This study aimed to quantitatively investigate the role of marginal chordae of the mitral valve during static closure by analyzing the force within these chordae and its potential correlation with the transvalvular pressure. Porcine (n = 10) and human (n = 4) mitral valves were mounted in a saddle-shaped annulus clamp, while an in vitro system was utilized to replicate a physiological systolic blood pressure by vacuum pressure applied to the atrial side of the valve. A Millar pressure catheter and force transducers (“C-gauges”) were used to acquire the data. Strut chordal force was recorded simultaneously with the marginal chordal force, to serve as a verification of the employed equipment. The marginal chordal force in porcine and human averaged to 0.012 N ± 0.008 N and 0.006 N ± 0.008 N respectively at peak systolic pressure of 120 mmHg. Additionally, a simplified finite element study was conducted and supports low marginal forces relative to intermediary chords. This low force calls into question the traditionally-described role of the marginal chordae in preventing mitral prolapse at closure. The chords do, however, still show signs of assisting with the leaflets’ positioning. The relationship between marginal chordal forces and transvalvular pressure varies significantly across experiments, further obfuscating their role in normal valvular function.
Neuroinflammation is a key driver and an important therapeutic target of neurodegeneration. Dysregulated nuclear factor-κB (NF-κB) signaling plays a central role in neuroinflammation and depends on M1 and K63 ubiquitination of NF-κB essential modulator (NEMO). Ivangustin (IVA) is a sesquiterpene lactone isolated from Inula japonica Thunb., a traditional Chinese medicine has been used to treat inflammatory diseases. But its anti-neuroinflammatory effects and molecular targets remain unclear. This study aimed to evaluate the anti-neuroinflammatory effects of IVA and elucidate its direct functional target and underlying mechanism. Integrated in vitro, in vivo, and in silico/bioinformatics approaches were employed. The anti-neuroinflammatory activity of IVA was evaluated in LPS-stimulated BV2 cells, primary microglia, and an LPS-induced acute cognitive impairment mouse model. Mechanistic studies were performed using pull-down, liquid chromatography-tandem mass spectrometry (LC–MS/MS), cellular thermal shift assay (CETSA), drug affinity responsive target stability (DARTS), gene knockdown, point mutation and bioinformatics analyses. In vitro, IVA significantly inhibited nitric oxide (NO) production and mRNA and protein expression of pro-inflammatory factors in LPS-stimulated microglia. Furthermore, IVA significantly suppressed inhibitor of NF-κB kinase α/β (IKKα/β) and inhibitory subunit of NF-κB alpha (IκBα) phosphorylation, IκBα degradation, and NF-κB p65 phosphorylation and nuclear translocation, thereby blocking the expression of NF-κB-targeted genes. Its anti-neuroinflammatory activity was attenuated by thiol donors, indicating the importance of its electrophilic lactone moiety. Furthermore, ubiquitin conjugating enzyme E2L3 (UBE2L3) was identified as the functional target of IVA in BV2 cells, whereas UBE2L3 knockdown markedly attenuated IVA-mediated anti-neuroinflammatory action. Bioinformatics analysis suggests UBE2L3 overexpression as a potential risk factor for neurodegenerative diseases. Mechanistically, IVA covalently bound to the catalytic cysteine 86 of UBE2L3, thereby inhibiting UBE2L3-mediated M1 and K63 ubiquitination of NEMO, which is crucial for NF-κB activation. In vivo, IVA ameliorated LPS-induced cognitive impairment and neuroinflammation in mice via inhibiting Iba1 expression and suppressing NF-κB activation. IVA exerts anti-neuroinflammatory effects by covalently targeting UBE2L3 and suppressing NF-κB signaling. These findings also identify UBE2L3 as a potential therapeutic target for neuroinflammation and support IVA as a promising lead compound for further preclinical investigation of neuroinflammatory disorders.
Traditional Chinese Medicine (TCM) clinical practice depends on both codified theoretical knowledge and practitioner-specific experience, which differ in their data sources, reasoning patterns, and scope of generalization. We developed DFGLM-TCM, a modular large language model-based service system that separately models these two knowledge types through task-oriented components and coordinates them within a unified multi-task architecture. The knowledge-oriented component integrated a curated 22-GB TCM corpus containing approximately 3 million structured entries, a manually validated knowledge graph with more than 200,000 entities, and retrieval-augmented generation for literature retrieval and general TCM question answering. The experience-oriented component was trained using approximately 5000 authentic outpatient records from a senior TCM practitioner and 2000 expert-reviewed augmented cases to provide practitioner-specific diagnostic and prescription references. Through standardized interfaces and role-based access, the system supports knowledge retrieval, question answering, structured consultation, and prescription reference for clinicians, patients, and students. In an expert-rated evaluation of 100 TCM knowledge questions, DFGLM-TCM achieved the highest descriptive mean score among the evaluated models (4.48 ± 0.76). In 454 independent pulmonary-nodule cases, the experience-oriented component achieved a prescription-consistency score of 8.95 ± 0.63, exceeding that of the model additionally trained with general TCM knowledge (7.52 ± 0.44). A one-month assessment involving 35 physicians at three primary-care institutions suggested favorable short-term usability and acceptance. These findings highlight the value of separating general TCM knowledge from practitioner-specific experience while coordinating task-oriented training and multi-task services within a unified system, and support further evaluation of DFGLM-TCM as an auxiliary reference tool in broader clinical settings.
Traumatic brain injury (TBI) is associated with high morbidity, disability, and long-term neurological sequelae. Mitochondrial dysfunction is a central component of secondary injury after TBI, contributing to impaired energy metabolism, oxidative stress, calcium dysregulation, neuroinflammation, and neuronal apoptosis. This review summarizes current evidence regarding acupuncture-mediated regulation of mitochondrial homeostasis after TBI, focusing on structural homeostasis, quantitative homeostasis, and functional/metabolic homeostasis. We distinguish direct evidence from TBI models, indirect evidence from related brain injury models, and hypothesis-generating mechanisms. Particular attention is given to mitochondrial dynamics, mitochondrial biogenesis, mitophagy, energy metabolism, oxidative stress, calcium signaling, mitochondrial membrane potential, apoptosis, intercellular mitochondrial transfer, and putative upstream neural and humoral pathways. Current preclinical evidence suggests that acupuncture, particularly electroacupuncture, may influence mitochondrial homeostasis after TBI through multidimensional and context-dependent mechanisms. However, direct TBI-specific evidence remains limited, and several proposed mechanisms require further validation before acupuncture-mediated mitochondrial regulation can be considered a clinically established therapeutic strategy.
Aortic stenosis (AS) develops from calcific aortic valve disease (CAVD), which narrows the aortic valve opening as leaflet stiffness increases due to calcium deposition. This study extends the Reverse Calcification Technique (RCT) by incorporating a time dimension to develop a quantitative parametric model for patient-specific prediction of CAVD progression from sequential CT scans. Seventeen pre-transcatheter aortic valve replacement (TAVR) patients underwent sequential CT scans (1.2–6.5 years); baseline aortic valve calcification (AVC) volumes: ≈ 250 to ≈ 1,600 mm3 (cohort mean ≈ 730 mm3 at the first scan and ≈ 920 mm3 at the follow-up scan). A parametric model was developed using two approaches: forward prediction (mild to severe stages) and backward reconstruction (from severe to moderate stages). 34 test cases were assessed through alternating calibration and verification, with performance evaluated using Bland–Altman analysis, paired t-tests, and relative error calculations. For scan intervals under 3 years, forward prediction achieved a mean absolute error of 77 mm3 (7.0
