To investigate the activity of Ras-related C3 botulinum toxin substrate 1(Rac1) in the lumbar facet joint osteoarthritis(FJOA). Fifty-five lumbar facet joint samples were collected from clinical patients, and they were divided into three groups according to Weishaup classification. Hematoxylin-eosin staining, Safranin O/Fast green staining, and the OARSI scoring system were used to assess the severity of cartilage degeneration. The activity of Rac1 was detected by pull-down assay.A rat lumbar FJOA model was constructed using sodium iodoacetate. Immunohistochemical staining was used to detect the expression of COL2 and MMP13 in rat cartilage tissue. SW1353 cells were stimulated with IL-1β to construct a model of chondrocyte apoptosis.The expression of COL2,MMP13, NF-κB signaling pathway proteins and apoptosis proteins were detected by western blotting. Immunofluorescence was used to detect the expression changes and co-localization of Rac1, COL2, and MMP13.NSC23766 was used to inhibit the activation of Rac1. TUNEL assay was used to detect the effect of chondrocyte apoptosis. The activity of Rac1 was increased in the cartilage tissue of the lumbar facet joint in osteoarthritis.IL-1β induced an increase of Rac1 activity in SW1353 cells, and promoted chondrocyte apoptosis through the NF-κB signaling pathway.NSC23766 inhibited the increase of Rac1 activity induced by IL-1β, and reduced chondrocyte apoptosis by inhibiting the NF-ΚB signaling pathway. The activity of Rac1 is increased in the cartilage tissue of lumbar FJOA, and the increase of activity of Rac1 induced by IL-1β can participates in the apoptosis of chondrocytes through the NF-κB signaling pathway.

ObjectiveTo investigate the relationship between bone metabolism markers, bone mineral density (BMD), clinical characteristics, and the occurrence of secondary fractures after percutaneous vertebroplasty (PVP) or percutaneous kyphoplasty (PKP) in patients with osteoporotic thoracolumbar fractures (OTF).MethodsA retrospective study was conducted on 107 OTF patients treated in our hospital from May 2023 to May 2024. Patients were divided into secondary fracture and non-fracture groups. Standard univariate analysis, Pearson correlation, collinearity diagnostics, and multivariate logistic regression were performed to identify independent risk factors. A predictive nomogram was constructed and internally validated via bootstrap resampling.ResultsSignificant differences were observed between the fracture and non-fracture groups regarding age, number of operated vertebrae, incidence of cement leakage, levels of type I collagen amino-terminal propeptide (PINP), levels of 25-hydroxyvitamin D (25(OH)D), and BMD (all P < 0.05). Pearson correlation analysis confirmed that all these indicators were strongly correlated with secondary fracture occurrence. Multivariate logistic regression confirmed all six variables as independent risk factors. The nomogram constructed from these factors demonstrated excellent discriminative performance, with an area under the curve (AUC) value of 0.975. The calibration curve indicated no significant difference between predicted and actual probabilities, demonstrating high predictive value.ConclusionAge, number of operated vertebrae, cement leakage, PINP, 25(OH)D, and BMD are closely associated with and are independent risk factors for secondary fractures after PVP/PKP in OTF patients. The nomogram model based on these factors has high value. Screening high-risk populations using these indicators provides crucial theoretical guidance for the clinical prevention and treatment of secondary fractures.

