crucial downstream factor of ADAM8 in regulating the biological phenotypes of FLSs. The in vivo experiments demonstrated that ADAM8 inhibition effectively reduced synoviocytes inflammation and alleviated the progression of OA in rats. CONCLUSIONS: ADAM8 could be a promising therapeutic target for treating OA by targeting synovial inflammation.