Brain effect mechanism of lever positioning manipulation on LDH analgesia based on multimodal MRI: a study protocol.

INTRODUCTION: The clinical symptoms of Lumbar Disc Herniation (LDH) can be effectively ameliorated through Lever Positioning Manipulation (LPM), which is closely linked to the brain's pain-regulating mechanisms. Magnetic Resonance Imaging (MRI) offers an objective and visual means to study how the brain orchestrates the characteristics of analgesic effects. From the perspective of multimodal MRI, we applied functional MRI (fMRI) and Magnetic Resonance Spectrum (MRS) techniques to comprehensively evaluate the characteristics of the effects of LPM on the brain region of LDH from the aspects of brain structure, brain function and brain metabolism. This multimodal MRI technique provides a biological basis for the clinical application of LPM in LDH. METHODS AND ANALYSIS: A total of 60 LDH patients and 30 healthy controls, matched by gender, age, and years of education, will be enrolled in this study. The LDH patients will be divided into two groups (Group 1, n = 30; Group 2, n = 30) using a random number table method. Group 1 will receive LPM treatment once every two days, for a total of 12 times over 4 weeks. Group 2 will receive sham LPM treatment during the same period as Group 1. All 30 healthy controls will be divided into Group 3. Multimodal MRI will be performed on Group 1 and Group 2 at three time points (TPs): before LPM (TP1), after one LPM session (TP2), and after a full course of LPM treatment. The healthy controls (Group 3) will not undergo LPM and will be subject to only a single multimodal MRI scan. Participants in both Group 1 and Group 2 will be required to complete clinical questionnaires. These assessments will focus on pain intensity and functional disorders, using the Visual Analog Scale (VAS) and the Japanese Orthopaedic Association (JOA) scoring systems, respectively. DISCUSSION: The purpose of this study is to investigate the multimodal brain response characteristics of LDH patients after treatment with LPM, with the goal of providing a biological basis for clinical applications. TRIAL REGISTRATION NUMBER: https://clinicaltrials.gov/ct2/show/NCT05613179 , identifier: NCT05613179.

Genetically predicted causal effects of gut microbiota on spinal pain: a two-sample Mendelian randomization analysis.

Background: Observational studies have hinted at a correlation between the gut microbiota and spinal pain (SP). However, the impact of the gut microbiota on SP remains inconclusive. Methods: In this study, we employed a two-sample Mendelian randomization (MR) analysis to explore the causal relationship between the gut microbiota and SP, encompassing neck pain (NP), thoracic spine pain (TSP), low back pain (LBP), and back pain (BP). The compiled gut microbiota data originated from a genome-wide association study (GWAS) conducted by the MiBioGen consortium (n = 18,340). Summary data for NP were sourced from the UK Biobank, TSP from the FinnGen Biobank, and LBP from both the UK Biobank and FinnGen Biobank. Summary data for BP were obtained from the UK Biobank. The primary analytical approach for assessing causal relationships was the Inverse Variance Weighted (IVW) method, supplemented by various sensitivity analyses to ensure result robustness. Results: The IVW analysis unveiled 37 bacterial genera with a potential causal relationship to SP. After Benjamini-Hochberg corrected test, four bacterial genera emerged with a strong causal relationship to SP. Specifically, Oxalobacter (OR: 1.143, 95% CI 1.061-1.232, P = 0.0004) and Tyzzerella 3 (OR: 1.145, 95% CI 1.059-1.238, P = 0.0007) were identified as risk factors for LBP, while Ruminococcaceae UCG011 (OR: 0.859, 95% CI 0.791-0.932, P = 0.0003) was marked as a protective factor for LBP, and Olsenella (OR: 0.893, 95% CI 0.839-0.951, P = 0.0004) was recognized as a protective factor for low back pain or/and sciatica. No significant heterogeneity or horizontal pleiotropy was observed through alternative testing methods. Conclusion: This study establishes a causal relationship between the gut microbiota and SP, shedding light on the "gut-spine" axis. These findings offer novel perspectives for understanding the etiology of SP and provide a theoretical foundation for potential interventions targeting the gut microbiota to prevent and treat SP.

