Optimizing the image quality of peripancreatic blood vessels through the clinical application of single-energy spectral computed tomography (CT) imaging.

Background: With the increase of pancreatic tumor patients in recent years, there is an urgent need to find a way to treat pancreatic tumors. Surgery is one of the best methods for the treatment of pancreatic tumors, the success of which depends on the evaluation of peripancreatic vessels before surgery. Computed tomography (CT), as a non-invasive, fast, and economical auxiliary examination method, is undoubtedly one of the best means of clinical auxiliary examination. In this study, we investigated the impact of single-energy spectral CT imaging on the image quality of peripancreatic blood vessels and the clinical value of low-keV imaging in enhancing the image quality of peripancreatic arteriovenous vessels. Methods: We prospectively enrolled 103 patients who underwent abdominal vascular-enhanced CT examinations at the Affiliated Hospital of Hebei University between December 2022 and May 2023 and who were all scanned with the dual-energy feature on the United Imaging ATLAS scanner. The images were reconstructed at 70 keV, mixed energy, and optimized single energy in the post-processing station of United Imaging Healthcare Technology Co., Ltd. The CT value and contrast-to-noise ratio (CNR) of the superior mesenteric artery (SMA), gastroduodenal artery (GDA), inferior pancreaticoduodenal artery (IPDA), and superior mesenteric vein (SMV) were compared across energy levels, and then the image quality was subjectively evaluated. One-way analysis of variance and rank-sum tests were utilized for the statistical analysis. Results: The CT values of SMA, GDA, IPDA, and SMV in the optimal single energy group were 358.37±70.24, 323.36±88.23, 300.76±76.27, and 257.74±20.56 Hounsfield unit (HU), respectively, which were superior to those in the mixed energy (241.66±47.69, 235.17±53.71, 207.36±45.17, and 187.39±23.21 HU) and 70 keV groups (260.89±54.27, 252.41±58.87, 223.17±43.65, and 203.18±18.17 HU) (P<0.05). The diagnostic efficacy was greater in the optimal single energy group than in the other 2 groups (4.63±0.50, 3.91±0.57, and 4.23±0.83) (P<0.05). Conclusions: The optimal single energy for showing peripancreatic blood vessels is 62±7 keV when utilizing single-energy spectral CT imaging.

MX1 and UBE2L6 are potential metaflammation gene targets in both diabetes and atherosclerosis.

Background: The coexistence of diabetes mellitus (DM) and atherosclerosis (AS) is widespread, although the explicit metabolism and metabolism-associated molecular patterns (MAMPs) responsible for the correlation are still unclear. Methods: Twenty-four genetically wild-type male Ba-Ma mini pigs were randomly divided into five groups distinguished by different combinations of 90 mg/kg streptozotocin (STZ) intravenous injection and high-cholesterol/lipid (HC) or high-lipid (HL) diet feeding for 9 months in total. Pigs in the STZ+HC and STZ+HL groups were injected with STZ first and then fed the HC or HL diet for 9 months. In contrast, pigs in the HC+STZ and HL+STZ groups were fed the HC or HL diet for 9 months and injected with STZ at 3 months. The controls were only fed a regular diet for 9 months. The blood glucose and abdominal aortic plaque observed through oil red O staining were used as evaluation indicators for successful modelling of DM and AS. A microarray gene expression analysis of all subjects was performed. Results: Atherosclerotic lesions were observed only in the HC+STZ and STZ+HC groups. A total of 103 differentially expressed genes (DEGs) were identified as common between them. The most significantly enriched pathways of 103 common DEGs were influenza A, hepatitis C, and measles. The global and internal protein-protein interaction (PPI) networks of the 103 common DEGs consisted of 648 and 14 nodes, respectively. The top 10 hub proteins, namely, ISG15, IRG6, IRF7, IFIT3, MX1, UBE2L6, DDX58, IFIT2, USP18, and IFI44L, drive aspects of DM and AS. MX1 and UBE2L6 were the intersection of internal and global PPI networks. The expression of MX1 and UBE2L6 was 507.22 ± 342.56 and 96.99 ± 49.92 in the HC+STZ group, respectively, which was significantly higher than others and may be linked to the severity of hyperglycaemia-related atherosclerosis. Further PPI network analysis of calcium/micronutrients, including MX1 and UBE2L6, consisted of 58 and 18 nodes, respectively. The most significantly enriched KEGG pathways were glutathione metabolism, pyrimidine metabolism, purine metabolism, and metabolic pathways. Conclusions: The global and internal PPI network of the 103 common DEGs consisted of 648 and 14 nodes, respectively. The intersection of the nodes of internal and global PPI networks was MX1 and UBE2L6, suggesting their key role in the comorbidity mechanism of DM and AS. This inference was partly verified by the overexpression of MX1 and UBE2L6 in the HC+STZ group but not others. Further calcium- and micronutrient-related enriched KEGG pathway analysis supported that MX1 and UBE2L6 may affect the inflammatory response through micronutrient metabolic pathways, conceptually named metaflammation. Collectively, MX1 and UBE2L6 may be potential common biomarkers for DM and AS that may reveal metaflammatory aspects of the pathological process, although proper validation is still needed to determine their contribution to the detailed mechanism.