BackgroundDifferentiating acute from chronic wedge-shaped thoracolumbar vertebral deformities on conventional lateral lumbar radiographs remains clinically challenging, especially when osteoporosis status also needs to be considered. This study aimed to develop and evaluate a You Only Look Once (YOLO)v8n framework for vertebral-level detection and classification of thoracolumbar fractures with osteoporosis-related stratification on lateral lumbar radiographs.MethodsWe retrospectively collected 1352 lateral lumbar radiographs from 1352 patients, with one radiograph per patient. A total of 1774 vertebral fracture segments were manually annotated. Lumbar magnetic resonance imaging (MRI) and dual-energy X-ray absorptiometry (DXA) were used as reference standards to stratify vertebral targets into three categories: acute fracture with osteoporosis, acute fracture without osteoporosis and chronic fracture with osteoporosis. The dataset was divided into training and validation subsets at the patient level. A YOLOv8n detector was trained as the primary model. To strengthen methodological rigor, additional baseline comparison experiments were conducted under the same patient-level training/validation split using YOLOv5n and Faster R-CNN. Detection performance was assessed using precision, recall, F1-score, mean average precision (mAP) 50 and mAP50-95.ResultsOn the validation set, the YOLOv8n model achieved a precision of 0.495, recall of 0.482, F1-score of 0.490, mAP50 of 0.506, and mAP50-95 of 0.397. In comparative experiments, YOLOv5n achieved a precision of 0.451, recall of 0.549, F1-score of 0.495, mAP50 of 0.494, and mAP50-95 of 0.367, whereas Faster R-CNN achieved a precision of 0.273, recall of 0.814, F1-score of 0.409, mAP50 of 0.300, and mAP50-95 of 0.217. These findings indicate that YOLOv8n provided the most balanced overall detection performance in the present dataset.ConclusionThe proposed YOLOv8n framework demonstrated preliminary feasibility for automated vertebral-level detection and classification of thoracolumbar fractures with osteoporosis-related stratification on lateral lumbar radiographs. However, given the moderate overall performance and lack of external validation, the current model should be regarded as an assistive screening tool rather than a standalone diagnostic system.

Spinal cord injury (SCI) is a prevalent form of spinal cord dysfunction, and the discovery of new effective treatments remains a critical research focus. This study investigated the role of paeoniflorin in a lipopolysaccharide (LPS)-induced PC-12 cell model of SCI and examined the involvement of phosphatase and tensin homolog (PTEN) and the phosphoinositide 3-kinase/protein kinase B (PI3K/AKT) signaling pathway. Rat neuronal PC-12 cells were injured using LPS. Cell viability, proliferation, and apoptosis were assessed using the Cell Counting Kit-8, 5-ethynyl-2′-deoxyuridine (EdU), and Terminal deoxynucleotidyl transferase dUTP Nick End Labeling (TUNEL) assays, respectively. Western blotting and quantitative polymerase chain reaction were used to analyze PI3K, AKT, and PTEN expressions. PTEN was overexpressed to determine its functional role. LPS significantly reduced cell viability and proliferation, while increasing apoptosis. Paeoniflorin treatment ameliorated these injury markers in a dose-dependent manner, downregulated PTEN expression, and enhanced phosphorylated PI3K and AKT levels. PTEN overexpression counteracted the protective effects of paeoniflorin and its activation of PI3K/AKT signaling. Paeoniflorin alleviates LPS-induced cell injury in PC-12 cell model by inhibiting PTEN expression and subsequently activating the PI3K/AKT pathway.

To evaluate the efficacy of an Internet-based Cognitive Behavioral Therapy (ICBT) program in improving kinesiophobia, exercise adherence, pain intensity, lumbar function, and spinal alignment parameters in patients following lumbar surgery. In this two-arm randomized controlled trial conducted at a tertiary hospital rehabilitation center, 90 adult patients (aged 18–55 years) who underwent single-level posterior lumbar fusion for lumbar disc herniation were randomly assigned to ICBT (n = 45) or control (n = 45) groups. The ICBT group received a 6-month digital rehabilitation program combining cognitive behavioral therapy and core muscle training, while controls received conventional postoperative care. Primary outcomes were kinesiophobia (measured by Tampa Scale of Kinesiophobia), exercise adherence (assessed using Orthopedic Patient Exercise Adherence Scale), and pain intensity (evaluated by Numerical Rating Scale). Secondary outcomes included lumbar function (measured by Japanese Orthopaedic Association scores) and spinal stability parameters (trunk deviation, pelvic torsion, and vertebral rotation angles). Outcomes were assessed at baseline, 1 week, 1 month, 3 months, and 6 months post-intervention. The ICBT group demonstrated significantly lower TSK scores at 1, 3, and 6 months post-intervention (30.31 ± 3.27, 25.38 ± 2.40, and 22.09 ± 2.04 vs. 39.56 ± 2.89, 36.40 ± 3.04, and 30.29 ± 2.90, respectively; all P < 0.05). Exercise compliance was progressively higher in the ICBT group at 1, 3, and 6 months (57.84 ± 3.37, 65.16 ± 3.51, and 66.33 ± 3.33 vs. 51.16 ± 5.40, 53.60 ± 4.40, and 50.33 ± 3.57, respectively; all P < 0.001). Pain scores showed greater reduction in the ICBT group from 1 month onwards (median 2.00, 1.00, and 0.00 vs. 3.00, 2.00, and 1.00 at 1, 3, and 6 months, respectively; all P < 0.01). The ICBT group also demonstrated superior outcomes in JOA scores (27.36 ± 1.75 vs. 23.09 ± 2.11, P < 0.001) and spinal stability parameters (all P < 0.001) at both 3 and 6 months post-intervention. Internet-based cognitive behavioral therapy combined with core muscle training effectively reduced pain intensity, improved functional recovery, and enhanced spinal stability in patients following lumbar fusion surgery. This digital intervention offers a promising approach for post-surgical rehabilitation management. The trial was registered in the ClinicalTrials.gov with the registration number: NCT07030582, (Date: 17/05/2025).

