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The development of a colorectal adenoma (CA) into carcinoma (CRC) is a long and stealthy process. There remains a lack of reliable biomarkers to distinguish CA from CRC. To effectively explore underlying molecular mechanisms and identify novel lipid biomarkers promising for early diagnosis of CRC, an ultrahigh-performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS) method was employed to comprehensively measure lipid species in human serum samples of patients with CA and CRC. Results showed significant differences in serum lipid profiles between CA and CRC groups, and 85 differential lipid species (P < 0.05 and fold change > 1.50 or < 0.67) were discovered. These significantly altered lipid species were mainly involved in fatty acid (FA), phosphatidylcholine (PC), and triacylglycerol (TAG) metabolism with the constituent ratio > 63.50%. After performance evaluation by the receiver operating characteristic (ROC) curve analysis, seven lipid species were ultimately proposed as potential biomarkers with the area under the curve (AUC) > 0.800. Of particular value, a lipid panel containing docosanamide, SM d36:0, PC 36:1e, and triheptanoin was selected as a composite candidate biomarker with excellent performance (AUC = 0.971), and the highest selected frequency to distinguish patients with CA from patients with CRC based on the support vector machine (SVM) classification model. To our knowledge, this study was the first to undertake a lipidomics profile using serum intended to identify screening lipid biomarkers to discriminate between CA and CRC. The lipid panel could potentially serve as a composite biomarker aiding the early diagnosis of CRC. Metabolic dysregulation of FAs, PCs, and TAGs seems likely involved in malignant transformation of CA, which hopefully will provide new clues to understand its underlying mechanism.

ObjectiveTo investigative the diagnostic performance of the morphological model, radiomics model, and combined model in differentiating invasive adenocarcinomas (IACs) from minimally invasive adenocarcinomas (MIAs).MethodsThis study retrospectively involved 307 patients who underwent chest computed tomography (CT) examination and presented as subsolid pulmonary nodules whose pathological findings were MIAs or IACs from January 2010 to May 2018. These patients were randomly assigned to training and validation groups in a ratio of 4:1 for 10 times. Eighteen categories of morphological features of pulmonary nodules including internal and surrounding structure were labeled. The following radiomics features are extracted: first-order features, shape-based features, gray-level co-occurrence matrix (GLCM) features, gray-level size zone matrix (GLSZM) features, gray-level run length matrix (GLRLM) features, and gray-level dependence matrix (GLDM) features. The chi-square test and F1 test selected morphology features, and LASSO selected radiomics features. Logistic regression was used to establish models. Receiver operating characteristic (ROC) curves evaluated the effectiveness, and Delong analysis compared ROC statistic difference among three models.ResultsIn validation cohorts, areas under the curve (AUC) of the morphological model, radiomics model, and combined model of distinguishing MIAs from IACs were 0.88, 0.87, and 0.89; the sensitivity (SE) was 0.68, 0.81, and 0.83; and the specificity (SP) was 0.93, 0.79, and 0.87. There was no statistically significant difference in AUC between three models (p > 0.05).ConclusionThe morphological model, radiomics model, and combined model all have a high efficiency in the differentiation between MIAs and IACs and have potential to provide non-invasive assistant information for clinical decision-making.

Precision interventional brachytherapy is a radiotherapy technique that combines radiation therapy medicine with computer network technology, physics, etc. It can solve the limitations of conventional brachytherapy. Radioactive drugs and their carriers change with each passing day, and major research institutions and enterprises worldwide have conducted extensive research on them. In addition, the capabilities of interventional robotic systems are also rapidly developing to meet clinical needs for the precise delivery of radiopharmaceuticals in interventional radiotherapy. This study reviews the main radiopharmaceuticals, drug carriers, dispensing and fixation technologies, and interventional robotic precision delivery systems used in precision brachytherapy of malignant tumors. We then discuss the current needs in the field and future development prospects in high-precision interventional brachytherapy.

Alpha beta hydrolase domain containing 5 (ABHD5) is an essential coactivator of adipose triglyceride lipase (ATGL), a rate-limiting enzyme in various cell types that promotes the hydrolysis of triacylglycerol (TG) into diacylglycerol (DG) and fatty acid (FA). It acts as a critical regulatory factor in cellular lipid metabolism. The reprogramming of lipid metabolism is one of the hallmarks of cancer, suggesting that altering lipid metabolism could become a new strategy for tumor treatment. Research has revealed a close association between ABHD5 and the development and progression of malignancies. This review summarizes the role of ABHD5 in various malignant tumors and explores the different signaling pathways and metabolic routes that may be involved, providing a comprehensive mechanistic understanding of ABHD5.

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the recent global COVID-19 outbreak, which led to a public health emergency. Entry of SARS-CoV-2 into human cells is dependent on the SARS-CoV receptor, angiotensin converting enzyme 2 (ACE2) receptor, and cathepsin. Cathepsin degrades the spike protein (S protein), which results in the entry of viral nucleic acid into the human host cell.MethodsWe explored the susceptibility of the central nervous system (CNS) to SARS-CoV-2 infection using single-cell transcriptome analysis of glioblastoma.ResultsThe results showed that ACE2 expression is relatively high in endothelial cells (ECs), bone marrow mesenchymal stem cells (BMSCs), and neural precursor cells (NPCs). Cathepsin B (Cat B) and cathepsin (Cat L) were also strongly expressed in various cell clusters within the glioblastoma microenvironment. Immunofluorescence staining of glioma and normal brain tissue chips further confirmed that ACE2 expression co-localized with CD31, CD73, and nestin, which confirmed the susceptibility to SARS-CoV-2 of nervous system cells, including ECs, BMSCs, and NPCs, from clinical specimens.ConclusionsThese findings reveal the mechanism of SARS-CoV-2 neural invasion and suggest that special attention should be paid to SARS-CoV-2–infected patients with neural symptoms, especially those who suffered a glioma.