A large thrombus within a giant coronary artery aneurysm in a child with Kawasaki disease: A case report.

Kawasaki disease (KD) is an acute systemic vasculitis that preferentially involves coronary arteries in young children, and predominantly affects young children. Cardiovascular lesions are the most severe complications of this disease. Even though giant aneurysms are rare, they can complicate thrombus formation, leading to myocardial ischemia, myocardial infarction, and even cardiac death. Later in life, it can lead to steno-occlusive lesions. Follow-up led to coronary artery stenosis. In this article, we report a case of a pediatric patient with KD who presented with a large thrombus within a giant coronary aneurysm as a consequence of delayed treatment with intravenous immunoglobulin (IVIG) and IVIG resistance, which contributed to the formation of coronary artery lesions. Transthoracic echocardiography is a valuable tool for detecting coronary artery abnormalities; however, computed tomography coronary angiography is valuable for precisely delineating coronary anatomy and complications. It is important to maintain a slightly higher international normalized ratio to decrease the risk of thrombosis in coronary artery aneurysms.

Neutrophil extracellular trap genes predict immunotherapy response in gastric cancer.

Background: Neutrophil extracellular trap (NET) is associated with host response, tumorigenesis, and immune dysfunction. However, the link between NET and the tumor microenvironment (TME) of gastric cancer (GC) remains unclear. Our study aims to characterize the expression patterns of NET-related genes and their relationships with clinicopathological characteristics, prognosis, TME features, and immunotherapy efficacy in GC cohorts. Methods: Transcriptomic and single-cell RNA sequencing profiles of GC with annotated clinicopathological data were obtained from TCGA-STAD (n = 415), GSE62254 (n = 300), GSE15459 (n = 192), and GSE183904 (n = 26). The consensus cluster algorithm was used to classify tumor samples into different NET-related clusters. A NET-related signature was constructed using LASSO regression and verified in four immunotherapy cohorts. ROC and Kaplan-Meier analyses were conducted to evaluate the predictive and prognostic value of the model for immunotherapy efficacy. Results: This study identified two NET-related clusters with distinct clinicopathological features, prognosis, and TME landscapes. The high NET-related cluster, characterized by increased NET-related gene expression, exhibited more aggressive behavior and a worse prognosis (HR = 1.63, P = 0.004) than the low NET-related cluster. DEGs were primarily involved in the chemokine/cytokine-associated pathways. Moreover, the high NET-related cluster had significantly higher levels of TME scores, immune infiltration, and immune effectors (all P < 0.001). The NET-related signature displayed a high predictive accuracy for immunotherapy response (AUC = 0.939, P < 0.001). Furthermore, patients with high NET-related scores consistently harbored a more favorable prognosis in different immunotherapy cohorts (all P < 0.05). Conclusions: This study identified the NET-related signature as a robust model for predicting immunotherapy response in GC, which can help clinicians make appropriate immunotherapy decisions.

Downregulation of malic enzyme 3 facilitates progression of gastric carcinoma via regulating intracellular oxidative stress and hypoxia-inducible factor-1α stabilization.