Association between gut microbiota and menstrual disorders: a two-sample Mendelian randomization study.

Background: Evidence from observational studies and clinical trials suggests that the gut microbiota is associated with gynecological diseases. However, the causal relationship between gut microbiota and menstrual disorders remains to be determined. Methods: We obtained summary data of gut microbiota from the global consortium MiBio-Gen's genome-wide association study (GWAS) dataset and data on menstrual disorders from the IEU Open GWAS project. MR-Egger, weighted median, inverse variance weighted, simple mode, and weighted mode were used to examine the causal association between gut microbiota and menstrual disorders. Thorough sensitivity studies were performed to confirm the data's horizontal pleiotropy, heterogeneity, and robustness. Results: Through MR analysis of 119 kinds of gut microbiota and 4 kinds of clinical phenotypes, it was discovered that 23 different kinds of gut microbiota were loosely connected to menstrual disorders. After FDR correction, the results showed that only Escherichia/Shigella (p = 0.00032, PFDR = 0.0382, OR = 1.004, 95%CI = 1.002-1.006) is related to menstrual disorders. Conclusion: According to our MR Analysis, there are indications of a causal relationship between menstrual disorders and gut microbiota. This finding could lead to new discoveries into the mechanisms behind menstrual disorders and clinical research involving the microbiota.

Intelligent structure prediction and visualization analysis of non-coding RNA in osteosarcoma research.

Background: Osteosarcoma (OS) is the most common bone malignant tumor in children and adolescents. Recent research indicates that non-coding RNAs (ncRNAs) have been associated with OS occurrence and development, with significant progress made in this field. However, there is no intelligent structure prediction and literature visualization analysis in this research field. From the perspective of intelligent knowledge structure construction and bibliometrics, this study will comprehensively review the role of countries, institutions, journals, authors, literature citation relationships and subject keywords in the field of ncRNAs in OS. Based on this analysis, we will systematically analyze the characteristics of the knowledge structure of ncRNAs in OS disease research and identify the current research hotspots and trends. Methods: The Web of Science Core Collection (WoSCC) database was searched for articles on ncRNAs in OS between 2001 and 2023. This bibliometric analysis was performed using VOSviewers, CiteSpace, and Pajek. Results: This study involved 15,631 authors from 2,631 institutions across 57 countries/regions, with a total of 3,642 papers published in 553 academic journals. China has the highest number of published papers in this research field. The main research institutions include Nanjing Medical University (n = 129, 3.54%), Shanghai Jiao Tong University (n = 128, 3.51%), Zhengzhou University (n = 110, 3.02%), and China Medical University (n = 109, 2.99%). Oncology Letters (n =139, 3.82%), European Review for Medical Pharmacological Sciences (120, 3.31%), and Molecular Medicine Reports (n = 95, 2.61%) are the most popular journals in this field, with Oncotarget being the most co-cited journal (Co-Citation = 4,268). Wei Wang, Wei Liu, and Zhenfeng Duan published the most papers, with Wang Y being the most co-cited author. "miRNA", "lncRNA" and "circRNA" are the main focuses of ncRNAs in OS studies. Key themes include "migration and invasion", "apoptosis and proliferation", "prognosis", "biomarkers" and "chemoresistance". Since 2020, hotspots and trends in ncRNA research in OS include "tumor microenvironment", "immune" and "exosome". Conclusion: This study represents the first comprehensive bibliometric analysis of the knowledge structure and development of ncRNAs in OS. These findings highlight current research hotspots and frontier directions, offering valuable insights for future studies on the role of ncRNAs in OS.

Gene association analysis to determine the causal relationship between immune cells and juvenile idiopathic arthritis.