Neuroinflammation and oxidative stress are pivotal drivers of neurological dysfunction following spinal cord injury (SCI). Consequently, precise modulation of pathological glial cells and amelioration of the neuronal microenvironment represent a promising therapeutic strategy. Herein, we developed an injectable, self-healing hydrogel system composed of oxidized sodium alginate, carboxymethyl chitosan, and tannic acid (OCT) for the sustained co-delivery of a Quercetin-Manganese complex (QM) and astrocyte-derived extracellular vesicles encapsulating siRNA (AEVs@siRNA). RNA sequencing revealed significant enrichment of the TNF and chemokine signaling pathways in SCI mice, with a notable upregulation of Serpina3n. This gene, predominantly expressed in astrocytes, modulates their reactive polarization. Leveraging the innate tropism of astrocyte-derived extracellular vesicles, we achieved targeted delivery of Serpina3n-targeting siRNA to astrocytes at the lesion site. This approach effectively suppressed the expression of Serpina3n, inhibiting the transition to a neurotoxic A1 phenotype and alleviating neuronal damage. Concurrently, the sustained release of QM NPs potently scavenged reactive oxygen species, significantly mitigating neuronal ferroptosis. Further mechanistic investigations demonstrated that this combinatorial system attenuated neuroinflammation by inhibiting NF-κB p65 signaling to reduce A1 astrocyte activation, and protected neurons by regulating the SLC7A11/GPX4 axis to counteract apoptosis and ferroptosis, both in vitro and in vivo. Consequently, this targeted delivery system represents a promising approach for enhancing therapeutic efficacy and promoting neural repair following SCI.

Background:Traumatic cervical spinal cord injury (TCSCI) often leads to significant patient paralysis. Current clinical diagnosis relies heavily on empirical interpretation of magnetic resonance imaging (MRI) and the American Spinal Injury Association Impairment Scale (AIS) grade, lacking robust quantitative markers to precisely reflect injury severity. This study aimed to build an artificial intelligence (AI) pipeline for AIS grade prediction based on radiomic features extracted from manually defined regions. Methods:We included 189 patients with TCSCI who underwent MRI within 48 h post-injury. MRI images from 130 patients were used for developing an AI model encompassing image segmentation. Radiomic features were extracted from manually delineated volumes of interest (VOIs). T2-weighted imaging (T2WI) sagittal images were randomly divided into training (n = 104), validation (n = 13), and test (n = 13) sets for segmentation. A total of 183 patients (excluding AIS E) were included in the AIS grade prediction task. Model performance was evaluated using mean dice similarity coefficient (mDICE), mean intersection over union (mIOU), mean specificity, and mean sensitivity. Results:An optimized UCTransnet network, leveraging a Transformer architecture for formal training, combined with a U-Net++ network for pretraining, achieved promising results in segmenting the spinal cord injury site on T2WI sagittal images (mDICE: 0.777 ± 0.021, mIOU: 0.646 ± 0.025, mean specificity: 0.998 ± 0.001, mean sensitivity: 0.895 ± 0.015). Subsequently, an ensemble model (we named Em-En) constructed using selected radiomic features from the manual VOIs demonstrated superior performance for predicting AIS grades in terms of sensitivity, specificity, accuracy, and clinical decision-making benefit compared to other tested models. Conclusions:This study presents an AI-assisted pipeline for predicting the severity of TCSCI. The developed resources provide a theoretical foundation for the clinical application of AI-assisted diagnostic methods, potentially lowering the interpretation barrier for MRI and offering clinicians preliminary quantitative indicators of injury severity. The source code is publicly available.