BACKGROUND: Gastric cancer (GC) is one of the most malignant cancers worldwide. Metabolism disorder is a critical characteristic of malignant tumors related to tumor progression and metastasis. However, the expression and molecular mechanism of malic enzyme 3 (ME3) in GC are rarely reported. In this study, we aim to investigate the molecular mechanism of ME3 in the development of GC and to explore its potential value as a prognostic and therapeutic target in GC. METHOD: ME3 mRNA and protein expression were evaluated in patients with GC using RT-qPCR, WB, and immunohistochemistry, as well as their correlation with clinicopathological indicators. The effect of ME3 on proliferation and metastasis was evaluated using Cell Counting Kit-8 (CCK-8), 5-ethynyl-20-deoxyuridine (EdU) assay, transwell assay, wound healing assay, and subcutaneous injection or tail vein injection of tumor cells in mice model. The effects of ME3 knockdown on the level of metabolites and hypoxia-inducible factor-1α (HIF-1α) protein were determined in GC cells. Oxidative phosphorylation was measured to evaluate adenosine triphosphate (ATP) production. RESULTS: ME3 was downregulated in human GC tissues (P < 0.001). The decreased ME3 mRNA expression was associated with younger age (P = 0.02), pathological staging (P = 0.049), and lymph node metastasis (P = 0.001), while low ME3 expression was associated with tumor size (P = 0.048), tumor invasion depth (P < 0.001), lymph node metastasis (P = 0.018), TNM staging (P < 0.001), and poor prognosis (OS, P = 0.0206; PFS P = 0.0453). ME3 knockdown promoted GC cell malignancy phenotypes. Moreover, α-ketoglutarate (α-KG) and NADPH/NADP+ ratios were reduced while malate was increased in the ME3 knockdown group under normoxia. When cells were incubated under hypoxia, the NADPH/NADP+ ratio and α-KG decreased while intracellular reactive oxygen species (ROS) increased significantly. The ME3 knockdown group exhibited an increase in ATP production and while ME3 overexpression group exhibited oppositely. We discovered that ME3 and HIF-1α expression were negatively correlated in GC cells and tissues, and proposed the hypothesis: downregulation of ME3 promotes GC progression via regulating intracellular oxidative stress and HIF-1α. CONCLUSION: We provide evidence that ME3 downregulation is associated with poor prognosis in GC patients and propose a hypothesis for the ME3 regulatory mechanism in GC progression. The present study is of great scientific significance and clinical value for exploring the prognostic and therapeutic targets of GC, evaluating and improving the clinical efficacy of patients, reducing recurrence and metastasis, and improving the prognosis and quality of life of patients.

The combination of exon sequencing and metabolomics to establish a molecular typing system for gastric cancer.

Background: Gastric cancer (GC) is one of the most common malignant tumors in the world. It has become increasingly difficult to meet the needs of precision therapy using the existing molecular typing system. Therefore, developing a more effective molecular typing system for GC is urgent. Methods: In this study, 100 Chinese GC patients were included. Whole-exome sequencing (WES) and metabolomics analysis were performed to reveal the characteristics of genomic and metabolic changes. Results: In WES, nonsynonymous mutations accounted for the majority. Based on metabolomics, GC has been divided into three subtypes with distinct metabolic features. Importantly, we ultimately divided GC into four subtypes with different metabolic characteristics, genomic alterations, and clinical prognoses by incorporating biomics analysis. Conclusions: Integrating biological features, we constructed a novel molecular system for GC that was closely related to genetics and metabolism, providing new insights for further understanding the heterogeneity and formulating precise treatment strategies.

Assessing the diagnostic value of left ventricular synchrony indices derived from phase analysis by D-SPECT in identifying obstructive coronary artery disease.

This study aimed to assess the diagnostic efficacy of left ventricular synchrony (LVS) for detecting coronary artery disease (CAD). We explored whether the LVS index derived from phase analysis of D-SPECT provides superior diagnostic value compared to conventional perfusion analysis in identifying obstructive CAD. Patients with suspected or confirmed CAD underwent drug-stress/rest gated D-SPECT myocardial perfusion imaging (MPI) and coronary angiography (CAG). A 50% stenosis was set as the threshold for obstructive CAD. 110 participants were enrolled in this analysis. There were significant differences in phase standard deviation (PSD), phase histogram bandwidth (PHB) and entropy among the four groups. Patients without cardiac disease and those with mild-moderate stenosis exhibited no noticeable contraction asynchrony. However, LVS indices demonstrated a gradual increase with the progression of coronary stenosis when compared to NC (P < 0.001). Obstructive CAD was identified in 43 out of 110 participants (39%). Optimal cutoff values for diagnosing obstructive CAD during stress were determined as 7.6° for PSD, 24° for PHB, and 37% for entropy, respectively. Notably, PSD, PHB, and entropy indices exhibited higher sensitivity compared to MPI. The integration of the stress-induced LVS indices into routine MPI analysis resulted in a significantly greater area under the curve (AUC), leading to improved diagnostic performance and enhanced differential capacity. Stress-induced LVS indices increase with the severity of coronary artery stenosis by D-SPECT phase analysis. Further, the indices-derived phase analysis exhibits superior sensitivity and discriminatory ability compared to MPI in detecting obstructive CAD.