BACKGROUND: Juvenile idiopathic arthritis (JIA) is a type of chronic childhood arthritis with complex pathogenesis. Immunological studies have shown that JIA is an acquired self-inflammatory disease, involving a variety of immune cells, and it is also affected by genetic and environmental susceptibility. However, the precise causative relationship between the phenotype of immune cells and JIA remains unclear to date. The objective of our study is to approach this inquiry from a genetic perspective, employing a method of genetic association analysis to ascertain the causal relationship between immune phenotypes and the onset of JIA. METHODS: In this study, a two-sample Mendelian randomization (MR) analysis was used to select single nucleotide polymorphisms (SNPs) significantly associated with immune cells as instrumental variables to analyze the bidirectional causal relationship between 731 immune cells and JIA. There were four types of immune features (median fluorescence intensity (MFI), relative cellular (RC), absolute cellular (AC), and morphological parameters (MP)). Finally, the heterogeneity and horizontal reproducibility of the results were verified by sensitivity analysis, which ensured more robust results. RESULTS: We found that CD3 on CM CD8br was causally associated with JIA at the level of 0.05 significant difference (95% CI = 0.630 ~ 0.847, P = 3.33 × 10-5, PFDR = 0.024). At the significance level of 0.20, two immunophenotypes were causally associated with JIA, namely: HLA DR on CD14+ CD16- monocyte (95% CI = 0.633 ~ 0.884, P = 6.83 × 10-4, PFDR = 0.16) and HLA DR on CD14+ monocyte (95% CI = 0.627 ~ 0.882, P = 6.9 × 10-4, PFDR = 0.16). CONCLUSION: Our study assessed the causal effect of immune cells on JIA from a genetic perspective. These findings emphasize the complex and important role of immune cells in the pathogenesis of JIA and lay a foundation for further study of the pathogenesis of JIA.

Bibliometric and Visualization Analysis of Biomechanical Research on Lumbar Intervertebral Disc.

Background: Biomechanical research on the lumbar intervertebral disc (IVD) provides valuable information for the diagnosis, treatment, and prevention of related diseases, and has received increasing attention. Using bibliometric methods and visualization techniques, this study investigates for the first time the research status and development trends in this field, with the aim of providing guidance and support for subsequent research. Methods: The Science Citation Index Expanded (SCI-Expanded) within the Web of Science Core Collection (WoSCC) database was used as the data source to select literature published from 2003 to 2022 related to biomechanical research on lumbar IVD. VOSviewer 1.6.19 and CiteSpace 6.2.R2 visualization software, as well as the online analysis platform of literature metrology, were utilized to generate scientific knowledge maps for visual display and data analysis. Results: The United States is the most productive country in this field, with the Ulm University making the largest contribution. Wilke HJ is both the most prolific author and one of the highly cited authors, while Adams MA is the most cited author. Spine, J Biomech, Eur Spine J, Spine J, and Clin Biomech are not only the journals with the highest number of publications, but also highly cited journals. The main research topics in this field include constructing and validating three-dimensional (3D) finite element model (FEM) of lumbar spine, measuring intradiscal pressure, exploring the biomechanical effects and related risk factors of lumbar disc degeneration, studying the mechanical responses to different torque load combinations, and classifying lumbar disc degeneration based on magnetic resonance images (MRI), which are also the hot research themes in recent years. Conclusion: This study systematically reviews the knowledge system and development trends in the field of biomechanics of lumbar IVD, providing valuable references for further research.

A clinical prediction model for lung metastasis risk in osteosarcoma: A multicenter retrospective study.

