ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

Integrated metabolomic and lipidomic profiling,utilizing liquid chromatography coupled with high-resolution mass spectrometry(LC-HRMS),has emerged as a pivotal strategy for biomarker discovery.However,the inherent polarity disparity between metabolites and lipids complicates simultaneous analysis.To address this,a dual-stationary phase polarity-extended liquid chromatography(PELC)system was developed,which surpassed conventional one-dimensional LC(1D-LC)by enabling comprehensive coverage of both polar and non-polar compounds within a single injection.This system enhanced chromatographic resolution,peak capacity,and throughput while minimizing analytical variability.Extracellular vesicles(EVs),lipid bilayer-enclosed nanoparticles ubiquitously present in biofluids,had gained prominence as reservoirs of cancer biomarkers due to their cargo stability and pathophysiological relevance.Herein,the application of PELC-HRMS for concurrent metabolome-lipidome profiling in EVs was pioneered.A total of 193 metabolites were identified using this technique coupled with MS-DIAL software and Human Metabolome Database.Subsequently,this technique was employed to explore potential biomarkers for prostate cancer(PCa).Multivariate analysis identified 17 differentially abundant metabolites in PCa,implicating dysregulated pathways including purine metabolism,starch and sucrose metabolism,galactose metabolism,cysteine and methionine metabolism,and biosynthesis of unsaturated fatty acids.Notably,creatine(AUC=0.92)and DG 42:5(AUC=0.80)demonstrated robust diagnostic efficacy,attributable to their broad polarity ranges and EV-specific enrichment.This study established PELC as a high-fidelity platform for multi-omics integration in complex biospecimens,advancing mechanistic insights into metabolic rewiring and disease pathophysiology.

Objective:To investigate the efficacy and safety of transurethral water vapor thermal therapy(WVTT)using the Rezūm system for benign prostatic hyperplasia(BPH)in the real world.Methods:A total of 181 patients with BPH were recruited from the Second Affiliated Hospital of Nanjing Medical University from August 2022 to December 2023,of whom 173 patients were treated with WVTT using the Rezūm system,while 8 patients were treated with WVTT combined with TURP.They were followed up at 1,3,and 6 months postoperatively to assess changes in the IPSS,QoL,Qmax,IIEF-5,and the occurrence of any complications.Results:All 181 surgeries in this group were successfully completed.The operation time of the Rezūm system was(4.6±1.4)mi-nutes.The postoperative indwelling catheterization time was(8.0±2.1)days.With a follow-up of at least 6 months,there was a significant decrease in PV,IPSS and QoL,and a remarkable increase had been found in Qmax as well(P＜0.05).There was no sig-nificant difference in IIEF-5 before and after the operation(P＞0.05).In this groups of patients,postoperative complications mainly included 95 cases(52.5％)of gross hematuria,6 cases(3.3％)of retrograde ejaculation,5 cases(2.8％)of urethral stricture,4 cases(2.2％)of prostatitis,and 10 cases(5.5％)of urinary tract infection.Four cases(2.2％)underwent surgical retreatment for BPH after surgery.Conclusion:In the real world,the use of Rezūm thermal steam ablation system for the treatment of BPH has sat-isfactory short-term effect,short surgical time,and significant improvement in IPSS,QoL,Qmax,which does not adversely affect sexu-al function.

[This corrects the article DOI: 10.1016/j.apsb.2022.03.002.].

