Imaging features and deep learning for prediction of pulmonary epithelioid hemangioendothelioma in CT images.

Background: Pulmonary epithelioid hemangioendothelioma (PEH) is a rare vascular tumour, and its early diagnosis remains challenging. This study aims to comprehensively analyse the imaging features of PEH and develop a model for predicting PEH. Methods: Retrospective and pooled analyses of imaging findings were performed in PEH patients at our center (n=25) and in published cases (n=71), respectively. Relevant computed tomography (CT) images were extracted and used to build a deep learning model for PEH identification and differentiation from other diseases. Results: In this study, bilateral multiple nodules/masses (n=19) appeared to be more common with most nodules less than 2 cm. In addition to the common types and features, the pattern of mixed type (n=4) and isolated nodules (n=4), punctate calcifications (5/25) and lymph node enlargement were also observed (10/25). The presence of pleural effusion is associated with a poor prognosis in PEH. The deep learning model, with an area under the receiver operating characteristic curve (AUC) of 0.71 [95% confidence interval (CI): 0.69-0.72], has a differentiation accuracy of 100% and 74% for the training and test sets respectively. Conclusions: This study confirmed the heterogeneity of the imaging findings in PEH and showed several previously undescribed types and features. The current deep learning model based on CT has potential for clinical application and needs to be further explored in the future.

Causal role of lipid metabolism in pulmonary alveolar proteinosis: an observational and mendelian randomisation study.

BACKGROUND: Pulmonary alveolar proteinosis (PAP) is a rare interstitial lung disease characterised by the accumulation of lipoprotein material in the alveoli. Although dyslipidaemia is a prominet feature, the causal effect of lipid traits on PAP remains unclear. This study aimed to explore the role of lipid traits in PAP and evaluate the potential of lipid-lowering drug targets in PAP. METHODS: Clinical outcomes, lipid profiles and lung function tests were analysed in a clinical cohort of diagnosed PAP patients and propensity score-matched healthy controls. Genome-wide association study data on PAP, lipid metabolism, blood cells and variants of genes encoding potential lipid-lowering drug targets were obtained for Mendelian randomisation (MR) and mediation analyses. FINDINGS: Observational results showed that higher levels of total cholesterol (TC), triglycerides and low-density lipoprotein (LDL) were associated with increased risks of PAP. Higher levels of TC and LDL were also associated with worse PAP severity. In MR analysis, elevated LDL was associated with an increased risk of PAP (OR: 4.32, 95% CI: 1.63 to 11.61, p=0.018). Elevated monocytes were associated with a lower risk of PAP (OR 0.34, 95% CI: 0.18 to 0.66, p=0.002) and mediated the risk impact of LDL on PAP. Genetic mimicry of PCSK9 inhibition was associated with a reduced risk of PAP (OR 0.03, p=0.007). INTERPRETATION: Our results support the crucial role of lipid and metabolism-related traits in PAP risk, emphasising the monocyte-mediated, causal effect of elevated LDL in PAP genetics. PCSK9 mediates the development of PAP by raising LDL. These finding provide evidence for lipid-related mechanisms and promising lipid-lowering drug target for PAP.

Interplay of chronic obstructive pulmonary disease and colorectal cancer development: unravelling the mediating role of fatty acids through a comprehensive multi-omics analysis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) patients often exhibit gastrointestinal symptoms, A potential association between COPD and Colorectal Cancer (CRC) has been indicated, warranting further examination. METHODS: In this study, we collected COPD and CRC data from the National Health and Nutrition Examination Survey, genome-wide association studies, and RNA sequence for a comprehensive analysis. We used weighted logistic regression to explore the association between COPD and CRC incidence risk. Mendelian randomization analysis was performed to assess the causal relationship between COPD and CRC, and cross-phenotype meta-analysis was conducted to pinpoint crucial loci. Multivariable mendelian randomization was used to uncover mediating factors connecting the two diseases. Our results were validated using both NHANES and GEO databases. RESULTS: In our analysis of the NHANES dataset, we identified COPD as a significant contributing factor to CRC development. MR analysis revealed that COPD increased the risk of CRC onset and progression (OR: 1.16, 95% CI 1.01-1.36). Cross-phenotype meta-analysis identified four critical genes associated with both CRC and COPD. Multivariable Mendelian randomization suggested body fat percentage, omega-3, omega-6, and the omega-3 to omega-6 ratio as potential mediating factors for both diseases, a finding consistent with the NHANES dataset. Further, the interrelation between fatty acid-related modules in COPD and CRC was demonstrated via weighted gene co-expression network analysis and Kyoto Encyclopedia of Genes and Genomes enrichment results using RNA expression data. CONCLUSIONS: This study provides novel insights into the interplay between COPD and CRC, highlighting the potential impact of COPD on the development of CRC. The identification of shared genes and mediating factors related to fatty acid metabolism deepens our understanding of the underlying mechanisms connecting these two diseases.