Introduction:Inflammatory signaling-induced stem cell dysfunction severely impairs bone regeneration. This study aimed to develop a combinatorial strategy using Ti3C2Tx MXene scaffolds and PSAT1-engineered dental pulp stem cells (oe-PSAT1 DPSCs) to counteract inflammation-mediated osteogenic suppression. Methods:Dental pulp stem cells (DPSCs) were treated with TNF-α to simulate an inflammatory microenvironment. miR-665 expression and its targeting relationship with PSAT1 were analyzed via qRT-PCR, dual-luciferase reporter assay, and Western blot. The role of the miR-665/PSAT1/GSK-3β/β-catenin axis in osteogenic differentiation was evaluated using ALP activity, alizarin red staining, and immunofluorescence. Ti3C2Tx MXene was synthesized and characterized, and its effects on ROS scavenging and osteogenesis were assessed in vitro. In vivo efficacy was validated using a rat calvarial defect model with micro-CT, histological staining, and immunohistochemistry. Results:TNF-α stimulation upregulated miR-665, which directly targeted PSAT1 and inhibited the GSK-3β/β-catenin pathway, suppressing DPSCs osteogenic differentiation. PSAT1 overexpression rescued this suppression. Ti3C2Tx MXene scavenged ROS, enhanced calcium-dependent mineralization, and synergized with oe-PSAT1 DPSCs to amplify β-catenin activation. In rat models, the Ti3C2Tx MXene /oe-PSAT1 DPSCs combination achieved superior bone defect closure (higher BV/TV, Tb. Th, and mature collagen deposition) compared to Ti3C2Tx MXene alone. Discussion:This study identifies the miR-665/PSAT1/GSK-3β/β-catenin axis as a key regulator of inflammatory osteogenesis. The Ti3C2Tx MXene/oe-PSAT1 DPSCs strategy concurrently neutralizes oxidative stress and activates osteogenic signaling, providing a translatable platform for inflammatory bone regeneration.

Background Abnormal expression of Zinc finger (ZNF) genes is commonly observed in osteosarcoma (OS), the most prevalent malignant bone tumor in children and teenagers. This project focused on the role of ZNF560 in the progress of OS. Methods The published datasets including TCGA-SARC and GSE99671 was utilized to screen out the abnormal expression of ZNF560 and associated gene patterns in sarcoma and OS tissues. Prognosis value of ZNF560 was identified in TCGA-SARC and OS cohorts. In order to manipulate ZNF560 expression in HOS and MG63 osteosarcoma (OS) cells, genetic strategies such as shRNA constructs were utilized. The expression patterns of ZNF560 were analyzed through techniques such as immunohistochemistry, Western blotting, and qRT-PCR. Results By analyzing data from both the GEO and the Cancer Genome Atlas (TCGA) databases, increased expression of ZNF560 in OS tissues was verified, which was significantly associated with poorer outcomes in osteosarcoma patients both in TCGA-SARC and our own OS cohorts. Additionally, downregulation of ZNF560 resulted in decreased cell viability, fewer colonies, and induced apoptosis of osteosarcoma cells. Moreover, ZNF560 was found to be essential for migration of human osteosarcoma HOS and MG63 cells. Conclusion Collectively, these findings suggest that ZNF560 has the potential to serve as a predictive biomarker for osteosarcoma.