Background: Lung metastases (LM) have a poor prognosis of osteosarcoma. This study aimed to predict the risk of LM using the nomogram in patients with osteosarcoma. Methods: A total of 1100 patients who were diagnosed as osteosarcoma between 2010 and 2019 in the Surveillance, Epidemiology and End Results (SEER) database were selected as the training cohort. Univariate and multivariate logistic regression analyses were used to identify independent prognostic factors of osteosarcoma lung metastases. 108 osteosarcoma patients from a multicentre dataset was as valiation data. The predictive power of the nomogram model was assessed by receiver operating characteristic curves (ROC) and calibration plots, and decision curve analysis (DCA) was utilized to interpret the accurate validity in clinical practice. Results: A total of 1208 patients with osteosarcoma from both the SEER database(n=1100) and the multicentre database (n=108) were analyzed. Univariate and multivariate logistic regression analyses showed that Survival time, Sex, T-stage, N-stage, Surgery, Radiation, and Bone metastases were independent risk factors for lung metastasis. We combined these factors to construct a nomogram for estimating the risk of lung metastasis. Internal and external validation showed significant predictive differences (AUC 0.779, 0.792 respectively). Calibration plots showed good performance of the nomogram model. Conclusions: In this study, a nomogram model for predicting the risk of lung metastases in osteosarcoma patients was constructed and turned out to be accurate and reliable through internal and external validation. Moreover we built a webpage calculator (https://drliwenle.shinyapps.io/OSLM/) taken into account nomogram model to help clinicians make more accurate and personalized predictions.

Establishment and validation of a nomogram and web calculator for the risk of new vertebral compression fractures and cement leakage after percutaneous vertebroplasty in patients with osteoporotic vertebral compression fractures.

PURPOSE: The aim of this work was to investigate the risk factors for cement leakage and new-onset OVCF after Percutaneous vertebroplasty (PVP) and to develop and validate a clinical prediction model (Nomogram). METHODS: Patients with Osteoporotic VCF (OVCF) treated with PVP at Liuzhou People's Hospital from June 2016 to June 2018 were reviewed and met the inclusion criteria. Relevant data affecting bone cement leakage and new onset of OVCF were collected. Predictors were screened using univariate and multi-factor logistic analysis to construct Nomogram and web calculators. The consistency of the prediction models was assessed using calibration plots, and their predictive power was assessed by tenfold cross-validation. Clinical value was assessed using Decision curve analysis (DCA) and clinical impact plots. RESULTS: Higher BMI was associated with lower bone mineral density (BMD). Higher BMI, lower BMD, multiple vertebral fractures, no previous anti-osteoporosis treatment, and steroid use were independent risk factors for new vertebral fractures. Cement injection volume, time to surgery, and multiple vertebral fractures were risk factors for cement leakage after PVP. The development and validation of the Nomogram also demonstrated the predictive ability and clinical value of the model. CONCLUSIONS: The established Nomogram and web calculator (https://dr-lee.shinyapps.io/RefractureApp/) (https://dr-lee.shinyapps.io/LeakageApp/) can effectively predict the occurrence of cement leakage and new OVCF after PVP.

Complement C1q (C1qA, C1qB, and C1qC) May Be a Potential Prognostic Factor and an Index of Tumor Microenvironment Remodeling in Osteosarcoma.

The tumor microenvironment (TME) has important effects on the tumorigenesis and development of osteosarcoma (OS). However, the dynamic mechanism regulating TME immune and matrix components remains unclear. In this study, we collected quantitative data on the gene expression of 88 OS samples from The Cancer Genome Atlas (TCGA) database and downloaded relevant clinical cases of OS from the TARGET database. The proportions of tumor-infiltrating immune cells (TICs) and the numbers of immune and matrix components were determined by CIBERSORT and ESTIMATE calculation methods. Protein-protein interaction (PPI) network construction and Cox regression analysis were conducted to analyze differentially expressed genes (DEGs). The complement components C1qA, C1qB and C1qC were then determined to be predictive factors through univariate Cox analysis and PPI cross analysis. Further analysis found that the levels of C1qA, C1qB and C1qC expression were positively linked to OS patient survival time and negatively correlated with the clinicopathological feature percent necrosis at definitive surgery. The results of gene set enrichment analysis (GSEA) demonstrated that genes related to immune functions were significantly enriched in the high C1qA, C1qB and C1qC expression groups. Proportion analysis of TICs by CIBERSORT showed that the levels of C1qA, C1qB and C1qC expression were positively related to M1 and M2 macrophages and CD8+ cells and negatively correlated with M0 macrophages. These results further support the influence of the levels of C1qA, C1qB and C1qC expression on the immune activity of the TME. Therefore, C1qA, C1qB and C1qC may be potential indicators of remodeling in the OS TME, which is helpful to predict the prognosis of patients with OS and provide new ideas for immunotherapy for OS.

