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The biofilm-induced "relatively immune-compromised zone" creates an immunosuppressive microenvironment that is a significant contributor to refractory infections in orthopedic endophytes. Consequently, the manipulation of immune cells to co-inhibit or co-activate signaling represents a crucial strategy for the management of biofilm. This study reports the incorporation of Mn2+ into mesoporous dopamine nanoparticles (Mnp) containing the stimulator of interferon genes (STING) pathway activator cGAMP (Mncp), and outer wrapping by M1-like macrophage cell membrane (m-Mncp). The cell membrane enhances the material's targeting ability for biofilm, allowing it to accumulate locally at the infectious focus. Furthermore, m-Mncp mechanically disrupts the biofilm through photothermal therapy and induces antigen exposure through photodynamic therapy-generated reactive oxygen species (ROS). Importantly, the modulation of immunosuppression and immune activation results in the augmentation of antigen-presenting cells (APCs) and the commencement of antigen presentation, thereby inducing biofilm-specific humoral immunity and memory responses. Additionally, this approach effectively suppresses the activation of myeloid-derived suppressor cells (MDSCs) while simultaneously boosting the activity of T cells. Our study showcases the efficacy of utilizing m-Mncp immunotherapy in conjunction with photothermal and photodynamic therapy to effectively mitigate residual and recurrent infections following the extraction of infected implants. As such, this research presents a viable alternative to traditional antibiotic treatments for biofilm that are challenging to manage.
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Unsupervised representation learning (URL) is still lack of a reasonable operator (e.g. convolution kernel) for exploring meaningful structural information from generic data including vector, image and tabular data. In this paper, we propose a simple end-to-end T-distributed Stochastic Neighbor Network (TsNet) for URL with clustering downstream task. Concretely, our TsNet model has three major components: (1) an adaptive connectivity distribution learning module is presented to construct a pairwise graph for preserving the local structure of generic data; (2) a T-distributed stochastic neighbor embedding based loss function is designed to learn a transformation between embeddings and original data, which improves the discrimination of representations; (3) a nonlinear parametric mapping is learned via our TsNet on an unsupervised generalized manner, which can address the "out-of-sample" issue. By combining these components, our method is able to considerably outperform previous related unsupervised learning approaches on visualization and clustering of generic data. A simple deep neural network equipped on our model respectively achieves 74.90%, 76.56% ACC and NMI, which is 8% relative improvement over previous state-of-the-art on real single-cell RNA-sequencing (scRNA-seq) datasets clustering.
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Lactiplantibacillus paraplantarum P3 (L. paraplantarum P3) cell-free supernatant (CFS) with good antifungal effect was sprayed on fresh in-shell peanuts stored at 5 °C and 30 °C to explore its effect on the microorganisms and quality of fresh in-shell peanuts during storage process. Results showed that L. paraplantarum P3 CFS effectively maintained good quality of fresh in-shell peanuts by not only reducing fungi amount and the mildew rate, but also improving the morphology, color and flavor. Besides, L. paraplantarum P3 CFS activated plant mitogen-activated protein kinase signaling pathway and plant hormone signaling pathway to produce more ethylene, gibberellin regulatory proteins and other substances to enhance plant resistance to pathogenic microorganisms. L. paraplantarum P3 CFS could also induce the biosynthesis of glycerophospholipid and arginine to increase the stress resistance of fresh peanuts. This study provides research data for the application of L. paraplantarum P3 CFS in the preservation and antimildew of fresh in-shell peanuts.