Temporal trend in burden of asthma in China, South Korea, and Japan, 1990-2019: results from the Global Burden of Disease Study 2019.

Background: Asthma is a public health problem worldwide. However, only a few studies have reported the epidemiology of asthma in various age groups in East Asia. The present study aimed to analyze and predict trends in the incidence of asthma in East Asia through the Global Burden of Disease 2019 (GBD 2019) study and provide information for prevention and control strategies. Methods: The estimates of incidence, deaths, disability-adjusted life years (DALYs), and risk factors of asthma in China, South Korea, Japan, and the world from 1990-2019 were retrieved from the GBD 2019 study. The age-standardized rates (ASRs) and the average annual percentage changes (AAPCs) assessed the incidence, deaths, and DALYs of asthma, and the projection was assessed by applying the age-period-cohort model. Results: The burden of asthma in South Korea and Japan was slightly higher than in China and slightly lower than that worldwide. The age-standardized incidence rate (ASIR) of asthma in China decreased slightly from 394.58/100,000 in 1990 to 355.33/100,000 in 2019 (with an AAPC of -0.59), while the age-standardized death rate (ASDR) and the age-standardized DALY rate (ASDALR) decreased significantly (with a AAPCs of -5.22 and -2.89, respectively), which were lower than those in South Korea and Japan. Moreover, males in China, South Korea, and Japan were significantly more affected by tobacco and environmental/occupational factors than females, while the proportion of metabolic factors in females was higher than that in males. The prediction for the burden of asthma in the three East Asian countries continued to decline or stabilize until 2030, especially in China and Japan. Conclusions: Although the overall asthma burden has a downward trend according to GBD 2019, it is still heavy in East Asia, especially South Korea. In addition, increased concern and control measures are needed for the disease burden in elderly patients.

Prediction of distant metastasis and survival prediction of gastric cancer patients with metastasis to the liver, lung, bone, and brain: research based on the SEER database.

BACKGROUND: Gastric cancer (GC) is a globally important disease. It is the 5th most common malignancy and the 4th most common cause of death from cancer in the world. Patients with GC are often at an advanced stage when they are first diagnosed, and their overall prognosis is poor due to locally advanced and distant metastasis. This study sought to establish a predictive model of GC distant metastasis and survival that can be used to guide individualized treatment. METHODS: Patients diagnosed with GC from the Surveillance, Epidemiology, and End Results database were enrolled in the study. Univariate and multivariate logistic regression analyses were used to identify risk and prognostic factors for GC patients with distant metastasis. The factors were then used to construct nomograms to predict the probability of distant metastasis and the survival time of GC patients. Receiver operating characteristic (ROC) curve and decision curve analyses were used to verify the prediction ability of the nomograms. RESULTS: We established a comprehensive nomogram to predict the survival time of GC patients and 4 nomograms to predict distant metastasis. Nomograms could help oncologists to formulate treatment strategies and provide hospice care under an overall management model. CONCLUSIONS: Establishing a prediction model for distant metastasis and the survival of GC patients is of great clinical significance. The prediction of distant metastasis could help clinicians to make individualized assessments of patients and formulate individualized examination measures. Survival prediction models could help oncologists to formulate good treatment strategies and provide hospice care.

Prognostic value of nicotinamide adenine dinucleotide (NAD+) metabolic genes in patients with stomach adenocarcinoma based on bioinformatics analysis.