Background: Spinal cord injury (SCI) constitutes a profoundly debilitating neurological disorder precipitating motor and sensory function impairment. Curtailing microglia-driven neuroinflammation alongside oxidative stress proves indispensable for efficacious SCI patient management. Poliumoside (POL), a phenylethanoid glycoside molecule, manifests anti-inflammatory, antioxidant, and neuroprotective capacities. Nevertheless, documentation concerning its SCI therapeutic efficacy remains sparse. Methods: Systemic drug toxicity for two POL dosages (15 mg/kg, 30 mg/kg) was evaluated across multiple organs. An SCI murine model was generated employing Allen’s technique. Mice received random assignment into sham, SCI, and SCI+POL cohorts. Intraperitoneal POL administration ensued for 7 consecutive days post-trauma. Histological staining probed tissue and cellular alterations. Functional recuperation was assessed via the Basso Mouse Scale (BMS), hindlimb flexion scoring, and footprint examination. RNA sequencing (RNA-seq) explored POL’s therapeutic impact within SCI. Immunofluorescence detected the axonal marker neurofilament 200 (NF200), myelin marker myelin basic protein (MBP), and the glial scar indicators ionized calcium-binding adapter molecule 1 and glial fibrillary acidic protein (IBA1, GFAP); Western blot (WB) identified the nerve growth-associated protein 43 (GAP43). WB and immunofluorescence quantified inflammatory and oxidative stress markers. POL’s regulatory function within the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mechanistic target of rapamycin (mTOR) cascade was scrutinized both in vivo and in vitro. Results: POL intervention induced no systemic organ toxicity. POL-treated mice exhibited pronounced locomotor function enhancement, diminished neuronal tissue depletion, elevated neuronal survival, and attenuated demyelination. RNA-seq analysis illuminated POL’s SCI therapeutic mechanism linkage to axonal regeneration, the phosphatidylinositol signaling apparatus, and the neuronal framework. POL concurrently attenuated glial scar formation and potentiated axonal and myelin regeneration. Mechanistically, POL suppressed pro-inflammatory cytokines and oxidative stress mediators while activating the PI3K/AKT/mTOR pathway. Conclusions: POL mitigated murine spinal cord injury-induced neuroinflammation and oxidative stress through PI3K/AKT/mTOR signaling pathway activation. Furthermore, POL treatment contracted the glial scar expanse within the injury epicenter and fostered axonal regeneration coupled with myelin regeneration. Consequently, POL enhances post-SCI motor function and accelerates neural function restoration.

The formation of foamy cells (FMMs) by excessive engulfment of myelin debris (MD) causes secondary neuroinflammation and chronic neuropathies after traumatic spinal cord injury (SCI). It is unclear what the function and mechanism of retinoid X receptor (RXR) α are in FMMs-induced neuroinflammation and neural improvement post SCI. The present study aims to investigate the effects and underlying mechanisms of RXRα activation on FMMs and SCI mice. We established an in vitro FMMs model by MD stimulation and an in vivo SCI model in mice. Using an agonist 2, 4-Di-tert-butylphenol (2, 4-DTBP), we activated RXRα and examined the inflammation levels by PCR, WB, and Immunofluorescence (IF), then detected lipid accumulation by BODIPY and Oil red O staining, and determined secondary neuropathies using IF and histological staining. The locomotor function recovery was assessed using motor evoked potential (MEP), Basso Mouse Scale (BMS), as well as footprint assay. Activation of RXRα by 2, 4-DTBP reduced the expression of interleukin (IL)-6, IL-1β, and tumor necrosis factor (TNF)-α and the levels of inflammatory mediators iNOS and COX-2. Besides, treatment with 2, 4-DTBP increased the expression of cholesterol efflux channels including Abca1, Abcg1, Apoe, and caused a marked decrease in intracellular cholesterol and lipid accumulation. Blocking the RXRα-induced cholesterol efflux caused an increase in cholesterol and FMMs, reversing the prior decrease, and exacerbated the degree of neuroinflammation. Also, administration of 2, 4-DTBP improved the neuropathies and locomotor function recovery after SCI.Taken together, activation of RXRα decreased the formation of FMMs by promoting cholesterol efflux and inhibited neuroinflammation by inhibition of p38 and NF-κB signaling after SCI. It is a promising target for mitigating FMMs-induced neuroinflammation and locomotor dysfunction.

