GMS-YOLO: An Algorithm for Multi-Scale Object Detection in Complex Environments in Confined Compartments.

Many compartments are prone to pose safety hazards such as loose fasteners or object intrusion due to their confined space, making manual inspection challenging. To address the challenges of complex inspection environments, diverse target categories, and variable scales in confined compartments, this paper proposes a novel GMS-YOLO network, based on the improved YOLOv8 framework. In addition to the lightweight design, this network accurately detects targets by leveraging more precise high-level and low-level feature representations obtained from GhostHGNetv2, which enhances feature-extraction capabilities. To handle the issue of complex environments, the backbone employs GhostHGNetv2 to capture more accurate high-level and low-level feature representations, facilitating better distinction between background and targets. In addition, this network significantly reduces both network parameter size and computational complexity. To address the issue of varying target scales, the first layer of the feature fusion module introduces Multi-Scale Convolutional Attention (MSCA) to capture multi-scale contextual information and guide the feature fusion process. A new lightweight detection head, Shared Convolutional Detection Head (SCDH), is designed to enable the model to achieve higher accuracy while being lighter. To evaluate the performance of this algorithm, a dataset for object detection in this scenario was constructed. The experiment results indicate that compared to the original model, the parameter number of the improved model decreased by 37.8%, the GFLOPs decreased by 27.7%, and the average accuracy increased from 82.7% to 85.0%. This validates the accuracy and applicability of the proposed GMS-YOLO network.

Drugs Associated with Urinary Retention Adverse Reactions: A Joint Analysis of FDA Adverse Event Reporting System and Mendelian Randomization.

OBJECTIVE: To explore the association between drugs and urinary retention using the FDA Adverse Event Reporting System (FAERs) database and Mendelian randomization (MR) analysis, providing preliminary insights into the underlying mechanisms. METHODS: Drug-adverse reaction reports from the FAERs database from 2004 to 2023 were obtained, and MR analysis was conducted to further validate the causal relationship between drugs and urinary retention using genetic data provided by the IEU OpenGWAS project. RESULTS: We identified 78 drugs associated with urinary retention, including Mirabegron, Tiotropium, Quetiapine, Amlodipine, etc. MR analysis indicated genetic markers (SNPs rs10500326, rs4815689, and rs1216743) of Amlodipine were associated with an increased risk of urinary retention. Sensitivity analysis demonstrated the robustness and reliability of the results. CONCLUSION: This study identified various drugs associated with urinary retention, particularly Amlodipine. This finding provides new clues for further investigation into the mechanisms of drug effects on bladder function and offers important references for clinical practice. However, further randomized controlled trials are needed to validate these associations and explore deeper mechanisms.

Landscape of the Lumbar Cartilaginous End Plate Microbiota and Metabolites in Patients with Modic Changes.

BACKGROUND: Modic changes (MCs), vertebral end plate and bone marrow damage observed by magnetic resonance imaging, are an independent risk factor for low back pain. The compositions of and interaction between microbiota and metabolites in the lumbar cartilaginous end plates (LCEPs) of patients with MCs have not been identified. METHODS: Patients with lumbar disc degeneration who were undergoing lumbar spinal fusion surgery were recruited between April 2020 and April 2021. LCEPs were collected for 16S rRNA sequencing and liquid chromatography-mass spectrometry (LC/MS)-based targeted metabolomic profiling. Of the 54 patients recruited, 24 had no MCs and 30 had changes classified as Modic type 2 or 3. The primary goal was to identify specific genera of microbiota associated with MCs, and secondary goals included investigating differences in metabolites between patients with and without MCs and exploring the correlation between these metabolites and microorganisms. RESULTS: Investigation of the microbiota community structure revealed that both alpha diversity and beta diversity were significantly different between patients with and without MCs, and the abundances of 26 genera were significantly different between these 2 groups. Metabolomic analysis revealed that 26 metabolites were significantly different between the 2 groups. The unsaturated fatty acid pathway was found to be the main pathway related to MCs. Multiomic correlation analysis suggested that Caulobacteraceae (unclassified) and Mycobacterium, Clostridium, Blautia, and Bifidobacterium at the genus level were linked to dysregulation of fatty acid metabolism, contributing to the pathogenesis of MCs. CONCLUSIONS: Our study represents a foundational effort to examine the landscape of the microbiota and metabolites in patients with MCs, informing future studies on the pathogenesis of and targeted therapy for MCs. LEVEL OF EVIDENCE: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Similar experimental study on diffusion and distribution of diesel exhaust in confined space of a coal mine.