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Arachis , Arachis/microbiologia , Armazenamento de Alimentos , Doenças das Plantas/microbiologia , Doenças das Plantas/prevenção & controle , Conservação de Alimentos/métodos , Fungos/efeitos dos fármacos , Fungos/metabolismo , Microbiologia de AlimentosRESUMO
BACKGROUND: Duane retraction syndrome (DRS) is known to relate to the absence of the abducens nucleus, with abnormal innervation of the lateral rectus (LR) muscle by branchesof the oculomotor nerve (CN III). The purposes of this study were to investigate the morphological characteristics of the oculomotor nerve (CN III), the abducens nerve (CN VI), and the extraocular muscles in patients with clinically diagnosed Duane retraction syndrome (DRS) using MRI. In addition, we assessed the association between ocular motility, horizontal rectus muscle volumes, and CN III/VI in patients with Duane retraction syndrome (DRS). METHODS: The study comprised 20 orthotropic control subjects (40 eyes) and 42 patients with Duane syndrome (48 eyes), including 20 patients with DRS Type I (24 eyes), 5 patients with DRS Type II (6 eyes), and 17 patients with DRS Type III (18 eyes). Three-dimensional (3D) T1/2 images of the brainstem and orbit were obtained to visualize the cranial nerves, especially the abducens (VI) and oculomotor (III) nerves, as well as extraocular muscles. RESULTS: Based on the clinical classification, among 42 patients, MRI showed that the abducens nerves (CN VI) on the affected side were absent in 24 of 24 eyes (100%; 20 patients) with Type I DRS and in 16 of 18 eyes (88%; 16 patients) with Type III DRS. However, CN VI was observed in 6 of 6 eyes (100%; 5 patients) with Type II DRS and in 2 of 18 eyes (11%) with Type III DRS. CN III was observed in all patients. The oculomotor nerves on the affected side were thicker than those on the nonaffected contralateral side in DRS Type I ( P < 0.05) and Type III ( P < 0.05), but not in DRS Type II. Smaller LR and larger MR volumes were shown in the affected eye than that in the nonaffected eye in DRS Types I and III. Based on the presence or absence of CN VI, there was a tendency for thicker oculomotor nerves in the affected eye than in the nonaffected eye in the absence groups ( P < 0.05). However, no significant difference was found in the present group. In the CN VI absence groups, similar results were found in the affected eyes than in the nonaffected eyes as in DRS Types I and III. In addition, the presence of CN VI was correlated with better abduction ( P = 0.008). The LR and MR volumes have positive correlations with the oculomotor nerve diameter in the affected eye. However, there was no correlation between the range of adduction/abduction and the LR/MR ratio in patients with or without an abducens nerve. CONCLUSIONS: Different types of DRS have different characteristic appearances of CN VI and CN III on MRI. Horizontal rectus muscles have morphological changes to adapt to dysinnervation of CN VI and aberrant innervation of CN III. Thus, these neuroimaging findings may provide a new diagnostic criterion for the classification of DRS, improving the comprehension of the physiopathogenics of this disease.
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Síndrome da Retração Ocular , Humanos , Síndrome da Retração Ocular/diagnóstico , Síndrome da Retração Ocular/patologia , Nervo Abducente/diagnóstico por imagem , Músculos Oculomotores/diagnóstico por imagem , Músculos Oculomotores/inervação , Órbita/patologia , Imageamento por Ressonância Magnética/métodosRESUMO
Internet of Medical Things (IoMT) enabled by artificial intelligence (AI) technologies can facilitate automatic diagnosis and management of chronic diseases (e.g., intestinal parasitic infection) based on two-dimensional (2D) microscopic images. To improve the model performance of object detection challenged by microscopic image characteristics (e.g., focus failure, motion blur, and whether zoomed or not), we propose Coupled Composite Backbone Network (C2BNet) to execute the parasitic egg detection task using 2D microscopic images. In particular, the C2BNet backbone adopts a two-path structure-based backbone and leverages model heterogeneity to learn object features from different perspectives. A novel feature composition style is proposed to flow the feature within the coupled composite backbone, and ensure mutual enhancement of feature representation ability among the different paths of the backbone. To further improve the accuracy of the detection results, we propose Multiscale Weighted Box Fusion (WBF) to fuse the location and confidence scores of all bounding boxes predicted from the multiscale feature maps, and iteratively refine the box coordinates to form the final prediction. Experimental results on Chula-ParasiteEgg-11 dataset demonstrate that the C2BNet not only performs satisfactorily compared with state-of-the-art methods, but also can focus more on learning detailed morphology features and abundant semantic features, resulting in more precise detection for parasitic eggs located in the 2D microscopic image.