Tumor mutational burden adjusted by neutrophil-to-lymphocyte ratio serves as a potential biomarker for atezolizumab-treated patients with extensive stage small cell lung cancer.

BACKGROUND: There is a desperate for the identification of more accurate and efficient biomarkers for ICI responses in patients with SCLC. METHODS: The data of our study was obtained from IMpower133 study. A total of 202 patients with SCLC received the treatment of placebo plus carboplatin plus etoposide (EC) while a total of 201 patients with SCLC received the treatment of atezolizumab plus EC. Overall survival (OS) was compared using Kaplan Meier analyses. Univariate and multivariate Cox regression analysis were used to determine independent prognostic variables affecting OS in patients with SCLC. RESULTS: We have demonstrated that a higher TMB adjusted by a lower neutrophil-to-lymphocyte ratio (NLR) is significantly correlated with improved OS, in patients with SCLC subject to either atezolizumab or placebo (P = 0.001 for atezolizumab and P = 0.034 for placebo). Moreover, Cox model showed that TMB < 10 mut/Mb adjusted by NLR ≥ median was an independent factor of OS for atezolizumab-treated SCLC patients (hazard ratio [HR], 2.82; 95% confidence interval; 1.52-5.24; P = 0.001). Both univariate and multivariate cox regression analysis showed that for patients with SCLC harboring low NLR and high TMB, survival is significantly longer in those treated with atezolizumab than those treated with placebo. Survival benefit is significantly higher in atezolizumab-treated patients with SCLC than those treated with placebo (P = 0.018 for TMB cutoff = 10 mut/Mb, P = 0.034 for TMB cutoff = 16 mut/Mb). CONCLUSION: Our findings provide a promising insight into the utility of NLR-adjusted TMB in the prognosis and immune responses in patients with SCLC.

High methylation of the same promoter of lncRNA ZNF582-AS1/ZNF582 promotes malignant progression of esophageal cancer.

Aim: This study aimed to investigate the functions of ZNF582-AS1 and ZNF582 in esophageal cancer (EC). Materials & methods: Bioinformatics analysis, qRT-PCR and western blot were used to analyze the expression levels. Biological functions were evaluated using cell-counting kit 8, colony formation, Transwell assays and flow cytometry. FISH was used to detect subcellular localization, and methylation-specific PCR determined gene methylation levels. Animal experiments validated the impact on tumor progression. Results: ZNF582-AS1 and ZNF582 were highly methylated and downregulated in EC. Overexpression of ZNF582-AS1 up-regulated the expression of ZNF582, thereby inhibiting EC cell viability and metastasis, promoting apoptosis and inhibiting tumor growth. Conclusion: Low expression of ZNF582-AS1/ZNF582 mediated by DNA hypermethylation facilitates the malignant progression of EC.

Promoter hypermethylation silences ZNF582-AS1 and ZNF582, driving esophageal cancer progression, which has the potential for novel therapeutic strategies. # Methylation # Esophageal Cancer.

The role of FERMT2 in the tumor microenvironment and immunotherapy in pan-cancer using comprehensive single-cell and bulk sequencing.