Background: Because stomach adenocarcinoma (STAD) has a poor prognosis, it is necessary to explore new prognostic genes to stratify patients to guide existing individualized treatments. Methods: Survival and clinical information, RNA-seq data and mutation data of STAD were acquired from The Cancer Genome Atlas (TCGA) database. Fifty-one nicotinamide adenine dinucleotide (NAD+) metabolism-related genes (NMRGs) were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases. Differentially expressed NMRGs (DE-NMRGs) between STAD and normal samples were screened, and consistent clustering analysis of STAD patients was performed based on the DE-NMRGs. Survival analysis, Gene Set Enrichment Analysis (GSEA), mutation frequency analysis, immune microenvironment analysis and drug prediction were performed among different clusters. Additionally, the differentially expressed genes (DEGs) among different clusters were selected, and the intersections of DEGs and DE-NMRGs were selected as the prognostic genes. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was performed on a human gastric mucosa epithelial cell line and cancer cell line to verify the expression of the prognostic genes. Results: A total of 27 DE-NMRGs and two clusters were selected. There was a difference in survival between clusters 1 and 2. Furthermore, 18 DE-NMRGs were significantly different between clusters 1 and 2. The different Gene Ontology (GO) biological processes and KEGG pathways between clusters 1 and 2 were mainly enriched in cyclic nucleotide mediated signaling, synaptic signaling and hedgehog signaling pathway, etc. The somatic mutation frequencies were different between the two clusters, and TTN was the highest mutated gene in the patients of the clusters 1 and 2. Additionally, eight immune cells, immune score, stromal score, and estimate score were different between clusters 1 and 2. The patients in cluster 2 were sensitive to CTLA4 inhibitor treatment. Furthermore, the top five drugs (AP.24534, BX.795, Midostaurin, WO2009093927 and CCT007093) were significantly higher in cluster 1 than in cluster 2. Finally, three genes (AOX1, NNMT and PTGIS) were acquired as prognostic, and their expressions were consistent with the results of bioinformatics analysis. Conclusions: Three prognostic genes related to NAD+ metabolism in STAD were screened out, which provides a theoretical basis and reference value for future treatment and prognosis of STAD.

The establishment of a hub differential gene model to predict prognosis in stage II and III right- and left-sided colon cancer patients.

BACKGROUND: It is now recognized that the symptoms of colon cancer differ according to whether the tumor is located on the left or right side of the patient. The results of the present study point to the differences in the tissue and embryonic origins of left- and right-sided colon cancer that cause the variations in molecular typing. The research purpose of this study is to establish a core differential gene scoring model and proved its effect. METHODS: We downloaded transcriptome data and clinical information from The Cancer Genome Atlas (TCGA). A total of 243 patients in stages II and III were grouped according to the colon cancer site. Then we screened for differential transcriptome products. The corresponding differential gene were performing a corresponding protein interaction analysis. We used 12 algorithms in Cytoscape to calculate the hub genes and a total of 37 hub genes were obtained finally. We extracted the first principal component value (PC1) of the hub genes to evaluate the effectiveness of screening. Cox regression analysis was performed for the differential genes. Finally, we performed a prognostic analysis on right-sided colon cancer patients using the BST2 gene, PC1 and relevant clinical information. RESULTS: After screening for differentially expressed genes, 37 hub genes were obtained with appropriate algorithms. PC1 showed differences in hub genes between left- and right-sided colon cancer patients. BST2 and 31 other genes were identified as significant by Cox regression analysis and were significantly mutated in patients with right-sided colon cancer. Finally, we selected the BST2 gene and relevant clinical information as the prognostic factors to build a scoring model. The prediction effect of the model was satisfied. CONCLUSIONS: We constructed a prognostic model based on BST2, PC1, and other relevant clinical information and proved its good effect.

Systemic treatment with resveratrol alleviates adjuvant arthritis-interstitial lung disease in rats via modulation of JAK/STAT/RANKL signaling pathway.

Interstitial lung disease (ILD) is the most common pulmonary manifestation of Rheumatoid arthritis (RA) lung disease. The mechanism of RA-ILD remains obscure and more effective treatments are still needed. Resveratrol (RSV) a phytoalexin found with anti-inflammation and antioxidant activity. RSV has been reported to protect against RA. In current study, we evaluated the effects of RSV on RA-ILD and further explored the underlying mechanisms. We established the RA-ILD rat model by injecting Freund's complete adjuvant (FCA). After administration of RSV into RA-ILD rats, the disease parameters were assessed, inflammatory cytokines productions were analyzed, and the effects of RSV on JAK/STAT/RANKL were evaluated. Injection of FCA caused RA-ILD in rats, which had clear lung damage, fibrosis, and elevated pro-inflammatory cytokines in both serum and lung. RSV treatment significantly ameliorated the lung disease and prevented pro-inflammatory cytokines production. In addition, RSV inhibited JAK/STAT/RANKL signaling pathway in RA-ILD rats. RSV treatment alleviates RA-ILD in rats by inhibiting JAK/STAT/RANKL signaling pathway.