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Introduction: Lignocellulose is one of the major components of particulate organic matter in sewage, which has a significant influence on biological wastewater treatment process. However, the effect of lignocellulose on aerobic granular sludge (AGS) system is still unknown. Methods: In this study, two reactors were operated over 5 months to investigate the effect of lignocellulose on granulation process, structure stability and pollutants removal of AGS. Results and discussion: The results indicated that lignocellulose not only promoted the secretion of tightly bound polysaccharide in extracellular polymeric substances, but also acted as skeletons within granules, thereby facilitating AGS formation, and enhancing structural strength. Lignocellulose imposed little effect on the removal efficiency of pollutants, with more than 95, 99, and 92% of COD, NH4+-N, and PO43--P were removed in both reactors. However, it did exhibit a noticeable influence on pollutants conversion processes. This might be due to that the presence of lignocellulose promoted the enrichment of functional microorganisms, including Candidatus_Accumulibacter, Candidatus_Competibacter, Nitrosomonas, and Nitrospira, etc. These findings might provide valuable insights into the control strategy of lignocellulose in practical AGS systems.
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The Boom syndrome helicase (BLM) unwinds a variety of DNA structures such as Guanine (G)-quadruplex. Here we reveal a role of RNF111/Arkadia and its paralog ARKL1, as well as Promyelocytic Leukemia Nuclear Bodies (PML NBs), in the regulation of ubiquitination and control of BLM protein levels. RNF111 exhibits a non-canonical SUMO targeted E3 ligase (STUBL) activity targeting BLM ubiquitination in PML NBs. ARKL1 promotes RNF111 localization to PML NBs through SUMO-interacting motif (SIM) interaction with SUMOylated RNF111, which is regulated by casein kinase 2 (CK2) phosphorylation of ARKL1 at a serine residue near the ARKL1 SIM domain. Upregulated BLM in ARKL1 or RNF111-deficient cells leads to a decrease of G-quadruplex levels in the nucleus. These results demonstrate that a CK2- and RNF111-ARKL1-dependent regulation of BLM in PML NBs plays a critical role in controlling BLM protein levels for the regulation of G-quadruplex.
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Caseína Quinase II , Corpos Nucleares da Leucemia Promielocítica , Proteína da Leucemia Promielocítica , RecQ Helicases , Humanos , Caseína Quinase II/genética , Caseína Quinase II/metabolismo , Proteína da Leucemia Promielocítica/genética , Proteína da Leucemia Promielocítica/metabolismo , RecQ Helicases/metabolismo , Ubiquitinação , Sumoilação , Proteína SUMO-1RESUMO
Lignocellulosic biomass (LCB) is the promising feedstock for value-added products, which would contribute to the bioeconomy and sustainable development. The efficient pretreatment is still required in the biorefinery of LCB. To make a simultaneous utilization of carbohydrates and lignin, a novel easy-recycled ethylenediamine (EDA) pretreatment was designed and evaluated in the present study. The results highlighted that this pretreatment yielded 96% glucose and 70% xylose in enzymatic hydrolysis. It simultaneously promoted the depolymerization of lignin into small molecules and functionalized the yielded lignin with Schiff base and amide structures. These animated-lignins showed a pH-responsive behavior and the excellent flocculation capacity by reducing more than 90% turbidity of kaolin suspensions. Therefore, easy-recycled EDA pretreatment hold the promise to simultaneously enhance the enzymatic hydrolysis of carbohydrates and endowed the new functionality of lignin toward downstream valorization, which improved the process feasibility and potentially enable the sustainability of LCB utilization.