FERMT2 has been identified as a participant in integrin-linked kinase signaling pathways, influencing epithelial-mesenchymal transition and thereby affecting tumor initiation, progression, and invasion. While the character of FERMT2 in the tumor microenvironment (TME) as well as its implications for immunotherapy remain unclear. Thus, we conducted a comprehensive analysis to assess the prognostic significance of FERMT2 using Kaplan-Meier analysis. In addition, we employed enrichment analysis to uncover potential underlying molecular mechanisms. Using "Immunedeconv" package, we evaluated the immune characteristics of FERMT2 within TME. Furthermore, we determined the expression levels of FERMT2 in various cell types within TME, based on single-cell sequencing data. To confirm the co-expression of FERMT2 and markers of cancer-associated fibroblasts (CAFs), we performed multiplex immunofluorescence staining on tissue paraffin sections across various cancer types. Our analysis disclosed a significant correlation between elevated FERMT2 expression and unfavorable prognosis in specific cancer types. Furthermore, we identified a strong correlation between FERMT2 expression and diverse immune-related factors, including immune checkpoint molecules, immune cell infiltration, microsatellite instability (MSI), and tumor mutational burden (TMB). Additionally, there was a significant correlation between FERMT2 expression and immune-related pathways, particularly those associated with activating, migrating, and promoting the growth of fibroblasts in diverse cancer types. Interestingly, we observed consistent co-expression of FERMT2 in both malignant tumor cells and stromal cells, particularly within CAFs. Notably, our findings also indicated that FERMT2, in particular, exhibited elevated expression levels within tumor tissues and co-expressed with α-SMA in CAFs based on the multiplex immunofluorescence staining results.

Atomically dispersed Iridium on Mo2C as an efficient and stable alkaline hydrogen oxidation reaction catalyst.

Hydroxide exchange membrane fuel cells (HEMFCs) have the advantages of using cost-effective materials, but hindered by the sluggish anodic hydrogen oxidation reaction (HOR) kinetics. Here, we report an atomically dispersed Ir on Mo2C nanoparticles supported on carbon (IrSA-Mo2C/C) as highly active and stable HOR catalysts. The specific exchange current density of IrSA-Mo2C/C is 4.1 mA cm-2ECSA, which is 10 times that of Ir/C. Negligible decay is observed after 30,000-cycle accelerated stability test. Theoretical calculations suggest the high HOR activity is attributed to the unique Mo2C substrate, which makes the Ir sites with optimized H binding and also provides enhanced OH binding sites. By using a low loading (0.05 mgIr cm-2) of IrSA-Mo2C/C as anode, the fabricated HEMFC can deliver a high peak power density of 1.64 W cm-2. This work illustrates that atomically dispersed precious metal on carbides may be a promising strategy for high performance HEMFCs.

Circumventing drug resistance in gastric cancer: A spatial multi-omics exploration of chemo and immuno-therapeutic response dynamics.

BACKGROUND: Gastric Cancer (GC) characteristically exhibits heterogeneous responses to treatment, particularly in relation to immuno plus chemo therapy, necessitating a precision medicine approach. This study is centered around delineating the cellular and molecular underpinnings of drug resistance in this context. METHODS: We undertook a comprehensive multi-omics exploration of postoperative tissues from GC patients undergoing the chemo and immuno-treatment regimen. Concurrently, an image deep learning model was developed to predict treatment responsiveness. RESULTS: Our initial findings associate apical membrane cells with resistance to fluorouracil and oxaliplatin, critical constituents of the therapy. Further investigation into this cell population shed light on substantial interactions with resident macrophages, underscoring the role of intercellular communication in shaping treatment resistance. Subsequent ligand-receptor analysis unveiled specific molecular dialogues, most notably TGFB1-HSPB1 and LTF-S100A14, offering insights into potential signaling pathways implicated in resistance. Our SVM model, incorporating these multi-omics and spatial data, demonstrated significant predictive power, with AUC values of 0.93 and 0.84 in the exploration and validation cohorts respectively. Hence, our results underscore the utility of multi-omics and spatial data in modeling treatment response. CONCLUSION: Our integrative approach, amalgamating mIHC assays, feature extraction, and machine learning, successfully unraveled the complex cellular interplay underlying drug resistance. This robust predictive model may serve as a valuable tool for personalizing therapeutic strategies and enhancing treatment outcomes in gastric cancer.

Influential Metrics Estimation and Dynamic Frequency Selection Based on Two-Dimensional Mapping for JPEG-Reversible Data Hiding.

