Metformin Suppresses Both PD-L1 Expression in Cancer Cells and Cancer-Induced PD-1 Expression in Immune Cells to Promote Antitumor Immunity.

Background: Metformin, a drug prescribed for patients with type 2 diabetes, has potential efficacy in enhancing antitumor immunity; however, the detailed underlying mechanisms remain to be elucidated. Therefore, we aimed to identify the inhibitory molecular mechanisms of metformin on programmed death ligand 1 (PD-L1) expression in cancer cells and programmed death 1 (PD-1) expression in immune cells. Methods: We employed a luciferase reporter assay, quantitative real-time PCR, immunoblotting analysis, immunoprecipitation and ubiquitylation assays, and a natural killer (NK) cell-mediated tumor cell cytotoxicity assay. A mouse xenograft tumor model was used to evaluate the effect of metformin on tumor growth, followed by flow-cytometric analysis using tumor-derived single-cell suspensions. Results: Metformin decreased AKT-mediated ß-catenin S552 phosphorylation and subsequent ß-catenin transactivation in an adenosine monophosphate-activated protein kinase (AMPK) activation-dependent manner, resulting in reduced CD274 (encoding PD-L1) transcription in cancer cells. Tumor-derived soluble factors enhanced PD-1 protein stability in NK and T cells via dissociation of PD-1 from ubiquitin E3 ligases and reducing PD-1 polyubiquitylation. Metformin inhibited the tumor-derived soluble factor-reduced binding of PD-1 to E3 ligases and PD-1 polyubiquitylation, resulting in PD-1 protein downregulation in an AMPK activation-dependent manner. These inhibitory effects of metformin on both PD-L1 and PD-1 expression ameliorated cancer-reduced cytotoxic activity of immune cells in vitro and decreased tumor immune evasion and growth in vivo. Conclusions: Metformin blocks both PD-L1 and PD-1 within the tumor microenvironment. This study provided a mechanistic insight into the efficacy of metformin in improving immunotherapy in human cancer.

Reliability of Artificial Intelligence-based Cone Beam Computed Tomography Integration with Digital Dental Images.

This study aimed to introduce cone-beam computed tomography (CBCT) digitization and integration of digital dental images (DDI) based on artificial intelligence (AI)-based registration (ABR) and to evaluate the reliability and reproducibility using this method compared with those of surface-based registration (SBR). This retrospective study consisted of CBCT images and DDI of 17 patients who had undergone computer-aided bimaxillary orthognathic surgery. The digitization of CBCT images and their integration with DDI were repeated using an AI-based program. CBCT images and DDI were integrated using a point-to-point registration. In contrast, with the SBR method, the three landmarks were identified manually on the CBCT and DDI, which were integrated with the iterative closest points method. After two repeated integrations of each method, the three-dimensional coordinate values of the first maxillary molars and central incisors and their differences were obtained. Intraclass coefficient (ICC) testing was performed to evaluate intra-observer reliability with each method's coordinates and compare their reliability between the ABR and SBR. The intra-observer reliability showed significant and almost perfect ICC in each method. There was no significance in the mean difference between the first and second registrations in each ABR and SBR and between both methods; however, their ranges were narrower with ABR than with the SBR method. This study shows that AI-based digitization and integration are reliable and reproducible.

Cerebrospinal Fluid-philic and Biocompatibility-Enhanced Soft Cranial Window for Long-Term In Vivo Brain Imaging.

Soft, transparent poly(dimethyl siloxane) (PDMS)-based cranial windows in animal models have created many opportunities to investigate brain functions with multiple in vivo imaging modalities. However, due to the hydrophobic nature of PDMS, the wettability by cerebrospinal fluid (CSF) is poor, which may cause air bubble trapping beneath the window during implantation surgery, and favorable heterogeneous bubble nucleation at the interface between hydrophobic PDMS and CSF. This may result in excessive growth of the entrapped bubble under the soft cranial window. Herein, to yield biocompatibility-enhanced, trapped bubble-minimized, and soft cranial windows, this report introduces a CSF-philic PDMS window coated with hydroxyl-enriched poly(vinyl alcohol) (PVA) for long-term in vivo imaging. The PVA-coated PDMS (PVA/PDMS) film exhibits a low contact angle θACA (33.7 ± 1.9°) with artificial CSF solution and maintains sustained CSF-philicity. The presence of the PVA layer achieves air bubble-free implantation of the soft cranial window, as well as induces the formation of a thin wetting film that shows anti-biofouling performance through abundant water molecules on the surface, leading to long-term optical clarity. In vivo studies on the mice cortex verify that the soft and CSF-philic features of the PVA/PDMS film provide minimal damage to neuronal tissues and attenuate immune response. These advantages of the PVA/PDMS window are strongly correlated with the enhancement of cortical hemodynamic changes and the local field potential recorded through the PVA/PDMS film, respectively. This collection of results demonstrates the potential for future microfluidic platforms for minimally invasive CSF extraction utilizing a CSF-philic fluidic passage.