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Carboidratos , Lignina , Lignina/química , Hidrólise , Glucose/química , Biomassa , EtilenodiaminasRESUMO
The solidification/stabilisation behaviours of Zn2+ in magnesium potassium phosphate cement (MKPC) have not been thoroughly investigated. Herein, a series of experiments and a detailed density functional theory (DFT) study were conducted to investigate the solidification/stabilisation behaviours of Zn2+ in MKPC. The results showed that the compressive strength of MKPC reduced with the addition of Zn2+ because the formation of MgKPO4·6H2O (the main hydration product in MKPC) was delayed with the addition of Zn2+, as discovered by the crystal characteristics, and because Zn2+ exhibited a lower binding energy in MgKPO4·6H2O compared to Mg2+, as revealed by DFT results. Additonally, Zn2+ had little influence on the structure of MgKPO4·6H2O, and Zn2+ existed in MKPC as the formation of Zn2(OH)PO4, which was decomposed in the range of around 190-350 °C. Moreover, there were a lot of well-crystallised tabular hydration products before the addition of Zn2+, but the matrix was comprised of irregular prism crystals after adding Zn2+. Furthermore, the leaching toxicity of Zn2+ of MKPC was much smaller than the requirements of Chinese and European standards.
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Magnésio , Metais Pesados , Potássio , Metais Pesados/química , Teoria da Densidade Funcional , ZincoRESUMO
Background: The effective analysis methods for steady-state visual evoked potential (SSVEP) signals are critical in supporting an early diagnosis of glaucoma. Most efforts focused on adopting existing techniques to the SSVEPs-based brain-computer interface (BCI) task rather than proposing new ones specifically suited to the domain. Method: Given that electroencephalogram (EEG) signals possess temporal, regional, and synchronous characteristics of brain activity, we proposed a transformer-based EEG analysis model known as EEGformer to capture the EEG characteristics in a unified manner. We adopted a one-dimensional convolution neural network (1DCNN) to automatically extract EEG-channel-wise features. The output was fed into the EEGformer, which is sequentially constructed using three components: regional, synchronous, and temporal transformers. In addition to using a large benchmark database (BETA) toward SSVEP-BCI application to validate model performance, we compared the EEGformer to current state-of-the-art deep learning models using two EEG datasets, which are obtained from our previous study: SJTU emotion EEG dataset (SEED) and a depressive EEG database (DepEEG). Results: The experimental results show that the EEGformer achieves the best classification performance across the three EEG datasets, indicating that the rationality of our model architecture and learning EEG characteristics in a unified manner can improve model classification performance. Conclusion: EEGformer generalizes well to different EEG datasets, demonstrating our approach can be potentially suitable for providing accurate brain activity classification and being used in different application scenarios, such as SSVEP-based early glaucoma diagnosis, emotion recognition and depression discrimination.
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Nuclear proteins are major constituents and key regulators of nucleome topological organization and manipulators of nuclear events. To decipher the global connectivity of nuclear proteins and the hierarchically organized modules of their interactions, we conducted two rounds of cross-linking mass spectrometry (XL-MS) analysis, one of which followed a quantitative double chemical cross-linking mass spectrometry (in vivoqXL-MS) workflow, and identified 24,140 unique crosslinks in total from the nuclei of soybean seedlings. This in vivo quantitative interactomics enabled the identification of 5340 crosslinks that can be converted into 1297 nuclear protein-protein interactions (PPIs), 1220 (94%) of which were non-confirmative (or novel) nuclear PPIs compared with those in repositories. There were 250 and 26 novel interactors of histones and the nucleolar box C/D small nucleolar ribonucleoprotein complex, respectively. Modulomic analysis of orthologous Arabidopsis PPIs produced 27 and 24 master nuclear PPI modules (NPIMs) that contain the condensate-forming protein(s) and the intrinsically disordered region-containing proteins, respectively. These NPIMs successfully captured previously reported nuclear protein complexes and nuclear bodies in the nucleus. Surprisingly, these NPIMs were hierarchically assorted into four higher-order communities in a nucleomic graph, including genome and nucleolus communities. This combinatorial pipeline of 4C quantitative interactomics and PPI network modularization revealed 17 ethylene-specific module variants that participate in a broad range of nuclear events. The pipeline was able to capture both nuclear protein complexes and nuclear bodies, construct the topological architectures of PPI modules and module variants in the nucleome, and probably map the protein compositions of biomolecular condensates.