Activating transcription factor 3 (ATF3) may function as a regulator of various diseases; however, its role in spinal cord injury (SCI) remains unknown. We designed a current work to evaluate the potentials of the ATF3/forkhead box protein A2 (FOXA2) axis in SCI. GSE45006 chip was analyzed, and a volcano plot and heatmap were drawn. Gene Ontology and KEGG analysis were performed for the differentially expressed genes. Animals with SCI were established. Quantitative reverse transcription polymerase chain reaction and western blotting were used to determine mRNA expression, and western blotting was used for detecting protein expression. The interaction between FOXA2 and the ATF3 promoter was evaluated using the UCSC database and confirmed using dual-luciferase and chromatin immunoprecipitation assays. Cellular behaviors were determined using CCK-8, EdU, and TUNEL assays. Levels of p-PI3K, PI3K, p-AKT, and AKT were examined by the WB method. We found that ATF3 expression was markedly increased in rats with SCI. Interestingly, ATF3 knockdown increased the proliferation and suppressed the apoptotic ability of PC12 cells. FOXA2 activates ATF3 transcription. Knockdown of FOXA2-mediated down-regulation of ATF3 increases growth and decreases PC12 cell death. ATF3 knockdown could increase the level of p-PI3K and p-AKT; FOXA2 shRNA could affect the expression of p-PI3K and p-AKT, which was partially abrogated by ATF3 OE. Forkhead box protein regulates the transcription of ATF3, thereby affecting cell growth and PC12 cell death.

ObjectiveThe aim of this study is to develop and validate a prediction model for fall risk factors in hospitalized older adults with osteoporosis.MethodsA total of 615 older adults with osteoporosis hospitalized at a tertiary (grade 3A) hospital in Nantong City, Jiangsu Province, China, between September 2022 and August 2023 were selected for the study using convenience sampling. Fall risk factors were identified using univariate and logistic regression analyses, and a predictive risk model was constructed and visualized through a nomogram. Model performance was evaluated using the area under the receiver operator characteristic curve (AUC), Hosmer-Lemeshow goodness-of-fit test, and clinical decision curve analysis, assessing the discrimination ability, calibration, and clinical utility of the model.ResultsBased on logistic regression analysis, we identified several significant fall risk factors for older adults with osteoporosis: gender of the study participant, bone mineral density, serum calcium levels, history of falls, fear of falling, use of walking aids, and impaired balance. The AUC was 0.798 (95% CI: 0.763–0.830), with a sensitivity of 80.6%, a specificity of 67.9%, a maximum Youden index of 0.485, and a critical threshold of 121.97 points. The Hosmer-Lemeshow test yielded a χ2 value of 8.147 and p = 0.419, indicating good model calibration. Internal validation showed a C-index of 0.799 (95% CI: 0.768–0.801), indicating the model’s high discrimination ability. Calibration curves showed good agreement between predicted and observed values, confirming good calibration. The clinical decision curve analysis further supported the model’s clinical utility.ConclusionThe prediction model constructed and verified in this study was to predict fall risk for hospitalized older adults with osteoporosis, providing a valuable tool for clinicians to implement targeted interventions for patients with high fall risks.

OBJECTIVES:Facet joint osteoarthritis (FJOA) is a degenerative spinal joint condition causing low back pain due to cartilage loss and joint damage. Although some studies have highlighted the importance of pyroptosis or autophagy in cartilage loss under FJOA, no report has identified the biomarkers between the two biological events. This direction demonstrates innovative potential and scientific value. The present study aimed to screen differentially expressed genes (DEGs) linked to pyroptosis and autophagy in FJOA and identify potential biomarkers for FJOA. METHODS:We collected the lumbar facet joints, performed transcriptome sequencing, used a variety of bioinformatics methods to obtain differentially expressed genes (DEGs), and obtained autophagy-related and pyroplosis-related genes (APRGs) from GeneCards database, and then screened out 17 APRGs. Two machine learning methods were used to identify potential biomarkers. Subsequently, clinical sample experiments and cellular experiments were carried out to validate. RESULTS:We found 7,783 DEGs in samples of FJOA patients and obtained 1,153 autophagy-related genes and 80 pyroptosis-related genes from the GeneCards database. 17 APRGs were screened out from the intersection of the three gene sets. Furthermore, CD274, DDX3X, Caspase-8, and MAPK14 were identified as FJOA characteristic biomarkers. We identified that DDX3X, Caspase-8, and MAPK14 were positively correlated with pyroptosis and autophagy in clinical samples and cell experiments, while CD274 was negatively correlated. CONCLUSIONS:Our study identified CD274, DDX3X, Caspase-8, and MAPK14 in chondrocyte and articular cartilage of articular process with pyroptosis and autophagy in FJOA. Therefore, the four genes are expected to be promising therapeutic targets for FJOA, our findings may provide novel insight in clinic.