JPEG Reversible Data Hiding (RDH) is a method designed to extract hidden data from a marked image and perfectly restore the image to its original JPEG form. However, while existing RDH methods adaptively manage the visual distortion caused by embedded data, they often neglect the concurrent increase in file size. In rectifying this oversight, we have designed a new JPEG RDH scheme that addresses all influential metrics during the embedding phase and a dynamic frequency selection strategy with recoverable frequency order after data embedding. The process initiates with a pre-processing phase of blocks and the subsequent selection of frequencies. Utilizing a two-dimensional (2D) mapping strategy, we then compute the visual distortion and file size increment (FSI) for each image block by examining non-zero alternating current (AC) coefficient pairs (NZACPs) and their corresponding run lengths. Finally, we select appropriate block groups based on the influential metrics of each block group and proceed with data embedding by 2D histogram shifting (HS). Extensive experimentation demonstrates how our method's efficiently and consistently outperformed existing techniques with a superior peak signal-to-noise Ratio (PSNR) and optimized FSI.

Surgical Resection of Giant Chest Wall Chondrosarcoma Combined with Sandwich Chest Wall Reconstruction in One Case.

INTRODUCTION: Primary chest wall tumors account for 5% of all thoracic neoplasms and 1% of all primary tumors. Chondrosarcoma is a rare solid tumor, with an annual incidence of <0.5 per million people per year. It predominantly occurs in the pelvis and femur, occasionally occurs in flat bones such as the sternum and ribs, and rarely invades lung tissue. Chest wall chondrosarcomas represent only 5-15% of all chondrosarcomas. Radical surgery often leads to a large range of chest wall defects, especially when the range exceeds 6 cm × 6 cm and involves the sternum, spine, or multiple consecutive ribs. The reconstruction of the chest wall bone should be considered to restore the integrity and stability of the chest, prevent chest wall softening and abnormal breathing, and ensure the stability of respiratory circulation. Chest wall reconstruction can help restore thoracic hardness and integrity, prevent lung hernia and abnormal breathing, while also ensuring a positive aesthetic outcome. The chest wall reconstruction includes reconstruction of the pleura, bony structures, and soft tissues. CASE REPORT: In our case of an adult male, after the resection of the third and fourth anterior rib chondrosarcoma, the common anatomical plate was shaped and fixed to the stump of the third rib with screws to ensure the stability of the thorax while retaining the mobility of the thorax. After applying hernia mesh pruning, the chest wall defect was stitched to complete the pleural reconstruction of the defect area. This procedure can effectively maintain the stability of the pleural cavity, provide more effective support for the chest wall soft tissue, and promote the recovery of upper limb function and lung function. CONCLUSION: The radical surgery of giant chest wall chondrosarcoma often leads to a large range of chest wall defects. Chest wall reconstruction needs to be carried out at the same time to restore the integrity and stability of the chest wall, to avoid chest wall softening and abnormal breathing, and to ensure the stability of respiratory circulation. Using the "sandwich" method for chest wall reconstruction, in which an anatomical plate is combined with hernia mesh and muscle soft tissue, and during which pleura, bony structure, and soft tissues are reconstructed, can provide more effective support for chest wall soft tissue, effectively prevent postoperative muscle tissue collapse, avoid postoperative abnormal breathing, and promote the recovery of postoperative upper limb function and lung function. It is a very effective method for chest wall reconstruction.

MEF2D facilitates liver metastasis of gastric cancer cells through directly inducing H1X under IL-13 stimulation.