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Arabidopsis , Núcleo Celular , Arabidopsis/genética , Arabidopsis/metabolismo , Espectrometria de Massas , Proteínas Nucleares/metabolismoRESUMO
Background: Kimura's disease (KD) is a rare, chronic inflammatory disease. Clinically, subcutaneous nodules of the head and neck are typical manifestations, often accompanied by local lymphadenopathy or salivary gland enlargement, but there is also systemic damage, such as kidney involvement. Due to the lack of specific markers and imaging examination is not specific, it is difficult to clinically diagnose accurately and can be easy to misdiagnose. The treatment of KD is still not standardized and overtreatment can affect the quality of life. Case Presentation: The case of a 26-year-old man complaining of chest pain with self-conscious progressive lymphadenopathy after receiving Pfizer BioNTech COVID-19 vaccine for more than 1 month is presented. Eosinophil levels were normal and IgE elevated and the final diagnosis of KD was eventually confirmed by lymph node biopsy, which revealed lymphadenopathy with extensive eosinophilic infiltration in the right neck. Treatment was prednisone combined with methotrexate, resulting in satisfactory control. Conclusion: This case demonstrates that that Kimura disease can involve systemic lymphadenopathy, not only in the head and face or regional lymphadenopathy, suggested that KD should be excluded in patients with systemic lymphadenopathy. The current patient's response to treatment suggested that corticosteroid combined with disease-modifying antirheumatic drugs (DENARDs) was a promising treatment for KD patients with systemic damage. It is worth noting that the mechanism of immunity in the pathogenesis of KD still needs to be further studied.
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Background: Automated diagnosis of various retinal diseases based on fundus images can serve as an important clinical decision aid for curing vision loss. However, developing such an automated diagnostic solution is challenged by the characteristics of lesion area in 2D fundus images, such as morphology irregularity, imaging angle, and insufficient data. Methods: To overcome those challenges, we propose a novel deep learning model named MyopiaDETR to detect the lesion area of normal myopia (NM), high myopia (HM) and pathological myopia (PM) using 2D fundus images provided by the iChallenge-PM dataset. To solve the challenge of morphology irregularity, we present a novel attentional FPN architecture and generate multi-scale feature maps to a traditional Detection Transformer (DETR) for detecting irregular lesion more accurate. Then, we choose the DETR structure to view the lesion from the perspective of set prediction and capture better global information. Several data augmentation methods are used on the iChallenge-PM dataset to solve the challenge of insufficient data. Results: The experimental results demonstrate that our model achieves excellent localization and classification performance on the iChallenge-PM dataset, reaching AP50 of 86.32%. Conclusion: Our model is effective to detect lesion areas in 2D fundus images. The model not only achieves a significant improvement in capturing small objects, but also a significant improvement in convergence speed during training.
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This research developed a novel, efficient and safe antimildew for peanut kernel postharvest storage. The antimildew, cinnamon-Litsea cubeba compound essential oil (CLCEO) microcapsule (CLCEOM), was synthesized with CLCEO as core materials and ß-cyclodextrin as wall materials. Fourier transform infrared spectroscopy and gas chromatography-mass spectrometry analyses indicated that major antifungal compounds of CLCEO were encapsulated in the cavity of ß-cyclodextrin. The inhibition zone experiment showed that CLCEOM retained antifungal effect on Aspergillus spp. strains even after storage for 2 months at 4 â. Besides, CLCEOM reduced total number of fungal colonies, relative abundance of Aspergillus spp., and aflatoxin B1 content of peanut kernels, and had positive effect on slowing down the increase in acid value of peanut oil without causing any adverse effect on the viability and sensory properties during storage process. Overall, CLCEOM presented good preservative effects on peanut kernels, providing evidence for its potential use as antimildew for peanut storage.