This study aimed to develop and evaluate the effectiveness of a perioperative blood management plan based on the problem, intervention, control, and outcomes (PICO) model for long-segment lumbar spine posterior surgery. In this retrospective study, 51 patients who needed long-segment posterior lumbar spine surgery at the Second Affiliated Hospital of Nantong University Department of Spinal Surgery from July 2020 to June 2022 were included in the control group, while 51 patients who needed long-segment posterior lumbar spine surgery from July 2021 to June 2022 were selected as the observation group. Patients in the control group received conventional blood management, while those in the observation group were additionally administered an evidence-based perioperative blood management plan. We compared the intervention outcomes in both the groups. Patients in the observation group demonstrated significantly higher postoperative hemoglobin levels and hematocrit at various time points compared to those in the control group (P < 0.05). Intraoperative blood loss, postoperative drainage volume, and average volume of allogeneic blood transfused per recipient, as well as the number and frequency of allogeneic blood transfusions, were significantly lower in the observation group (P < 0.05). The duration of surgical drain placement and postoperative hospital stay were notably shorter in the observation group (P < 0.05). The two groups did not differ significantly in the incidence of postoperative venous thromboembolism (VTE) (P > 0.05). The implementation of a perioperative blood management plan was effective in reducing the total blood loss and transfusion volume in the perioperative period, improving hemoglobin and hematocrit levels, facilitating earlier removal of surgical drains, and accelerating patient discharge.

Background: Spinal cord injury (SCI)-induced mitochondrial dysfunction in microglia exacerbates neuroinflammation and neurological deficits. Monoammonium glycyrrhizinate (MAG), a bioactive liquorice-derived compound, exhibits anti-inflammatory and antioxidant properties; however, its effects on microglial mitochondria remain unknown.Methods: Mice received a moderate contusion injury at the T10 spinal segment. Histopathology was assessed using Hematoxylin-Eosin, Nissl staining, and Luxol Fast Blue; locomotor recovery was evaluated via the Basso Mouse Scale, hindlimb flexion scoring, and gait footprint analysis. RNA-Seq and molecular docking identified KEAP1/NRF2 signaling. Verification employed qPCR, Western blot, and immunofluorescence. Mitochondrial function was gauged by JC-1 and MitoSOX.Results: In SCI mice, MAG attenuated neuroinflammation, reduced neuronal tissue loss and demyelination, enhanced neuronal survival, and improved functional recovery. Transcriptomic and molecular docking established that MAG directly activates NRF2, promoting dissociation from KEAP1, nuclear translocation, and induction of NQO1. Pathway enrichment analysis further indicated MAG modulation of mitochondrial regulatory processes. MAG treatment significantly restored mitochondrial function in BV2 cells, improving membrane potential and reducing oxidative stress. Critically, NRF2 inhibition with ML385 abolished MAG's protective effects on anti-inflammatory responses and antioxidant activity.Conclusion: This study identifies MAG as a novel activator of the KEAP1/NRF2/NQO1 axis, alleviating microglial mitochondrial dysfunction and neuroinflammation post-SCI. These findings provide mechanistic insights into MAG's neuroprotective actions and support its therapeutic potential.

