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.

Manual Therapy for a Chronic Non-Specific Low Back Pain Rat Model.

Chronic low back pain (CLBP) is a highly prevalent condition worldwide and a major cause of disability. The majority of patients with CLBP are diagnosed with chronic non-specific low back pain (CNLBP) due to an unknown pathological cause. Manual therapy (MT) is an integral aspect of traditional Chinese medicine and is recognized as Tuina in China. It involves techniques like bone-setting and muscle relaxation manipulation. Despite its clinical efficacy in treating CNLBP, the underlying mechanisms of MT remain unclear. In animal experiments aimed at investigating these mechanisms, one of the main challenges is achieving normative MT on CNLBP model rats. Improving the stability of finger strength is a key issue in MT. To address this technical limitation, a standardized procedure for MT on CNLBP model rats is presented in this study. This procedure significantly enhances the stability of MT with the hands and alleviates common problems associated with immobilizing rats during MT. The findings of this study are of reference value for future experimental investigations of MT.

Platelet proteomics in diagnostic differentiation of primary immune thrombocytopenia using SELDI-TOF-MS.

BACKGROUND: Primary immune thrombocytopenic purpura (pITP) is defined as isolated autoimmune thrombocytopenia with idiopathic low platelet count, normal bone marrow, and unexplained causes of thrombocytopenia. Currently there is no definite criterion for ITP diagnosis. METHODS: We conducted proteomic screen of patients with pITP, secondary immune thrombocytopenia (sITP), and healthy controls using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). The proteomic profiles were obtained from platelet lysate samples of 82 healthy adult controls, 64 pITP, and 70 sITP patients, from which we screened marker proteins with significant differences, and constructed a diagnosis model using the artificial neural network (ANN) technique. RESULTS: We identified 6 marker proteins in the platelet lysates of pITP patients. This diagnosis method differentiated pITP patients from sITP effectively with a sensitivity of 96.9% (31/32), a specificity of 71.0% (54/76), and the area under the ROC curve of 0.864 in the training set, and a sensitivity of 87.5% (28/32), a specificity of 69.7% (53/76), and a positive predictive value of 75.0% (81/108) in the test set. CONCLUSION: The artificial neural network model based on platelet protein profiling established a potential pITP diagnosis platform.

Protein Biomarkers in Serum of Patients with Schizophrenia.

This study was devised to identify potential biomarkers of schizophrenia (SP) using proteomics techniques. We obtained 44 serum specimens from patients with SP, 26 specimens from patients with depression, and 40 specimens from healthy controls. Immobilized metal affinity capture protein chips (IMAC30) and surface-enhanced laser desorption-ionization time-of-flight mass spectrometry were used to isolate and obtain mass spectrometric data of differentially expressed serum proteins. The sequences of the peaks discrepant among the study groups were obtained using matrix-assisted laser desorption/ionization mass spectrometry and proteins identified using Mascot database. In the SP group, there were 91 protein peaks that were different from other study groups at the p value of <0.05 and 54 peaks different at the p value of <0.01. Two protein peaks at the mass-to-charge ratio of 1,207.41 and 1,466.78 were markedly different among the study groups, with the lowest expression in specimens from patients with SP. The amino acid sequences were, respectively, Glu-Gly-Asp-Phe-Leu-Ala-Glu-Gly-Gly-Gly-Val-Arg (EGDFLAEGGGVR) and Asp-Ser-Gly-Glu-Gly-Asp-Phe-Leu-Ala-Glu-Gly-Gly-Gly-Val-Arg (DSGEGDFLAEGGGVR). These proteins were identified as the N-terminal fragments of fibrinogen. In conclusion, these biomarker proteins may be useful for molecular diagnosis of SP.

[Diagnosis model of idiopathic thrombocytopenic purpura based on platelet differential proteome].

This study was purposed to establish a new quick and simple diagnostic method with high sensitivity and good specificity for idiopathic thrombocytopenic purpura (ITP) and to evaluate its significance. 240 platelet lysates (from patients with ITP, leukemia, MDS, and healthy adults, each of 60 cases) were randomly assigned to training set (120 cases) or validation set (120 cases), all of them were detected by surface enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS), in order to identify the differentially expressed protein, the diagnostic model was established by means of artificial neural network (ANN), and was validated by blind test with SPSS 17.0. The results showed that 5 marked proteins significantly differentially expressed (P < 0.01), m/z of highly expressed proteins were 2234.30, 3476.36, and 7526.29, m/z of low expressed proteins were 4990.02 and 5152.39, respectively. The sensitivity and specificity of diagnostic model were 80.6% and 77.3% respectively. The area under the ROC curve consisting of the output value of artificial neura1 network was 0.837. Efficacy of the model was validated by means of blinded test. It is concluded that the ANN model is useful for clinical diagnosis of ITP on the basis of platelet protein fingerprint spectrum.