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Litsea , Óleos Voláteis , Óleos Voláteis/química , Arachis , Litsea/química , Cinnamomum zeylanicum , Antifúngicos/farmacologia , Cápsulas , AspergillusRESUMO
Heparin is a commonly used anticoagulant in clinical practice; however, excessive heparin can cause serious adverse reactions. Convenient and accurate detection of heparin levels is thus very important. In this research, a pyrene-based self-assembling fluorescent peptide PyFFRRR was designed for simple, selective, and efficient heparin detection. The guanidine groups in the arginine residues of PyFFRRR bind tightly with heparin, which is highly sulfated, through electrostatic interactions. Charge neutralization facilitated the self-assembly of PyFFRRR, resulting in its spectral response changing from deep blue monomer fluorescence to green excimer fluorescence. PyFFRRR exhibited excellent sensitivity and selectivity for ratiometric detection of heparin. The binding mechanism was investigated by using spectral and simulation tools, and structural observation. Finally, PyFFRRR was employed in human serum samples for ratiometric detection of heparin.
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Corantes Fluorescentes , Heparina , Humanos , Heparina/química , Corantes Fluorescentes/química , Peptídeos/química , Anticoagulantes , Espectrometria de Fluorescência/métodos , Pirenos/químicaRESUMO
Hydroxyapatite (HAp) as natural bone composition is highly osteoinductive. To harvest its osteoinductivity in bone regenerative engineering, the HAp-supporting hydrogel is urgently needed to minimize inhomogeneous aggregation of HAp. Here, we developed a HAp-stabilizing hydrogel based on peptide self-assembly. FmocFFRR was efficient for HAp-capping due to arginine-phosphate interaction. Tethering FmocFFRR on the HAp surface facilitated self-assembly to form FmocFFRR/HAp hybrid hydrogel, enabling stable dispersion of HAp in it. The molecular interactions between FmocFFRR and HAp particles were studied using microscopic and spectral characterizations. FmocFFRR/HAp hydrogel exhibited more enhanced mechanical properties than FmocFFRR. The biocompatibility of FmocFFRR/HAp hydrogel was verified using an ATP assay and live-dead staining assay. More importantly, FmocFFRR/HAp hydrogel not only enabled cell attachment on its surface, but also supported 3D cell culturing inside the hydrogel. Further, 3D culturing of MC3T3-E1 preosteoblasts inside FmocFFRR/HAp hydrogel significantly enhanced the expressions of osteogenesis markers, including alkaline phosphate (ALP), type-I collagen (COL1), and osteocalcin (OCN), demonstrating the promoting effect of osteoblast differentiation. These findings inspire its potential application in bone regenerative engineering.
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Solid developments have been seen in deep-learning-based pose estimation, but few works have explored performance in dense crowds, such as a classroom scene; furthermore, no specific knowledge is considered in the design of image augmentation for pose estimation. A masked autoencoder was shown to have a non-negligible capability in image reconstruction, where the masking mechanism that randomly drops patches forces the model to build unknown pixels from known pixels. Inspired by this self-supervised learning method, where the restoration of the feature loss induced by the mask is consistent with tackling the occlusion problem in classroom scenarios, we discovered that the transfer performance of the pre-trained weights could be used as a model-based augmentation to overcome the intractable occlusion in classroom pose estimation. In this study, we proposed a top-down pose estimation method that utilized the natural reconstruction capability of missing information of the MAE as an effective occluded image augmentation in a pose estimation task. The difference with the original MAE was that instead of using a 75% random mask ratio, we regarded the keypoint distribution probabilistic heatmap as a reference for masking, which we named Pose Mask. To test the performance of our method in heavily occluded classroom scenes, we collected a new dataset for pose estimation in classroom scenes named Class Pose and conducted many experiments, the results of which showed promising performance.