In the confined space of the underground coal mine, which is dominated by transportation lanes, explosion-proof diesel-powered trackless rubber-wheeled vehicles are becoming the main transportation equipment, and the exhaust gas produced by them is hazardous to the health of workers and pollutes the underground environment. In this experiment, a similar test platform is built to study the effects of wind speed, vehicle speed, and different wind directions on the diffusion characteristics of exhaust gas. In this paper, CO and SO2 are mainly studied. The results show that the diffusion of CO and SO2 gas is similar and the maximum SO2 concentration only accounts for 11.4% of the CO concentration. Exhaust gas is better diluted by increasing the wind speed and vehicle speed, respectively. Downwind is affected by the reverse wind flow and diffuses to the driver's position, which is easy to cause occupational diseases. When the wind is a headwind, the exhaust gases spread upwards and make a circumvention movement, gathering at the top. When the wind speed and vehicle speed are both 0.6 m/s, the CO concentration corresponds to the change trend of the Lorentz function when the wind is downwind and the CO concentration corresponds to the change trend of the BiDoseResp function when the wind is headwind. The study of exhaust gas diffusion characteristics is of great significance for the subsequent purification of the air in the restricted mine space and the protection of the workers' occupational health.

ß-blockades and the risk of atrial fibrillation in patients with cardiovascular diseases.

Background: ß-blockers have been widely used in patients with extensive cardiovascular disease (CVD) and have provided benefits. However, they are more likely to cause symptomatic bradycardia, hypotension, or glucose metabolism disorders, which may lead to an increased risk of atrial fibrillation (AF), but evidence is lacking. Aims: This study was to analyze the association between the use of ß-blockers and the risk of developing AF. Methods: This nationwide, prospective cohort study utilized data from the 2013-2020 National Health and Nutrition Examination Survey (NHANES). The patients were stratified into a ß-blocker treatment group (n = 2585) and a non-ß-blocker treatment group (n = 8525). Univariate and multivariate logistic regression analyses were performed to identify the relationship between ß-blockades and the risk of AF. Propensity matching analysis was used to balance patient baseline characteristics and to control for confounders. Results: A total of 11,110 subjects were included in this study (mean [SD] age, 59.89 [15.07] years; 5657 [49.7%] males). A total of 111/2585 subjects developed AF in the ß-blocker treatment group, and 75/8525 developed AF in the non-ß-blocker treatment group (incidence rate, 4.2% vs. 0.8%). Compared with the non-ß-blocker group, the ß-blocker group had an increased risk of incident AF (aOR, 2.339; 95% CI, 1.614-3.410). Some sensitivity analyses also revealed consistent findings of increased AF risk associated with ß-blocker treatment. Conclusion: The findings from this study suggest that ß-blocker treatment is associated with an increased risk of incident AF and may help physicians select a modest medication for patients while also assessing the risk of AF.

Corrigendum to "Establishment and verification of the first prognostic nomograms in locally advanced thyroid cancer based on the analysis of clinical and follow-up information on 2396 patients" [Heliyon 10(3), January 2024, e24798].

[This corrects the article DOI: 10.1016/j.heliyon.2024.e24798.].

Nursing observations of stage-based care in patients diagnosed with hepatitis B virus infection based on TBIL and ALT levels.

This study explored techniques and effects of stage-based care on patients with chronic hepatitis B virus (HBV) infection. The clinical data of 156 patients with chronic HBV infection treated in our hospital from September 2018 to December 2019 were retrospectively analyzed and classified as the experimental group (EG). Patients were categorized into early, intermediate, and late hepatitis stages and received targeted clinical care during the various phases of chronic HBV infection. In addition, 144 cases of patients with chronic HBV admitted to the hospital from January 2018 to August 2018 and treated without stage-based care were classified as the control group (COG). General care was implemented for all patients before the initiation of stage-based care. Patient satisfaction, mortality rates of patients at different stages, liver pain scores, depression scores, blood biochemical indices, and alanine transaminase and total bilirubin levels before and after nursing care were compared. The total satisfaction rate of the EG group (90.38%) was significantly higher than that of the COG group (83.33%) (P < .05). We found no significant differences in the mortality rates of early-, middle-, and late-stage patients in the EG group when compared with those of the COG group at corresponding stages (P < .05). The self-care agency scores (for all dimensions) and psychosocial adaptation scores in the EG group were significantly higher than those in the COG group (P < .05) after care. Moreover, the pain scores in the EG group were significantly lower than those in the COG group after care (P < .05). Furthermore, the observed psychological status of patients in the EG group significantly improved when compared with that in the COG group (P < .05). Stage-based care for patients with severe chronic type B hepatitis increased clinical satisfaction, relieved pain, reduced depression, and improved blood biochemical indices. Therefore, stage-based care for chronic HBV infection should be included in the clinical environment.