Nanoconstruction on Living Cell Surfaces with Cucurbit[7]uril-Based Supramolecular Polymer Chemistry: Toward Cell-Based Delivery of Bio-Orthogonal Catalytic Systems.

Employing living cells as carriers to transport transition metal-based catalysts for target-specific bio-orthogonal catalysis represents a cutting-edge approach in advancing precision biomedical applications. One of the initial hurdles in this endeavor involves effectively attaching the catalysts to the carrier cells while preserving the cells' innate ability to interact with biological systems and maintaining the unaltered catalytic activity. In this study, we have developed an innovative layer-by-layer method that leverages a noncovalent interaction between cucurbit[7]uril and adamantane as the primary driving force for crafting polymeric nanostructures on the surfaces of these carrier cells. The strong binding affinity between the host-guest pair ensures the creation of a durable polymer coating on the cell surfaces. Meanwhile, the layer-by-layer process offers high adaptability, facilitating the efficient loading of bio-orthogonal catalysts onto cell surfaces. Importantly, the polymeric coating shows no discernible impact on the cells' physiological characteristics, including their tropism, migration, and differentiation, while preserving the effectiveness of the bio-orthogonal catalysts.

Exploring the supramolecular chemistry of cyclopropeniums: halogen-bonding-induced electrostatic assembly of polymers.

Exploring new noncovalent synthons for supramolecular assembly is essential for material innovation. Accordingly, we herein report a unique type of cyclopropenium-based supramolecular motif and demonstrate its applications to polymer self-assembly. Because of the "ion pair strain" effect, trisaminocyclopropenium iodides complex strongly with fluoroiodobenzene derivatives, forming stable adducts. Crystal structure analysis reveals that halogen-bonding between the iodide anion and the iodo substituent of the fluoroiodobenzene is the driving force for the formation of these electrostatically complexed adducts. Such halogen-bonding-induced electrostatic interactions were further successfully applied to drive the assembly of polymers in solution, on surfaces, and in bulk, demonstrating their potential for constructing supramolecular polymeric materials.

Engineering living cells with cucurbit[7]uril-based supramolecular polymer chemistry: from cell surface engineering to manipulation of subcellular organelles.

Supramolecular polymer chemistry, which closely integrates noncovalent interactions with polymeric structures, is a promising toolbox for living cell engineering. Here, we report our recent progress in exploring the applications of cucurbit[7]uril (CB[7])-based supramolecular polymer chemistry for engineering living cells. First, a modular polymer-analogous approach was established to prepare multifunctional polymers that contain CB[7]-based supramolecular recognition motifs. The supramolecular polymeric systems were successfully applied to cell surface engineering and subcellular organelle manipulation. By anchoring polymers on the cell membranes, cell-cell interactions were established by CB[7]-based host-guest recognition, which further facilitated heterogeneous cell fusion. In addition to cell surface engineering, placing the multifunctional polymers on specific subcellular organelles, including the mitochondria and endoplasmic reticulum, has led to enhanced physical contact between subcellular organelles. It is highly anticipated that the CB[7]-based supramolecular polymer chemistry will provide a new strategy for living cell engineering to advance the development of cell-based therapeutic materials.

Prediction of early recurrence of hepatocellular carcinoma after liver transplantation based on computed tomography radiomics nomogram.

BACKGROUND: Early recurrence results in poor prognosis of patients with hepatocellular carcinoma (HCC) after liver transplantation (LT). This study aimed to explore the value of computed tomography (CT)-based radiomics nomogram in predicting early recurrence of patients with HCC after LT. METHODS: A cohort of 151 patients with HCC who underwent LT between December 2013 and July 2019 were retrospectively enrolled. A total of 1218 features were extracted from enhanced CT images. The least absolute shrinkage and selection operator algorithm (LASSO) logistic regression was used for dimension reduction and radiomics signature building. The clinical model was constructed after the analysis of clinical factors, and the nomogram was constructed by introducing the radiomics signature into the clinical model. The predictive performance and clinical usefulness of the three models were evaluated using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA), respectively. Calibration curves were plotted to assess the calibration of the nomogram. RESULTS: There were significant differences in radiomics signature among early recurrence patients and non-early recurrence patients in the training cohort (P < 0.001) and validation cohort (P < 0.001). The nomogram showed the best predictive performance, with the largest area under the ROC curve in the training (0.882) and validation (0.917) cohorts. Hosmer-Lemeshow testing confirmed that the nomogram showed good calibration in the training (P = 0.138) and validation (P = 0.396) cohorts. DCA showed if the threshold probability is within 0.06-1, the nomogram had better clinical usefulness than the clinical model. CONCLUSIONS: Our CT-based radiomics nomogram can preoperatively predict the risk of early recurrence in patients with HCC after LT.