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BACKGROUND: lncRNA, a type of non-coding RNA, plays an important role in the osteogenic differentiation of bone marrow-derived mesenchymal stem cells (BM-MSCs). In this study, lncRNA and mRNA microarrays were performed to study the change of gene expression during osteogenic differentiation of BM-MSCs. We focused on Hedgehog interacting protein (HHIP), because HHIP mRNA and lncRNA HHIP-AS1 were gradually down-regulated on days 0, 7, and 14 during osteogenic differentiation. In addition, the gene coding lncRNA HHIP-AS1 is located on the anti-sense of Hhip gene, implying the potential interaction between lncRNA HHIP-AS1 and HHIP mRNA. METHODS: BM-MSCs with over-expressed or silenced lncRNA HHIP-AS1 were constructed to explore the biological role of HHIP-AS1 in osteogenic differentiation. BM-MSCs were lysed to determine the alkaline phosphatase activity. Fluorescence in situ hybridization and immunofluorescence were performed to analyze HHIP-AS1, HHIP, RUNX2 and osteocalcin. RESULTS: Overexpression of lncRNA HHIP-AS1 increased HHIP expression, which suppressed Hedgehog signaling pathway, as indicated by the reduction of SMO, Gli1 and Gli2. The suppression of Hedgehog signal was associated with the inhibited osteogenesis. HHIP knockdown abolished the suppression of osteogenesis induced by lncRNA HHIP-AS1 overexpression. Through binding to HHIP mRNA, lncRNA HHIP-AS1 recruited ELAVL1 to HHIP mRNA, whereby increasing the mRNA stability and the protein level. CONCLUSIONS: This study revealed that down-regulation of HHIP due to lncRNA HHIP-AS1 reduction promoted the osteogenic differentiation of BM-MSCs though removing the suppression of Hedgehog signal.
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Células-Tronco Mesenquimais , RNA Longo não Codificante , Proteínas Hedgehog/genética , Osteogênese/genética , RNA Longo não Codificante/genética , Hibridização in Situ Fluorescente , Diferenciação Celular/genética , RNA Mensageiro , Transdução de Sinais/genética , Células CultivadasRESUMO
Background context: Low back pain, affecting nearly 40% of adults, mainly results from intervertebral disc degeneration (IVDD), while the pathogenesis of IVDD is still not fully elucidated. Recently, some researches have revealed that necroptosis, a programmed necrosis, participated in the progression of IVDD, nevertheless, the underlying mechanism remains unclear. Purpose: To study the mechanism of necroptosis of Nucleus Pulposus (NP) cells in IVDD, focusing on the role of MyD88 signaling. Study design: The expression and co-localization of necroptotic indicators and MyD88 were examined in vivo, and MyD88 inhibitor was applied to determine the role of MyD88 signaling in necroptosis of NP cells in vitro. Methods: Human disc specimens were collected from patients receiving diskectomy for lumbar disc herniation (LDH) or traumatic lumbar fractures after MRI scanning. According to the Pfirrmann grades, they were divided into normal (Grades 1, 2) and degenerated groups (4, 5). Tissue slides were prepared for immunofluorescence to assess the co-localization of necroptotic indicators (RIP3, MLKL, p-MLKL) and MyD88 histologically. The combination of TNFα, LPS and Z-VAD-FMK was applied to induce necroptosis of NP cells. Level of ATP, reactive oxygen species (ROS), live-cell staining and electron microscope study were employed to study the role of MyD88 signaling in necroptosis of NP cells. Results: In vivo, the increased expression and co-localization of necroptotic indicators (RIP3, MLKL, p-MLKL) and MyD88 were found in NP cells of degenerated disc, while very l low fluorescence intensity in tissue of traumatic lumbar fractures. In vitro, the MyD88 inhibitor effectively rescued the necroptosis of NP cells, accompanied by increased viability, ATP level, and decreased ROS level. The effect of MyD88 inhibition on necroptosis of NP cells was further confirmed by ultrastructure of mitochondria shown by Transmission Electron Microscope (TEM). Conclusion: Our results indicated that the involvement of MyD88 signaling in the necroptosis of NP cells in IVDD, which will replenish the pathogenesis of IVDD and provide a novel potential therapeutic target for IVDD.