[Simultaneous Determination of Three Components in Ficus microcarpa Leaves by HPLC].

OBJECTIVE: To develop an HPLC method for the content determination of benzoic acid, 4-hydroxyphenylacetic acid and acetosyringonecas in Ficus microcarpa Leaves. METHODS: The determination was performed on Purospher® STAR C18 (250 mm x 4.6 mm,5 µm). The mobile phase was consisted of acetonitrile-0.2% phosphoric acid aqueous solution with linear gradient elution and the flow rate of 1.0 mL/min. The column temperature was set at 35 °C and the detection wavelength was 270 nm. RESULTS: The linear range of benzoic acid, 4-hydroxyphenylacetic acid and acetosyringonecas was 0.0121-1.21 µg (r = 0.9995), 0.423-42.32 [Lg ( r = 0.9999) and 0.047-4.70 pg( r = 0. 9996) , respectively. The average recovery was 100.7, 101.2 and 96.5 respectively. CONCLUSION: This method is simple,reproducible,and can be used for determination of three components of benzoic acid, 4-hydroxyphenylacetic acid and acetosyringonecas in Ficus microcarpa Leaves.

Neuroprotective Effects of (-)-Epigallocatechin-3-Gallate Against Focal Cerebral Ischemia/Reperfusion Injury in Rats Through Attenuation of Inflammation.

Stroke is the second leading cause of death among adults worldwide. (-)-Epigallocatechin-3-gallate (EGCG) has been demonstrated to exhibit neuroprotective functions in cerebral ischemia/reperfusion injury. However, the underlying mechanisms in this process and its contribution to the protection function remain unknown. The current study examined the neuroprotective effects of EGCG after transient middle cerebral artery occlusion (tMCAO) in rats. tMCAO for 120 min was induced in male Sprague-Dawley rats treated with EGCG (50 mg/kg, i.p.) or Vehicle immediately after reperfusion. Neurological score, infarct ratio and inflammation-related molecules (assessed by 2,3,5-triphenyltetrazolium chloride, enzyme-linked immunosorbent assays, quantitative real-time PCR or western blotting) were estimated at 24 h after operation. EGCG prevented the impairment of neurological function and decreased the infarct volume, compared with the Vehicle group. The inflammation-related molecules TNF-α, IL-1ß, IL-6 levels usually caused by ischemia/reperfusion were significantly ameliorated by EGCG. EGCG also inhibited the upregulation of nuclear factor-kappa B/p65 (NF-κB/p65), and induction of cyclooxygenase 2 and inducible nitric oxide synthase. The present study indicates that EGCG may be a promising therapeutic agent for cerebral ischemia/reperfusion injury through attenuation of inflammation.

[Study on Effective Parts of Ficus microcarpa Leaves by Serum HPLC Fingerprint].

OBJECTIVE: To study the relevance between the drug effects and serum HPLC fingerprint of chemical constituents in blood from Ficus microcarpa leaves. METHODS: Fingerprints of the preparation and drug-containing serum of rats were established by HPLC. Based on the fingerprints, chemical constituents in blood were investigated. RESULTS: There were seven common peaks in the HPLC fingerprints of drug-containing serum of rats. Polarity fraction of the chemical constituents in blood existed in the ethyl acetate extract, and five fingerprint peaks of serum HPLC fingerprint existed in n-butanol extract. CONCLUSION: Determination of the component groups in blood provides some data on material basis study in vivo for Ficus microcarpa leaves.