Objective:To evaluate the relationship between postoperative changes in femoral head coverage (FHC) after S 2-Alar-Iliac (S 2AI) screw fixation and the development of sagittal imbalance during follow-up in patients with adult spinal deformity (ASD), providing insights for clinical assessment and treatment strategies. Methods:A consecutive cohort of 98 ASD patients who underwent S2AI fixation between September 2019 and September 2021 was retrospectively analyzed. Patients were divided into two groups based on changes in femoral head coverage (ΔFHC): the FHC-C group (upper quartile ΔFHC, 25 cases) and the FHC-NC group (lower quartile ΔFHC, 24 cases). Additionally, patients were classified into proximal junctional kyphosis (PJK) and non-PJK groups based on their clinical outcomes at the last follow-up. Standing full-spine anteroposterior and lateral X-rays were taken preoperatively, postoperatively, and at the two-year follow-up to measure and document the following spinal parameters: Cobb angle, proximal lumbar lordosis (PLL), distal lumbar lordosis (DLL), lumbar lordosis (LL), lordosis distribution index (LDI), sagittal vertical axis (SVA), coronal balance distance (CBD), thoracic kyphosis (TK), T 1 pelvic angle (T 1PA), pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), PI-LL, and proximal junctional angle (PJA). Parameters related to hip joint coverage included: femoral head coverage (FHC), lateral center-edge angle (LCE angle), acetabular index (AI), Sharp angle, and extrusion index (EI). Comparisons of radiographic indicators between the two groups were performed at preoperative, postoperative, and final follow-up assessments. The visual analogue scale (VAS) was used to evaluate the hip pain and back pain. Results:At final follow-up, the incidence of PJK was significantly higher in the FHC-NC group [37.5% (9/24)] compared to the FHC-C group [16.0% (4/25)] (χ 2=3.952, P=0.042). Moreover, the increase in sagittal vertical axis (ΔSVA) was significantly greater in the FHC-NC group (35.9±44.7 mm vs. 14.6±31.8 mm, t=2.216, P=0.031). Patients with PJK had significantly higher preoperative T 1PA (36.8°±10.8° vs. 31.9°±18.4°, t=2.150, P=0.034) and lower immediate postoperative ΔFHC (1.7%±1.5% vs. 3.3%±2.5%, t=2.987, P=0.004), as well as lower changes in lateral center-edge angle during follow-up (0.3°±3.0° vs. 1.1°±8.9°, t=2.334, P=0.022). Pearson correlation analysis revealed significant negative correlations between postoperative ΔFHC and both ΔSVA ( r=-0.374, P=0.008) and proximal junctional angle changes (ΔPJA, r=-0.429, P=0.006). Additionally, increases in VAS leg pain scores correlated negatively with immediate postoperative FHC ( r=-0.314, P=0.025) and ΔFHC ( r=-0.298, P=0.031). Logistic regression indicated that immediate postoperative ΔFHC was a protective factor against PJK [ OR=0.722, 95% CI (0.541, 0.963), P=0.009), with a ROC-determined optimal ΔFHC cut-off of 3.90% (AUC=0.723, Youden index=0.847). Conclusions:Postoperative evaluation of femoral head coverage is clinically important for ASD patients undergoing S2AI screw fixation. A pre-to-post ΔFHC below 3.90% may indicate reduced hip compensation capacity, increasing risks for hip pain, sagittal imbalance progression, and PJK postoperatively.

Objective:To predict mechanical complications (MC) following spinal deformity surgery for adult spine deformity (ASD) using machine learning models, identify key risk factors, and develop a visualizable tool for individualized risk assessment.Methods:Clinical and radiological data from 525 patients with ASD who underwent surgery in our hospital between January 2017 and December 2021 were collected. Patients were randomly assigned to a training set (70%) and a test set (30%) for model development. The cohort included 88 males and 437 females, with a mean age of 42.2±18.1 years. Variables included demographic data, comorbidities, local and systemic radiological parameters, paraspinal muscle fat infiltration (FI), and vertebral bone quality (VBQ) scores. Multiple machine learning algorithms: Random Forest (RF), Gaussian Naive Bayes (GNB), Light GBM, Support Vector Machine (SVM), XGBoost (XGB), and Logistic Regression (LR) were trained and evaluated. Model performance was compared using the receiver operating characteristic curve (ROC) and precision-recall curve (PRC). SHAP (Shapley Additive Explanations) was used to rank risk factors, while LIME (Local Interpretable Model-Agnostic Explanations) was applied to visualize MC risk in individual cases.Results:Of the 525 patients, 135 (25.7%) developed postoperative MC. Among these, 80 (59.3%) experienced proximal junction kyphosis or failure (PJK/PJF), 7 (5.2%) had distal junction kyphosis or failure (DJK/DJF), 28 (20.7%) sustained rod fractures, and 29 (21.5%) showed significant loss of correction. In the validation cohort, the RF model achieved the highest area under the curve (AUC=0.80), followed by GNB (0.77), XGB (0.76), LR (0.74), LightGBM (0.73), and SVM (0.66). The RF model also demonstrated the best PRC value (0.58), highest sensitivity (0.65), and lowest Brier score (0.20). GNB, Light GBM, and LR models achieved the highest accuracy (0.78 each), while LightGBM exhibited the highest specificity (0.93). SHAP analysis identified higher preoperative VBQ scores, larger T 1 pelvic angle (TPA), and higher paraspinal muscle FI as the main risk factors for MC. Based on the RF model, a LIME-based tool was successfully constructed for individualized MC risk estimation. Conclusion:The RF model demonstrated the best overall predictive performance for MC. A machine learning-based prediction model has the potential to provide valuable guidance for surgical decision-making in ASD patients.

