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.

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.

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.

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.

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.

Praseodymium-Doped Cr2O3 Prepared by In Situ Pyrolysis of MIL-101(Cr) for Highly Efficient Catalytic Oxidation of 1,2-Dichloroethane.

The development of economical catalysts that exhibit both high activity and durability for chlorinated volatile organic compounds (CVOCs) elimination remains a challenge. The oxidizing and acidic sites play a crucial role in the oxidation process of CVOCs; herein, praseodymium (Pr) was introduced into CrOx catalysts via in situ pyrolysis of MIL-101(Cr). With the decomposition of the ligand, a mixed micro-mesoporous structure was formed within the M-Cr catalyst, thereby reducing the contact resistance between catalyst active sites and the 1,2-dichloroethane molecule. Moreover, the synergistic interaction between chromium and praseodymium facilitates Oß species and acidic sites, significantly enhancing the low-temperature catalytic performance and durability of the M-PrCr catalyst for 1,2-dichloroethane (1,2-DCE) oxidation. The M-30PrCr catalyst possess enhanced active oxygen sites and acid sites, thereby exhibiting the highest catalytic activity and stability. This study may provide a novel and promising strategy for practical applications in the elimination of 1,2-DCE.

Group efficiency based on the termination rule in the multiple-targets visual search task.

In practical visual search fields, observers often encounter errors that result from an unknown number of targets, which may induce reduced accuracy and speed. Our current study addresses the potential enhancement of collaborative search efficiency as a dyad to mitigate such incurred search costs. Utilizing the capacity coefficient, we evaluated search efficiency and explored the interplay of task difficulty and termination rule in collaborative visual search. Our prediction that collaborative benefits increased with elevated task difficulty was not supported in Experiment 1, where participants were tasked with judging the presence of any target. In contrast, Experiment 2 demonstrated that dyads exhibited greater search efficiency during exhaustive searches for multiple targets with elevated task difficulty. Notably, our findings indicated an advantage in dyad searches compared to baseline predictions from individual searches. Our results underscored the significance of task difficulty and termination rules in leveraging human resources for improved collaborative visual search performance.

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.

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.

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.

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.

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.

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.

A novel Bi12O17Cl2/GO/Co3O4 Z-type heterojunction photocatalyst with ZIF-67 derivative modified for highly efficient degradation of antibiotics under visible light.

Levofloxacin (LVX) is difficult to be naturally degraded by microorganisms in water, and its residues in water will pose significant risks to human health and ecological environment. In this study, Bi12O17Cl2 was used as the main body, Bi12O17Cl2/GO/Co3O4 composite photocatalyst was prepared by pyrolysis of zeolitic imidazolate framework-67 (ZIF-67) combined with in-situ precipitation method and used to degrade LVX. A sequence of characterizations shows that addition of Co3O4 and graphene oxide (GO) increases the visible light response range, improves the separation efficiency of photogenerated electrons and holes (e--h+) of photocatalyst, and thus improves the degradation efficiency of LVX. Under the optimal reaction conditions, the LVX degradation rate of Bi12O17Cl2/1.5GO/7.5Co3O4 can reach 91.2 % at 120 min, and its reaction rate constant is the largest (0.0151 min-1), which is 2.17, 13.14 and 1.53 times that of Bi12O17Cl2, Co3O4 and Bi12O17Cl2/7.5Co3O4, respectively, showing better photocatalytic performance. Simultaneously, the recycling stability of Bi12O17Cl2/1.5GO/7.5Co3O4 was also verified. The capture experiments and electron EPR test results showed that superoxide radicals (•O2-) and photogenerated holes (h+) were the primary active substances in the reaction process. Finally, combined with HPLC-MS results, the photocatalytic degradation pathway of LVX was derived. This work will provide a theoretical basis for the design of Metal Organic Frameworks (MOFs)-derivative modified Bi12O17Cl2-based photocatalysts.

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.

What do osteoporosis and osteoarthritis have in common? An integrated study of overlapping differentially expressed genes in bone mesenchymal stem cells of osteoporosis and osteoarthritis.

OBJECTIVE: For identification of aberrantly expressed genes in mesenchymal stem cells of osteoporosis (OP) and osteoarthritis (OA), Gene Expression Omnibus (GEO) datasets were integrated to investigate the intersection point. METHODS: GSE35958 (osteoporosis) and GSE19664 (osteoarthritis) datasets were obtained from GEO database. The abnormally expressed genes were analyzed by GEO2R. Functional enrichment was explored by Metascape database and R software. The String database and Cytoscape software were used to build the protein-protein interaction network and identify hub genes. GSE35957 and GSE116925 were used as verification datasets. Single-cell analysis and pseudotime analysis were undertaken. CTDbase, Network Analyst, HPA database, HERB database and MIRW database were used to research the information, tissue and cell distribution, regulation, interaction and ingredients targeting the hub genes. Additionally, in vitro experiments such as RT-PCR, ALP staining and immunofluorescence were undertaken as verification tests. RESULTS: Ten hub genes were identified in this study. All these genes play an important role in bone or cartilage generation. They have diagnostic values and therapeutic potential for OA and OP. Single-cell analysis visualized the cell distribution and pseudotime distribution of these genes. Some potential therapeutic ingredients of these genes were identified, such as curcumin, wogonin and glycerin. In vitro experiments, RT-PCR results showed that COL9A3 and MMP3 were downregulated and PTH1R was upregulated during osteogenic induction of BMSC. Immunohistochemical results showed the expression trend of MMP3 and COL2A1. CONCLUSION: Ten abnormal hub genes of osteoporosis and osteoarthritis were identified successfully by this study. They were important regulatory genes for healthy bone and cartilage. These genes could be the common connections between osteoporosis and osteoarthritis as well as treatment targets. Further study of the regulatory mechanism and treatment effects of these genes would be valuable. The results of this study could contribute to further research.

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.

Heme oxygenase 1 linked to inactivation of subchondral osteoclasts in osteoarthritis. / è¡€çº¢ç´ åŠ æ°§é ¶1ä¸Žéª¨å ³èŠ‚ç‚Žè½¯éª¨ä¸‹ç ´éª¨ç»†èƒžå¤±æ´»çš„ç›¸å ³ç ”ç©¶.

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.

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.

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.