Aldehyde dehydrogenase 2 family member repression promotes colorectal cancer progression by JNK/p38 MAPK pathways-mediated apoptosis and DNA damage.

BACKGROUND: Aldehyde (ALDH2) dysfunction has been verified to contribute to human cancers. AIM: To investigate the molecular mechanism and biological function of ALDH2 in colorectal cancer (CRC) progression. METHODS: Human CRC cells with high expression of ALDH2 were screened. After shRNA ALDH2 (sh-ALDH2) transfection, phenotypes [proliferation, apoptosis, acetaldehyde (ACE) accumulation, DNA damage] of CRC cells were verified using cell counting kit-8, flow cytometry, ACE assay, and comet assays. Western blotting was used for evaluation of the apoptosis proteins (Bax and Bcl-2) and JNK/p38 MAPK pathway-associated proteins. We subjected CVT-10216 (a selective ALDH2 inhibitor) to nude mice for establishment of SK-CO-1 mouse xenograft model and observed the occurrence of CRC. RESULTS: The inhibition of ALDH2 could promote the malignant structures of CRC cells, including apoptosis, ACE level, and DNA damage, and cell proliferation was decreased in the sh-ALDH2 group, whereas ALDH2 agonist Alda-1 reversed features. ALDH2 repression can cause ACE accumulation, whereas ACE enhanced CRC cell features related to increased DNA damage. Additionally, ALDH2 repression led to JNK/P38 MAPK activation, and apoptosis, ACE accumulation, and DNA damage were inhibited after p38 MAPK inhibitor SB203580 and JNK inhibitor SP600125 addition. ACE accumulation and raised DNA damage were recognized in CVT-10216 treated-mouse tumor tissues in vivo. CONCLUSION: The repression of ALDH2 led to ACE accumulation, inducing cell apoptosis and DNA damage by the JNK/p38 MAPK signaling pathway activation in CRC.

PPIA dictates NRF2 stability to promote lung cancer progression.

Nuclear factor erythroid 2-related factor 2 (NRF2) hyperactivation has been established as an oncogenic driver in a variety of human cancers, including non-small cell lung cancer (NSCLC). However, despite massive efforts, no specific therapy is currently available to target NRF2 hyperactivation. Here, we identify peptidylprolyl isomerase A (PPIA) is required for NRF2 protein stability. Ablation of PPIA promotes NRF2 protein degradation and blocks NRF2-driven growth in NSCLC cells. Mechanistically, PPIA physically binds to NRF2 and blocks the access of ubiquitin/Kelch Like ECH Associated Protein 1 (KEAP1) to NRF2, thus preventing ubiquitin-mediated degradation. Our X-ray co-crystal structure reveals that PPIA directly interacts with a NRF2 interdomain linker via a trans-proline 174-harboring hydrophobic sequence. We further demonstrate that an FDA-approved drug, cyclosporin A (CsA), impairs the interaction of NRF2 with PPIA, inducing NRF2 ubiquitination and degradation. Interestingly, CsA interrupts glutamine metabolism mediated by the NRF2/KLF5/SLC1A5 pathway, consequently suppressing the growth of NRF2-hyperactivated NSCLC cells. CsA and a glutaminase inhibitor combination therapy significantly retard tumor progression in NSCLC patient-derived xenograft (PDX) models with NRF2 hyperactivation. Our study demonstrates that targeting NRF2 protein stability is an actionable therapeutic approach to treat NRF2-hyperactivated NSCLC.

Clinical evaluation of maxillary sinus floor elevation with or without bone grafts: a systematic review and meta-analysis of randomised controlled trials with trial sequential analysis.

Introduction: Our goal was to systematically review the current evidence comparing the relative effectiveness of two maxillary sinus floor elevation (MSFE) approaches (internal and external) without bone grafts with that of conventional/grafted MSFE in patients undergoing implantation in the posterior maxilla. Material and methods: Medical databases (PubMed/Medline, Embase, Web of Science, and Cochrane Library) were searched for randomised controlled trials published between January 1980 and May 2023. A manual search of implant-related journals was also performed. Studies published in English that reported the clinical outcomes of MSFE with or without bone material were included. The risk of bias was assessed using the Cochrane Handbook Risk Assessment Tool. Meta-analyses and trial sequence analyses were performed on the included trials. Meta-regression analysis was performed using pre-selected covariates to account for substantial heterogeneity. The certainty of evidence for clinical outcomes was assessed using GRADEpro GDT online (Guideline Development Tool). Results: Seventeen studies, including 547 sinuses and 696 implants, were pooled for the meta-analysis. The meta-analysis showed no statistically significant difference between MSFE without bone grafts and conventional MSFE in terms of the implant survival rate in the short term (n = 11, I2 = 0%, risk difference (RD): 0.03, 95% confidence intervals (CI): -0.01-0.07, p = 0.17, required information size (RIS) = 307). Although conventional MSFE had a higher endo-sinus bone gain (n = 13, I2 = 89%, weighted mean difference (WMD): -1.24, 95% CI: -1.91- -0.57, p = 0.0003, RIS = 461), this was not a determining factor in implant survival. No difference in perforation (n = 13, I2 = 0%, RD = 0.03, 95% CI: -0.02-0.09, p = 0.99, RIS = 223) and marginal bone loss (n = 4, I2 = 0%, WMD = 0.05, 95% CI: -0.14-0.23, p = 0.62, no RIS) was detected between the two groups using meta-analysis. The pooled results of the implant stability quotient between the two groups were not robust on sensitivity analysis. Because of the limited studies reporting on the visual analogue scale, surgical time, treatment costs, and bone density, qualitative analysis was conducted for these outcomes. Conclusions: This systematic review revealed that both non-graft and grafted MSFE had high implant survival rates. Owing to the moderate strength of the evidence and short-term follow-up, the results should be interpreted with caution.