Objective The experimental method of cervical vestibular evoked myogenic potential(cVEMP)with high retest reliability was designed to verify the accuracy of locating sternocleidomastoid muscle in mice.Methods Three 2-month-old ICR male mice were selected,one of which was dissected to locate the sternocleidomastoid muscle,while the other two were used to design the experimental plan to verify the accuracy of localization.Results The recording electrode positioned on the sternocleidomastoid muscle of mice can repeatedly elicit clear cVEMP waveform.Conclusion The cVEMP waveform with high retest reliability can be measured in both experimental mice,suggesting that the localization of sternocleidomastoid muscle in this research is accurate.

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

Emodin is a hydroxyanthraquinone compound that is widely distributed and has multiple pharmacological activities, including anti-diarrheal, anti-inflammatory, and liver-protective effects. Research indicates that emodin may be one of the main components responsible for inducing hepatotoxicity. However, studies on the mechanisms of liver injury are relatively limited, particularly those related to bile acids(BAs) metabolism. This study aims to systematically investigate the effects of different dosages of emodin on BAs metabolism, providing a basis for the safe clinical use of traditional Chinese medicine(TCM)containing emodin. First, this study evaluated the safety of repeated administration of different dosages of emodin over a 5-week period, with a particular focus on its impact on the liver. Next, the composition and content of BAs in serum and liver were analyzed. Subsequently, qRT-PCR was used to detect the mRNA expression of nuclear receptors and transporters related to BAs metabolism. The results showed that 1 g·kg~(-1) emodin induced hepatic damage, with bile duct hyperplasia as the primary pathological manifestation. It significantly increased the levels of various BAs in the serum and primary BAs(including taurine-conjugated and free BAs) in the liver. Additionally, it downregulated the mRNA expression of farnesoid X receptor(FXR), retinoid X receptor(RXR), and sodium taurocholate cotransporting polypeptide(NTCP), and upregulated the mRNA expression of cholesterol 7α-hydroxylase(CYP7A1) in the liver. Although 0.01 g·kg~(-1) and 0.03 g·kg~(-1) emodin did not induce obvious liver injury, they significantly increased the level of taurine-conjugated BAs in the liver, suggesting a potential interference with BAs homeostasis. In conclusion, 1 g·kg~(-1) emodin may promote the production of primary BAs in the liver by affecting the FXR-RXR-CYP7A1 pathway, inhibit NTCP expression, and reduce BA reabsorption in the liver, resulting in BA accumulation in the peripheral blood. This disruption of BA homeostasis leads to liver injury. Even doses of emodin close to the clinical dose can also have a certain effect on the homeostasis of BAs. Therefore, when using traditional Chinese medicine or formulas containing emodin in clinical practice, it is necessary to regularly monitor liver function indicators and closely monitor the risk of drug-induced liver injury.
Emodin/administration & dosage* ; Bile Acids and Salts/metabolism* ; Animals ; Male ; Liver/injuries* ; Chemical and Drug Induced Liver Injury/genetics* ; Drugs, Chinese Herbal/adverse effects* ; Humans ; Rats, Sprague-Dawley ; Mice ; Rats

OBJECTIVE: To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures. METHODS: Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details. RESULTS: Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters. CONCLUSION Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans ; Male ; Female ; Radius Fractures/surgery* ; Middle Aged ; Adult ; Aged ; Aged, 80 and over ; Tomography, X-Ray Computed/methods* ; Retrospective Studies ; Software ; Wrist Fractures