Ultrahigh Thermal Conductivity of Epoxy/Ag Flakes/MXene@Ag Composites Achieved by In Situ Sintering of Silver Nanoparticles.

The growing use of high-power and integrated electronic devices has created a need for thermal conductive adhesives (TCAs) with high thermal conductivity (TC) to manage heat dissipation at the interface. However, TCAs are often limited by contact thermal resistance at the interface between materials. In this study, we synthesized MXene@Ag composites through a direct in situ reduction process. The Ag nanoparticles (Ag NPs) generated by the reduction of the MXene interlayer and surface formed effective thermally conductive pathways with Ag flakes within an epoxy resin matrix. Various characterization analyses revealed that adding MXene@Ag composites at a concentration of 3 wt % resulted in a remarkable TC of 40.80 W/(m·K). This value is 8.77 times higher than that achieved with Ag flakes and 7.9 times higher than with MXene filler alone. The improved TC is attributed to the sintering of the in situ reduced Ag NPs during the curing process, which formed a connection between MXene (a highly conductive material) and the Ag flakes, thereby reducing contact thermal resistance. This reduction in contact thermal resistance significantly enhanced the TC of the thermal interface materials (TIMs). This study presents a novel approach for developing materials with exceptionally high TC, opening new possibilities for the design and fabrication of advanced thermal management systems.

SnO2QDs sensitized ZnFe2O4spheres with enhanced acetone sensing performance.

Herein, SnO2QDs (<10 nm) with small size instead of conventional nanoparticles was employed to modify ZnFe2O4to synthesize porous and heterogeneous SnO2/ZnFe2O4(ZFSQ) composites for gas sensing. By an immersion process combined with calcination treatment, the resultant porous ZFSQ composites with different contents of SnO2QDs were obtained, and their sensing properties were investigated. Compared with bare ZnFe2O4and SnO2QDs, porous ZFSQ composites based-sensors showed much improved sensor response to acetone. For contrast, the sensor performance of ZFSQ composites was also compared with that of ZnFe2O4sphere modified by SnO2nanoparticles with different size. The porous ZFSQ composite with 5 wt% SnO2QDs (ZFSQ-5) showed a better acetone sensing response than that of other ZFSQ composites, and it exhibited a high response value of 110-100 ppm of acetone and a low detection limit of 0.3 ppm at 240 °C. In addition to the rich heterojunctions and porous structure, the size effect of SnO2QDs was other indispensable reasons for the improved sensor performance. Finally, the ZFSQ-5 composite sensor was attempted to be applied for acetone sensing in exhaled breath, suggesting its great potential in monitoring acetone.

Development and validation of a radiomics-based model for predicting osteoporosis in patients with lumbar compression fractures.