Effect of Aluminum Flakes on Mechanical and Optical Properties of Foam Injection Molded Parts.

Injection research using aluminum flakes has been conducted to realize metallic textures on the surface of plastic products. Several studies have focused on the effect of the orientation and quality of the flakes when using conventional injection molding methods; however, limited studies have focused on the foam injection molding method. In this study, we examined the orientation of aluminum flakes through foam injection with an inert gas and observed the changes in texture using a spectrophotometer and a gloss meter. The mechanical properties were also studied because the rigidity of the product, which is affected by the weight reduction that occurs during foaming, is an important factor. The results demonstrate that under foam injection molding, reflectance and gloss increased by 6% and 7 GU, respectively, compared to those obtained using conventional injection molding; furthermore, impact strength and flexural modulus increased by 62% and 15%, respectively. The results of this research can be applied to incorporate esthetic improvements to products and to develop functional parts.

Mechanical Properties of Biocomposites Using Polypropylene and Sesame Oil Cake.

Sesame oil cakes (SOC) produced during sesame oil production can be classified as plant residues. This study aims to use SOC as a composite material for injection molding. A biocomposite containing polypropylene (PP) and SOC, namely PP/SOC, was developed and its mechanical properties were evaluated. PP/SOC is largely divided into Homo-PP/SOC (HPS) based on Homo-PP and Block-PP/SOC (BPS) based on block-PP. The specimens containing 0-50 wt% SOC were prepared through extrusion and injection molding. As a result of the evaluation, SOC acted as a reinforcement in the matrix, and HPS and BPS showed improved flexural modulus by 36.4% and 37.3% compared to the neat PP, respectively. Tensile strength, on the other hand, decreased by 58% and 55.1%, respectively. To analyze the cause of this, cross-section observation was conducted through scanning electron microscope (SEM), and phase separation and voids were confirmed to be the cause of this. Impact strength of PP/SOC tended to vary depending on the type of matrix. HPS increased by 30.9% compared to neat PP, and BPS decreased by 25%. This tendency difference appears to be the result of SOC inhibiting crystallization of PP, and it has been confirmed through x ray diffraction (XRD) and differential scanning calorimetry (DSC) analysis. Moreover, PP/SOC can be manufactured at a low cost and is environmentally friendly because it utilizes SOC, a plant residue. It can also be applied to commercial products, such as food packaging, owing to its good moldability and improved mechanical properties.

Intratumoral Spatial Heterogeneity at Perfusion MR Imaging Predicts Recurrence-free Survival in Locally Advanced Breast Cancer Treated with Neoadjuvant Chemotherapy.

Purpose To characterize intratumoral spatial heterogeneity at perfusion magnetic resonance (MR) imaging and investigate intratumoral heterogeneity as a predictor of recurrence-free survival (RFS) in breast cancer. Materials and Methods In this retrospective study, a discovery cohort (n = 60) and a multicenter validation cohort (n = 186) were analyzed. Each tumor was divided into multiple spatially segregated, phenotypically consistent subregions on the basis of perfusion MR imaging parameters. The authors first defined a multiregional spatial interaction (MSI) matrix and then, based on this matrix, calculated 22 image features. A network strategy was used to integrate all image features and classify patients into different risk groups. The prognostic value of imaging-based stratification was evaluated in relation to clinical-pathologic factors with multivariable Cox regression. Results Three intratumoral subregions with high, intermediate, and low MR perfusion were identified and showed high consistency between the two cohorts. Patients in both cohorts were stratified according to network analysis of multiregional image features regarding RFS (log-rank test, P = .002 for both). Aggressive tumors were associated with a larger volume of the poorly perfused subregion as well as interaction between poorly and moderately perfused subregions and surrounding parenchyma. At multivariable analysis, the proposed MSI-based marker was independently associated with RFS (hazard ratio: 3.42; 95% confidence interval: 1.55, 7.57; P = .002) adjusting for age, estrogen receptor (ER) status, progesterone receptor status, human epidermal growth factor receptor type 2 (HER2) status, tumor volume, and pathologic complete response (pCR). Furthermore, imaging helped stratify patients for RFS within the ER-positive and HER2-positive subgroups (log-rank test, P = .007 and .004) and among patients without pCR after neoadjuvant chemotherapy (log-rank test, P = .003). Conclusion Breast cancer consists of multiple spatially distinct subregions. Imaging heterogeneity is an independent prognostic factor beyond traditional risk predictors.