Liver metastasis is the most common metastatic occurrence in gastric cancer patients, although the precise mechanism behind it remains unclear. Through a combination of proteomics and quantitative RT-PCR, our study has revealed a significant correlation between the upregulation of myocyte enhancer factor-2D (MEF2D) and both distant metastasis and poor prognosis in gastric cancer patients. In mouse models, we observed that overexpressing or knocking down MEF2D in gastric cancer cells respectively promoted or inhibited liver metastasis. Furthermore, our research has demonstrated that MEF2D regulates the transcriptional activation of H1X by binding to the H1X promoter. This regulation leads to the upregulation of H1X, which, in turn, promotes the in vivo metastasis of gastric cancer cells along with the upregulation of the downstream gene ß-CATENIN. Additionally, we found that the expression of MEF2D and H1X at both mRNA and protein levels can be induced by the inflammatory factor IL-13, and this induction exhibits a time gradient dependence. In human gastric cancer tissues, the expression of IL13RA1, the receptor for IL-13, positively correlates with the expression of MEF2D and H1X. IL13RA1 has been identified as an intermediate receptor through which IL-13 regulates MEF2D. In conclusion, our findings suggest that MEF2D plays a crucial role in promoting liver metastasis of gastric cancer by upregulating H1X and downstream target ß-CATENIN in response to IL-13 stimulation. Targeting MEF2D could therefore be a promising therapeutic strategy for the clinical management of gastric cancer. STATEMENT OF SIGNIFICANCE: MEF2D promotes its transcriptional activation in gastric cancer cells by binding to the H1X promoter and is upregulated by IL-13-IL13RA1, thereby promoting distant metastasis of gastric cancer.

FTO-mediated autophagy inhibition promotes non-small cell lung cancer progression by reducing the stability of SESN2 mRNA.

The role of fat mass and obesity-associated protein (FTO), an N6-methyladenosine (m6A) demethylase, in non-small cell lung cancer (NSCLC) has recently received widespread attention. However the underlying mechanisms of FTO-mediated autophagy regulation in NSCLC progression remain elusive. In this study, we found that FTO was significantly upregulated in NSCLC, and downregulation of FTO suppressed the growth, invasion and migration of NSCLC cells by inducing autophagy. FTO knockdown resulted in elevated m6A levels in NSCLC cells. Methylated RNA immunoprecipitation sequencing showed that sestrin 2 (SESN2) was involved in m6A regulation during autophagy in NSCLC cells. Interestingly, m6A modifications in exon 9 of SESN2 regulated its stability. FTO deficiency promoted the binding of insulin-like growth factor 2 mRNA-binding protein 1 to SESN2 mRNA, enhancing its stability and elevating its protein expression. FTO inhibited autophagic flux by downregulating SESN2, thereby promoting the growth, invasion and migration of NSCLC cells. Besides, the mechanism by which FTO blocked SESN2-mediated autophagy activation was associated with the AMPK-mTOR signaling pathway. Taken together, these findings uncover an essential role of the FTO-autophagy-SESN2 axis in NSCLC progression.

Tuning the apparent hydrogen binding energy to achieve high-performance Ni-based hydrogen oxidation reaction catalyst.

High-performance platinum-group-metal-free alkaline hydrogen oxidation reaction catalysts are essential for the hydroxide exchange membrane fuel cells, which generally require high Pt loadings on the anode. Herein, we report a highly active hydrogen oxidation reaction catalyst, NiCuCr, indicated by the hydroxide exchange membrane fuel cell with a high peak power density of 577 mW cm-2 (18 times as high as the Ni/C anode) and a stability of more than 150 h (a degradation rate slower by 7 times than the Ni/C anode). The spectroscopies demonstrate that the alloy effect from Cu weakens the hydrogen binding, and the surface Cr2O3 species enhance the interfacial water binding. Both effects bring an optimized apparent hydrogen binding energy and thus lead to the high hydrogen oxidation reaction performance of NiCuCr. These results suggest that the apparent hydrogen binding energy determines the hydrogen oxidation reaction performance and that its tuning is beneficial toward high electrocatalytic performance.

Acid-Base Cascades in Zeotype Single Crystal for Sugar Conversion.

The chemically catalyzed production of fructose syrup from high concentrations of glucose is crucial for the food industry and biorefining. In this work, a single crystal catalyst was synthesized via protective desilication of zeolite while incorporating indium. Glucose was isomerized in methanol at concentrations as high as 33 wt % before being hydrolyzed with water. The final fructose production was 54.9 %, with 89.1 % selectivity and 93.3 % sugar recovery, the highest isomerization rate at the highest concentration ever reported. Indium was present in the single-crystal catalyst as oxide nanoparticles and boundary framework atoms, and it achieved intelligent cooperation in the production of fructose syrup in methanol by catalyzing isomerization and selective glycosidation, minimizing degradation due to fructose accumulation and eliminating side reactions. This study contributed to the advancement of the industrial practice of chemically catalyzed glucose isomerization.