BACKGROUND: Osteoporosis, a metabolic bone disorder, markedly elevates fracture risks, with vertebral compression fractures being predominant. Antiosteoporotic treatments for patients with osteoporotic vertebral compression fractures (OVCF) lessen both the occurrence of subsequent fractures and associated pain. Thus, diagnosing osteoporosis in OVCF patients is vital. PURPOSE: The aim of this study was to develop a predictive radiographic model using T1 sequence MRI images to accurately determine whether patients with lumbar spine compression fractures also have osteoporosis. STUDY DESIGN: Retrospective cohort study. PATIENT SAMPLE: Patients over 45 years of age diagnosed with a fresh lumbar compression fracture. OUTCOME MEASURES: Diagnostic accuracy of the model (area under the ROC curve). METHODS: The study retrospectively collected clinical and imaging data (MRI and DEXA) from hospitalized lumbar compression fracture patients (L1-L4) aged 45 years or older between January 2021 and June 2023. Using the pyradiomics package in Python, features from the lumbar compression fracture vertebral region of interest (ROI) were extracted. Downscaling of the extracted features was performed using the Mann-Whitney U test and the least absolute shrinkage selection operator (LASSO) algorithm. Subsequently, six machine learning models (Naive Bayes, Support Vector Machine [SVM], Decision Tree, Random Forest, Extreme Gradient Boosting [XGBoost], and Light Gradient Boosting Machine [LightGBM]) were employed to train and validate these features in predicting osteoporosis comorbidity in OVCF patients. RESULTS: A total of 128 participants, 79 in the osteoporotic group and 49 in the nonosteoporotic group, met the study's inclusion and exclusion criteria. From the T1 sequence MRI images, 1906 imaging features were extracted in both groups. Utilizing the Mann-Whitney U test, 365 radiologic features were selected out of the initial 1,906. Ultimately, the lasso algorithm identified 14 significant radiological features. These features, incorporated into six conventional machine learning algorithms, demonstrated successful prediction of osteoporosis in the validation set. The NaiveBayes model yielded an area under the receiver operating characteristic curve (AUC) of 0.84, sensitivity of 0.87, specificity of 0.70, and accuracy of 0.81. CONCLUSIONS: A NaiveBayes machine learning algorithm can predict osteoporosis in OVCF patients using t1-sequence MRI images of lumbar compression fractures. This approach aims to obviate the necessity for further osteoporosis assessments, diminish patient exposure to radiation, and bolster the clinical care of patients with OVCF.

Association between the oxidative balance score and thyroid function: Results from the NHANES 2007-2012 and Mendelian randomization study.

BACKGROUND: Oxidative stress is a significant contributor to the development of various diseases, and the oxidative balance score (OBS) is a valuable tool for assessing the impact of dietary and lifestyle factors on oxidative stress in humans. Nevertheless, the precise relationship between OBS and thyroid function in adults remains elusive. METHODS: This cross-sectional study comprised 6222 adult participants drawn from the National Health and Nutrition Examination Survey (NHANES) conducted from 2007 to 2012. Employing weighted multivariable linear regression modeling, the study estimated the connection between OBS quartiles and thyroid functions. The causal relationship between OBS components and thyroid function was analyzed by Mendelian randomization (MR). RESULTS: We found a significant negative correlation between OBS and free thyroxine (FT4) and total thyroxine (TT4). Univariate and multivariate MR Analyses showed a causal relationship between BMI and FT4. Copper, smoking, and riboflavin showed a causal relationship with FT4 after moderation. CONCLUSION: We found that a lifestyle high in antioxidant exposure reduced FT4 and TT4 levels in the population. We suggest that BMI, Copper, and Riboflavin are important factors in the regulation of FT4 levels.

Establishment and verification of the first prognostic nomograms in locally advanced thyroid cancer based on the analysis of clinical and follow-up information on 2396 patients.

Background and objectives: The purpose of this research was to develop and validate the first prognostic nomograms for 3-, 5-, and 10-year cancer-specific survival (CSS) and overall survival (OS) in patients diagnosed with locally advanced thyroid cancer (LATC) by evaluating independent predictors of prognosis in a population of LATC patients. Methods: Demographics, clinicopathologic characteristics, treatment, and follow-up of 2396 LATC patients in the surveillance, epidemiology, and end results database from 2004 to 2015 were retrospectively analyzed and compared with patients with LATC according to staging. We randomized all LATC patients into training and validation groups in a 7:3 ratio. Cox regression analyses helped us to derive independent prognostic factors for LATC patients. According to these results, we established and validated the first prognostic nomograms and risk stratification. Results: In our research, the clinical information of LATC patients was compared and significant differences were found in the relevant variables including CSS and OS (P < 0.05), with CSS of 82.0 % and 49.0 %, and OS of 70.6 % and 40.0 %, respectively. Cox regression analyses showed that age at diagnosis, tumor diameter, presence of DM, extrathyroidal extension sites, histological type, thyroidectomy scope, radiotherapy status, and chronological sequence of radiotherapy and surgery were observably correlated with CSS in LATC patients, and in addition to the above factors, gender, marital status, and chemotherapy status were also observably correlated with OS in LATC patients. The prognostic predictive power of the above factors is visualized by the Kaplan-Meier survival curve. The concordance index of nomograms for CSS and OS were 0.933, 0.925, and 0.926 (CSS), 0.918, 0.909, and 0.906 (OS), respectively, and the time-dependent receiver operating characteristic curve, area under curve, calibration curve and decision curve analysis curve indicate that the nomograms have good discriminatory ability, accuracy and clinical applicability in both the training and validation groups. Conclusions: In these findings, we drawed a conclusion that there were significant differences in clinical information between patients with T4a and T4b LATC, and we established and validated the first prognostic nomograms and risk stratification of CSS and OS for LATC patients at 3, 5, and 10 years, which will help clinicians to individualize their postoperative treatment and individualized follow-up.