A Quantitative CT Imaging Signature Predicts Survival and Complements Established Prognosticators in Stage I Non-Small Cell Lung Cancer.

PURPOSE: Prognostic biomarkers are needed to guide the management of early-stage non-small cell lung cancer (NSCLC). This work aims to develop an image-based prognostic signature and assess its complementary value to existing biomarkers. METHODS AND MATERIALS: We retrospectively analyzed data of stage I NSCLC in 8 cohorts. On the basis of an analysis of 39 computed tomography (CT) features characterizing tumor and its relation to neighboring pleura, we developed a prognostic signature in an institutional cohort (n = 117) and tested it in an external cohort (n = 88). A third cohort of 89 patients with CT and gene expression data was used to create a surrogate genomic signature of the imaging signature. We conducted further validation using data from 5 gene expression cohorts (n = 639) and built a composite signature by integrating with the cell-cycle progression (CCP) score and clinical variables. RESULTS: An imaging signature consisting of a pleural contact index and normalized inverse difference was significantly associated with overall survival in both imaging cohorts (P = .0005 and P = .0009). Functional enrichment analysis revealed that genes highly correlated with the imaging signature were related to immune response, such as lymphocyte activation and chemotaxis (false discovery rate < 0.05). A genomic surrogate of the imaging signature remained a significant predictor of survival when we adjusted for known prognostic factors (hazard ratio, 1.81; 95% confidence interval, 1.34-2.44; P < .0001) and stratified patients within subgroups as defined by stage, histology, or CCP score. A composite signature outperformed the genomic surrogate, CCP score, and clinical model alone (P < .01) regarding concordance index (0.70 vs 0.62-0.63). CONCLUSIONS: The proposed CT imaging signature reflects fundamental biological differences in tumors and predicts overall survival in patients with stage I NSCLC. When combined with established prognosticators, the imaging signature improves survival prediction.

Prognostic value and molecular correlates of a CT image-based quantitative pleural contact index in early stage NSCLC.

PURPOSE: To evaluate the prognostic value and molecular basis of a CT-derived pleural contact index (PCI) in early stage non-small cell lung cancer (NSCLC). EXPERIMENTAL DESIGN: We retrospectively analysed seven NSCLC cohorts. A quantitative PCI was defined on CT as the length of tumour-pleura interface normalised by tumour diameter. We evaluated the prognostic value of PCI in a discovery cohort (n = 117) and tested in an external cohort (n = 88) of stage I NSCLC. Additionally, we identified the molecular correlates and built a gene expression-based surrogate of PCI using another cohort of 89 patients. To further evaluate the prognostic relevance, we used four datasets totalling 775 stage I patients with publically available gene expression data and linked survival information. RESULTS: At a cutoff of 0.8, PCI stratified patients for overall survival in both imaging cohorts (log-rank p = 0.0076, 0.0304). Extracellular matrix (ECM) remodelling was enriched among genes associated with PCI (p = 0.0003). The genomic surrogate of PCI remained an independent predictor of overall survival in the gene expression cohorts (hazard ratio: 1.46, p = 0.0007) adjusting for age, gender, and tumour stage. CONCLUSIONS: CT-derived pleural contact index is associated with ECM remodelling and may serve as a noninvasive prognostic marker in early stage NSCLC. KEY POINTS: • A quantitative pleural contact index (PCI) predicts survival in early stage NSCLC. • PCI is associated with extracellular matrix organisation and collagen catabolic process. • A multi-gene surrogate of PCI is an independent predictor of survival. • PCI can be used to noninvasively identify patients with poor prognosis.