Noninvasive 3D-CT simulation versus glue injection to localize small pulmonary nodules prior to anatomical segmentectomy: a randomized controlled trial.

OBJECTIVES: This study aimed to investigate whether adding glue injection to three-dimensional computed tomography bronchography and angiography (3D-CTBA) has extra benefits to facilitate anatomical segmentectomy for pulmonary nodules. METHODS: We conducted a randomized controlled trial. The patients undergoing thoracoscopic segmentectomy assisted with 3D-CTBA simulation were enrolled. Then, they were divided into the 3D-CTBA group and the glue-labelling group who received additional computed tomography-guided percutaneous glue (2-octyl cyanoacrylate) injection to label the nodules. The primary outcome was the resection rate of the nodules, and the secondary measures included the operation time, complications and thorax drainage. RESULTS: A total of 173 patients were randomized into the 3D-CTBA group (89 patients) and glue-labelling group (84 patients) between January 2018 and March 2019. Before the segmentectomy, the patients using glue labelling recorded 5 (6.0%) cases of pneumothorax, 2 (2.4%) cases of haemothorax and 1 (1.2%) case of severe chest pain. All the surgical procedure was performed fluently and safely. The resection rate of the nodules was 100% in both groups. Furthermore, these patients demonstrated similar operation time [(141.5 ± 41.9) vs (142.1 ± 38.9) min], estimated blood loss [(111.3 ± 74.0) vs (106.0 ± 63.8) ml], duration of chest tube duration [(5.1 ± 3.0) vs (5.0 ± 3.5) days] and total drainage volume [(872.3 ± 643.1) vs (826.7 ± 806.0) ml], with a P-value of >0.05 respectively. In addition, 6 (7.1%) patients in the glue-labelling group and 6 (6.7%) patients in the 3D-CTBA group reported air leakage (>5 days) and chylothorax. CONCLUSIONS: Noninvasive 3D-CTBA alone is probably sufficient to facilitate anatomical segmentectomy. The additional invasive glue labelling could be avoided in selected patients who undergo intentional segmentectomy. CLINICAL TRIAL REGISTRATION: The trial was registered under the Chinese Clinical Trial Registry (ChiCTR). Identifier: ChiCTR1800018293, https://www.chictr.org.cn/showproj.html?proj=29345.

Construction of a Diagnostic Model for Small Cell Lung Cancer Combining Metabolomics and Integrated Machine Learning.

BACKGROUND: To date, no study has systematically explored the potential role of serum metabolites and lipids in the diagnosis of small cell lung cancer (SCLC). Therefore, we aimed to conduct a case-cohort study that included 191 cases of SCLC, 91 patients with lung adenocarcinoma, 82 patients with squamous cell carcinoma, and 97 healthy controls. METHODS: Metabolomics and lipidomics were applied to analyze different metabolites and lipids in the serum of these patients. The SCLC diagnosis model (d-model) was constructed using an integrated machine learning technology and a training cohort (n = 323) and was validated in a testing cohort (n=138). RESULTS: Eight metabolites, including 1-mristoyl-sn-glycero-3-phosphocholine, 16b-hydroxyestradiol, 3-phosphoserine, cholesteryl sulfate, D-lyxose, dioctyl phthalate, DL-lactate and Leu-Phe, were successfully selected to distinguish SCLC from controls. The d-model was constructed based on these 8 metabolites and showed improved diagnostic performance for SCLC, with the area under curve (AUC) of 0.933 in the training cohort and 0.922 in the testing cohort. Importantly, the d-model still had an excellent diagnostic performance after adjusting the stage and related clinical variables and, combined with the progastrin-releasing peptide (ProGRP), showed the best diagnostic performance with 0.975 of AUC for limited-stage patients. CONCLUSION: This study is the first to analyze the difference between metabolomics and lipidomics and to construct a d-model to detect SCLC using integrated machine learning. This study may be of great significance for the screening and early diagnosis of SCLC patients.