Effect of lead-free glass on the current transmission method at the Ag/Si interface in crystalline silicon solar cells.

Environmental protection mandates have spurred the widespread adoption of lead-free glass in electronic material adhesion. Glass powder, crucial for solar silver paste, notably affects the ohmic contact at the Ag-Si interface of crystalline silicon solar cells. This study examines how TeO2 content influences the high-temperature flowability and wettability of lead-free Bi2O3-TeO2-based glass powder, alongside the interplay between the glass's thermal properties and interface contact. Additionally, it investigates the Bi2O3-TeO2 ratio's impact on current transmission through the interfacial glass layer. Experimental results show that the synthesized glass powder exhibits superior high-temperature flowability and wettability, with a low contact resistance of 1.5 mΩ cm2 in silver paste applications. This study also proposes an optimal approach for enhancing current transmission through the interfacial glass layer. Consequently, this glass powder is highly valuable for c-Si solar cell silver paste applications, offering novel insights into improving current transmission efficiency.

Discovery of Artemisinins as Microsomal Prostaglandins Synthase-2 Inhibitors for the Treatment of Colorectal Cancer via Chemoproteomics.

Colorectal cancer remains the second leading cause of cancer-related mortalities worldwide. While artemisinin (ART), a key active compound from the traditional Chinese medicinal herb Artemisia annua, has been recognized for its antiproliferative activity against colon cancer cells, its underlying molecular underpinnings remain elusive. Whereas promiscuity of heme-dependent alkylating of macromolecules, mainly proteins, has been seen pivotal as a universal and primary mode of action of ART in cancer cells, accumulating evidence suggests the existence of unique targets and mechanisms of actions contingent on cell or tissue specificities. Here, we employed photoaffinity probes to identify the specific targets responsible for ART's anti-colon cancer actions. Upon validation, microsomal prostaglandins synthase-2 emerged as a specific and reversible target of ART in HCT116 colorectal cancer cells, whose inhibition resulted in reduced cellular prostaglandin E2 biosynthesis and cell growth. Our discovery opens new opportunities for pharmacological treatment of colon cancer.

Chemoproteomic development of SLC15A4 inhibitors with anti-inflammatory activity.

SLC15A4 is an endolysosome-resident transporter linked with autoinflammation and autoimmunity. Specifically, SLC15A4 is critical for Toll-like receptors (TLRs) 7-9 as well as nucleotide-binding oligomerization domain-containing protein (NOD) signaling in several immune cell subsets. Notably, SLC15A4 is essential for the development of systemic lupus erythematosus in murine models and is associated with autoimmune conditions in humans. Despite its therapeutic potential, the availability of quality chemical probes targeting SLC15A4 functions is limited. In this study, we used an integrated chemical proteomics approach to develop a suite of chemical tools, including first-in-class functional inhibitors, for SLC15A4. We demonstrate that these inhibitors suppress SLC15A4-mediated endolysosomal TLR and NOD functions in a variety of human and mouse immune cells; we provide evidence of their ability to suppress inflammation in vivo and in clinical settings; and we provide insights into their mechanism of action. Our findings establish SLC15A4 as a druggable target for the treatment of autoimmune and autoinflammatory conditions.

Enhanced mapping of small-molecule binding sites in cells.

