Pulmonary arterial hypertension (PAH) is a progressive disorder that can lead to right ventricular failure and severe consequences. Despite extensive efforts, limited progress has been made in preventing the progression of PAH. Mitochondrial dysfunction is implicated in the development of PAH, but the key mitochondrial functional alterations in the pathogenesis have yet to be elucidated. We integrated three microarray datasets from the Gene Expression Omnibus (GEO), including 222 lung samples (164 PAH, 58 controls), for differential expression and functional enrichment analyses. Machine learning identified key mitochondria-related signaling pathways. PAH and control lung tissue samples were collected, and transcriptomic and metabolomic profiling were performed. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis investigated shared pathways, and canonical correlation analysis assessed gene-metabolite relationships. In the GEO datasets, mitochondria-related signaling pathways were significantly enriched in PAH samples, in particular the electron transport chain (ETC) in mitochondrial oxidative phosphorylation system. Notably, the electron transport from cytochrome c to oxygen in ETC was identified as the most crucial mitochondria-related pathway, which was down-regulated in PAH samples. Transcriptomic profiling of the clinical lung tissue analysis identified 14 differentially expressed genes (DEGs) related to mitochondrial function. Metabolomic analysis revealed three differential metabolites in PAH samples: increased 3-phenyllactic acid and ADP, and decreased citric acid. Mitochondria-related genes highly correlated with these metabolites included KIT, OTC, CAMK2A, and CHRNA1. Down-regulation of electron transport from cytochrome c to oxygen in mitochondrial ETC and disruption of the citric acid cycle homeostasis may contribute to PAH pathogenesis. 3-phenyllactic acid emerges as a potential novel diagnostic biomarker for PAH. These findings offer insights for developing novel PAH therapies and diagnostics.

Background: The length of time for clinical improvement of patients with thymomatous myasthenia gravis (MG) after extended thymectomy is not clear. The purpose of this study was to determine the length of time after thymectomy in patients with thymomatous MG to achieve a 3-point reduction of Quantitative Myasthenia Gravis Score (QMGS), and identify variables associated with a failure to achieve the reduction. Methods: The records of patients with thymomatous MG who underwent extended thymectomy from January 2005 to December 2018 were retrospectively reviewed. The primary end point was a reduction of 3 points of QMGs and the secondary end point was another reduction of 3 points of QMGs. Results: A total of 481 patients were included in the analysis, the mean age of the patients was 41.63 ± 8.55 years, and approximately 60% were male. The median time to achieve a 3 point decrease in QMGS was 6 months, and the median time to achieve another 3 point decrease was 30 months. Multivariable analysis indicated that age ≥ 42 years and Masaoka-Koga stage > I were associated with a lower probability of achieving a 3 point decrease in QMGS (HR = 0.55 and 0.65, respectively). Likewise, multivariable analysis indicated that age ≥ 42 years and Masaoka-Koga stage > I were associated with a lower probability of achieving a second 3 point decrease in QMGS (HR = 0.53 and 0.53, respectively). Conclusions: In patients with thymomatous MG who receive thymectomy, age ≥ 42 years and Masaoka-Koga stage > I are associated with a worse prognosis and failure to achieve a 3 point decrease in QMGS.

Background: Accurate assessment of pathologic complete response (pCR) after neoadjuvant immunochemotherapy (NICT) is crucial to implement active surveillance or tailor therapeutic strategies for esophageal squamous cell carcinoma (ESCC), while reliable non-invasive methods for pCR prediction are lacking. We aimed to evaluate the potential of integrating circulating tumor DNA (ctDNA) and PET/CT for predicting pCR to NICT for ESCC. Methods: A total of 123 eligible patients were enrolled, including 68 patients from our prospective clinical trial (ChiCTR2000028900) and a real-world study (NCT04822103) that formed the discovery cohort, as well as 55 patients from another clinical trial (ChiCTR2100051763) comprising the validation cohort. Blood samples for ctDNA sequencing and PET/CT metrics were collected before and after NICT. Results: The ctDNA status and PET/CT parameters at the post-NICT stage rather than the pre-NICT stage significantly differentiated pCR from non-pCR patients. ctDNA and PET/CT synergistically enhanced the prediction of pCR from perspectives of sensitivity and specificity, respectively. The model integrating ctDNA concentration and mean standardized uptake value (SUVmean) demonstrated area under curves (AUCs) of 0.860 in the discovery cohort and 0.798 in the validation cohort for pCR prediction and stratified patients into high- and low-risk groups with differential survival prospects. The key gene modules converged on TP53 as the core mutation for pCR prediction, among which those located in the exon regions contributed the most to its predictive capacity. The model constructed based on TP53 mutation and SUVmean differentiated pCR from non-pCR with comparable performance to the model based on PET/CT and the overall ctDNA concentration. Conclusion: The combination of post-treatment TP53-centric ctDNA and PET/CT synergistically enhances the prediction of pCR following NICT in ESCC patients, indicating the potential to inform clinical decision-making for these patients.

Esophageal disease is a common disorder of the digestive system that can severely affect the quality of life and prognosis of patients. Esophageal stenting is an effective treatment that has been widely used in clinical practice. However, esophageal stents of different types and parameters have varying adaptability and effectiveness for patients, and they need to be individually selected according to the patient’s specific situation. The purpose of this study was to provide a reference for clinical doctors to choose suitable esophageal stents. We used 3D printing technology to fabricate esophageal stents with different ratios of thermoplastic polyurethane (TPU)/(Poly-ε-caprolactone) PCL polymer, and established an artificial neural network model that could predict the radial force of esophageal stents based on the content of TPU, PCL and print parameter. We selected three optimal ratios for mechanical performance tests and evaluated the biomechanical effects of different ratios of stents on esophageal implantation, swallowing, and stent migration processes through finite element numerical simulation and in vitro simulation tests. The results showed that different ratios of polymer stents had different mechanical properties, affecting the effectiveness of stent expansion treatment and the possibility of postoperative complications of stent implantation.

Background Pulmonary arterial hypertension (PAH) is a progressive disorder that can lead to right ventricular failure and severe consequences. Despite extensive efforts, limited progress has been made in preventing the progression of PAH. Understanding its pathogenesis is crucial for developing better treatments. Methods We integrated three microarray datasets from the Gene Expression Omnibus (GEO), including 222 lung samples (164 PAH, 58 controls), for differential expression and functional enrichment analyses. Machine learning identified key signaling pathways. PAH and control lung tissue samples were collected, and transcriptomic and metabolomic profiling were performed. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis investigated shared pathways, and canonical correlation analysis assessed gene-metabolite relationships. Results In the GEO datasets, mitochondria-related pathways were significantly enriched in PAH samples, in particular the electron transport chain in mitochondrial oxidative phosphorylation, notably the electron transport from cytochrome c to oxygen. Transcriptomic profiling of the clinical lung tissue analysis identified 14 differentially expressed genes (DEGs) related to mitochondrial function. Metabolomic analysis revealed three differential metabolites: increased 3-phenyllactic acid and ADP, and decreased citric acid in PAH samples. Mitochondria-related genes highly correlated with these metabolites included KIT, OTC, CAMK2A, and CHRNA1. Conclusions Disruption of the mitochondrial electron transport chain and citric acid cycle homeostasis likely contributes to PAH pathogenesis. 3-phenyllactic acid emerges as a potential novel diagnostic biomarker for PAH. These findings offer insights for developing novel PAH therapies and diagnostics.