Rationale: Necroptosis in astrocytes induced by mitochondrial dysfunction following spinal cord injury (SCI) significantly contributes to neuronal functional deficits. Mitophagy plays a crucial role in clearing damaged mitochondria and inhibiting necroptosis. Fanconi anemia complementation group C (FANCC), a member of the Fanconi anemia gene family, exerts a protective role by facilitating mitophagy in immune processes. However, the role of FANCC in SCI-induced astrocytic necroptosis and the underlying mechanisms remain unexplored. Methods: Astrocyte-specific FANCC conditional knockout (Fanccfl/fl-GFAP-Cre) mice, obtained by mating Fanccfl/fl mice with GFAP-Cre mice, served as a model of moderate thoracic spinal cord contusion injuries. Using bulk and single-nucleus RNA sequencing, we investigated the protective role of FANCC in astrocytes after SCI. We assessed necroptosis and mitophagy in astrocytes through quantitative PCR, western blotting, flow cytometry, immunofluorescence, and transmission electron microscopy. Molecular mechanisms were explored via co-immunoprecipitation, proteomics, molecular docking, and confocal imaging. Computer virtual screening identified poliumoside as a FANCC activator. Histopathological staining and functional assessments (gait analysis, Basso Mouse Scale, and hindlimb reflex score) were conducted to evaluate the therapeutic effects of poliumoside on SCI. Results: Astrocytic FANCC deficiency exacerbated necroptosis and mitochondrial damage, leading to severe neurological deficits. Conversely, FANCC overexpression increased PTEN-induced kinase 1-Parkin expression, thereby activating mitophagy and reducing necroptosis. Proteomics revealed FANCC's interaction with a specific peptide of TANK-binding kinase 1 (TBK1), which further promoted mitophagy. Treatment with the FANCC activator poliumoside improved neural pathology and motor function recovery in SCI mice. Conclusion: The current study indicated that FANCC interacts with TBK1 and consequently mediates Parkin translocation, activates mitophagy, and inhibits astrocyte necroptosis. Our findings demonstrate the neuroprotective role and therapeutic potential of FANCC for SCI amelioration.

Objectives:Laminoplasty (LAMP) is a common procedure for multilevel cervical spondylotic myelopathy (MCSM). The traditional K-line is a guide for LAMP candidate selection but is inferior to the modified K-line (mK-line) in predicting clinical outcomes. The spinal cord line (SC-line) is another indicator that considers anterior compression but is not typically used for selecting surgical segments. This study intended to propose and validate the combined application of modified spinal cord line (mSC-line) with mK-line for surgical decision-making in MCSM patients. Methods:This study included 63 MCSM patients categorized into K-line(-) group and K-line(+) group, or Type I group and Type II group based on SC-line. We defined mK-line and mSC-line in sagittal T2WI MRIs. All patients with both mK-line(+) and mSC-line(+) underwent standard LAMP. Radiographic analysis was conducted using CCI, mK-INT and mSC-INT. Clinical outcomes were evaluated by JOA, NDI and VAS scores. Preoperative and postoperative radiological outcomes and clinical outcomes were used to evaluate the prognosis and the efficacy of segmental decision-making. Results:There were no difference in baseline characteristics among all the participants. Post-operative spinal cord shift indicators (mK-INT and mSC-INT) increased significantly. The JOA score increased, while NDI and VAS scores decreased. Both the radiological outcomes and clinical outcomes demonstrated a good prognosis even in K-line(-) group and Type II group. There was a statistical correlation between JOA score recovery rate with both mK-INT and mSC-INT. Conclusions:The presence of mK-line(+) and mSC-line(+) in MRI is crucial for the selection of surgical segments in LAMP for MCSM patients. This combined criterion can help predict sufficient decompression of the cervical spinal cord and good clinical outcomes.

Purpose Develop machine learning models utilizing computed tomography (CT) and the weishaupt grading criteria to assess the degeneration severity of facet joint of osteoarthritis (FJOA). Methods The machine learning model utilizes features extracted from patient Lumbar CT at the First People's Hospital of Nantong. Use 3D Slicer software to perform semi-automatic image segmentation on CT images and extract radiological features from the segmented regions. Preliminary screening of radiomic features extracted by radiomics using t-test and rank sum test with p<0.05 as the standard. Based on the core features selected by Lasso regression, construct random forest (RF), K-nearest neighbor (KNN), and support vector machine (SVM) models. Use receiver operating characteristic (ROC) curves to evaluate the model's performance, considering metrics such as accuracy, recall, precision, F1 score, and area under curve (AUC). Results The radiomics package of 3D Slicer extracted 1037 radiomic features from ROI. The T-test combined with rank sum test preliminarily screened 589 radiomics features with statistical differences. Subsequently, Lasso regression was used to identify 28 core features. Develop machine learning models based on 28 core feature selections of RF, SVM, and KNN. The AUCs of RF model, SVM model and KNN model in the training set were 0.783, 0.803 and 0.693 respectively, and those in the validation set were 0.699, 0.719 and 0.671 respectively. Conclusion The machine learning model utilizing lumbar CT images can effectively assess lumbar facet joint degeneration. Through this model, diseases can be classified and diagnosed, and doctors can develop personalized treatment plans.