Photoaffinity probes are routinely utilized to identify proteins that interact with small molecules. However, despite this common usage, resolving the specific sites of these interactions remains a challenge. Here we developed a chemoproteomic workflow to determine precise protein binding sites of photoaffinity probes in cells. Deconvolution of features unique to probe-modified peptides, such as their tendency to produce chimeric spectra, facilitated the development of predictive models to confidently determine labeled sites. This yielded an expansive map of small-molecule binding sites on endogenous proteins and enabled the integration with multiplexed quantitation, increasing the throughput and dimensionality of experiments. Finally, using structural information, we characterized diverse binding sites across the proteome, providing direct evidence of their tractability to small molecules. Together, our findings reveal new knowledge for the analysis of photoaffinity probes and provide a robust method for high-resolution mapping of reversible small-molecule interactions en masse in native systems.

Effect of Silver Powder Microstructure on the Performance of Silver Powder and Front-Side Solar Silver Paste.

Silver powder, as the primary component of solar silver paste, significantly influences various aspects of the paste's performance, including printing, sintering, and conductivity. This study reveals that, beyond the shape and size of the silver powders, their microstructure is a critical factor influencing the performance of both silver powders and silver pastes in solar cell applications. The growth process leads to the formation of either polycrystalline aggregated silver powder or crystal growth silver powder. Analyzing the performance characteristics of these different microstructures provides guidance for selecting silver powders for silver pastes at different sintering temperatures. Polycrystalline aggregated silver powder exhibits higher sintering activity, with a sintering initiation temperature around 450 °C. The resulting silver paste, sintered at 750 °C, demonstrates a low sheet resistance of 2.92 mΩ/sq and high adhesion of 2.13 N. This silver powder is suitable for formulating silver pastes with lower sintering temperatures. The solar cell electrode grid lines have a high aspect ratio of 0.37, showing poor uniformity. However, due to the high sintering activity of the silver powder, the glass layer dissolves and deposits more silver, resulting in excellent conductivity, a low contact resistance of the silver electrode, a low series resistance of the solar cell of 1.23 mΩ, and a high photoelectric conversion efficiency of 23.16%. Crystal growth silver powder exhibits the highest tap density of 5.52 g/cm3. The corresponding silver paste shows improved densification upon sintering, especially at 840 °C, yielding a sheet resistance of 2.56 mΩ/sq and adhesion of 3.05 N. This silver powder is suitable for formulating silver pastes with higher sintering temperatures. The solar cell electrode grid lines are uniform with the highest aspect ratio of 0.40, resulting in a smaller shading area, a high fill factor of 81.59%, and a slightly higher photoelectric conversion efficiency of 23.17% compared to the polycrystalline aggregated silver powder.

Low-dose Lipopolysaccharide Alleviates Spinal Cord Injury-induced Neuronal Inflammation by Inhibiting microRNA-429-mediated Suppression of PI3K/AKT/Nrf2 Signaling.

This study investigated the impact of low-dose lipopolysaccharide (LPS) on spinal cord injury (SCI) and the potential molecular mechanism. Rats were randomly assigned to four groups: Sham, SCI, SCI + LPS, and SCI + LPS + agomir. Allen's weight-drop method was used to establish an in vivo SCI model. The Basso Bcattie Bresnahan rating scale was employed to monitor locomotor function. An in vitro SCI model was constructed by subjecting PC12 cells to oxygen and glucose deprivation/ reoxygenation (OGD/R). Enzyme-linked immunosorbent assay (ELISA) was applied for the determination interleukin (IL)-1ß and IL-6. The dual luciferase reporter assay was used to validate the targeting of microRNA (miR)-429 with PI3K. Immunohistochemical staining was used to assess the expression of PI3K, phosphorylated AKT and Nrf2 proteins. The Nrf2-downstream anti-oxidative stress proteins, OH-1 and NQO1, were detected by western blot assay. MiR-429 expression was detected by fluorescence in situ hybridization and real-time quantitative reverse transcription PCR. In vitro, low-dose LPS decreased miR-429 expression, activated PI3K/AKT/Nrf2, inhibited oxidative stress and inflammation, and attenuated SCI. MiR-429 was found to target and negatively regulate PI3K. Inhibition of miR-429 suppressed low-dose LPS-mediated oxidative stress and inflammation via activation of the PI3K/AKT/Nrf2 pathway. In vivo, miR-429 was detectable in neurons. Inhibition of miR-429 blocked low-dose LPS-mediated oxidative stress and inflammation via activation of the PI3K/AKT/Nrf2 pathway. Overall, low-dose LPS was found to alleviate SCI-induced neuronal oxidative stress and inflammatory response by down-regulating miR-429 to activate the PI3K/AKT/Nrf2 pathway.