Prediction of human epidermal growth factor receptor 2 (HER2) status in breast cancer by mammographic radiomics features and clinical characteristics: a multicenter study.

OBJECTIVES: To preoperatively evaluate the human epidermal growth factor 2 (HER2) status in breast cancer using mammographic radiomics features and clinical characteristics on a multi-vendor and multi-center basis. METHODS: This multi-center study included a cohort of 1512 Chinese female with invasive ductal carcinoma of no special type (IDC-NST) from two different hospitals and five devices (1332 from Institution A, used for training and testing the models, and 180 women from Institution B, as the external validation cohort). The Gradient Boosting Machine (GBM) was employed to establish radiomics and multiomics models. Model efficacy was evaluated by the area under the curve (AUC). RESULTS: The number of HER2-positive patients in the training, testing, and external validation cohort were 245(26.3%), 105 (26.3.8%), and 51(28.3%), respectively, with no statistical differences among the three cohorts (p = 0.842, chi-square test). The radiomics model, based solely on the radiomics features, achieved an AUC of 0.814 (95% CI, 0.784-0.844) in the training cohort, 0.776 (95% CI, 0.727-0.825) in the testing cohort, and 0.702 (95% CI, 0.614-0.790) in the external validation cohort. The multiomics model, incorporated radiomics features with clinical characteristics, consistently outperformed the radiomics model with AUC values of 0.838 (95% CI, 0.810-0.866) in the training cohort, 0.788 (95% CI, 0.741-0.835) in the testing cohort, and 0.722 (95% CI, 0.637-0.811) in the external validation cohort. CONCLUSIONS: Our study demonstrates that a model based on radiomics features and clinical characteristics has the potential to accurately predict HER2 status of breast cancer patients across multiple devices and centers. CLINICAL RELEVANCE STATEMENT: By predicting the HER2 status of breast cancer reliably, the presented model built upon radiomics features and clinical characteristics on a multi-vendor and multi-center basis can help in bolstering the model's applicability and generalizability in real-world clinical scenarios. KEY POINTS: • The mammographic presentation of breast cancer is closely associated with the status of human epidermal growth factor receptor 2 (HER2). • The radiomics model, based solely on radiomics features, exhibits sub-optimal performance in the external validation cohort. • By combining radiomics features and clinical characteristics, the multiomics model can improve the prediction ability in external data.

Synergistic Amelioration of Osseointegration and Osteoimmunomodulation with a Microarc Oxidation-Treated Three-Dimensionally Printed Ti-24Nb-4Zr-8Sn Scaffold via Surface Activity and Low Elastic Modulus.

Biomaterial scaffolds, including bone substitutes, have evolved from being primarily a biologically passive structural element to one in which material properties such as surface topography and chemistry actively direct bone regeneration by influencing stem cells and the immune microenvironment. Ti-6Al-4V(Ti6Al4V) implants, with a significantly higher elastic modulus than human bone, may lead to stress shielding, necessitating improved stability at the bone-titanium alloy implant interface. Ti-24Nb-4Zr-8Sn (Ti2448), a low elastic modulus ß-type titanium alloy devoid of potentially toxic elements, was utilized in this study. We employed 3D printing technology to fabricate a porous scaffold structure to further decrease the structural stiffness of the implant to approximate that of cancellous bone. Microarc oxidation (MAO) surface modification technology is then employed to create a microporous structure and a hydrophilic oxide ceramic layer on the surface and interior of the scaffold. In vitro studies demonstrated that MAO treatment enhances the proliferation, adhesion, and osteogenesis capabilities on the scaffold surface. The chemical composition of the MAO-Ti2448 oxide layer is found to enhance the transcription and expression of osteogenic genes in bone mesenchymal stem cells (BMSCs), potentially related to the enrichment of Nb2O5 and SnO2 in the oxide layer. The MAO-Ti2448 scaffold, with its synergistic surface activity and low stiffness, significantly activates the anti-inflammatory macrophage phenotype, creating an immune microenvironment that promotes the osteogenic differentiation of BMSCs. In vivo experiments in a rabbit model demonstrated a significant improvement in the quantity and quality of the newly formed bone trabeculae within the scaffold under the contact osteogenesis pattern with a matched elastic modulus. These trabeculae exhibit robust connections to the external structure of the scaffold, accelerating the formation of an interlocking structure between the bone and implant and providing higher implantation stability. These findings suggest that the MAO-Ti2448 scaffold has significant potential as a bone defect repair material by regulating osteoimmunomodulation and osteogenesis to enhance osseointegration. This study demonstrates an optional strategy that combines the mechanism of reducing the elastic modulus with surface modification treatment, thereby extending the application scope of ß-type titanium alloy.

Bacteria-Based Nanoprobes for Cancer Therapy.

Surgical removal together with chemotherapy and radiotherapy has used to be the pillars of cancer treatment. Although these traditional methods are still considered as the first-line or standard treatments, non-operative situation, systemic toxicity or resistance severely weakened the therapeutic effect. More recently, synthetic biological nanocarriers elicited substantial interest and exhibited promising potential for combating cancer. In particular, bacteria and their derivatives are omnipotent to realize intrinsic tumor targeting and inhibit tumor growth with anti-cancer agents secreted and immune response. They are frequently employed in synergistic bacteria-mediated anticancer treatments to strengthen the effectiveness of anti-cancer treatment. In this review, we elaborate on the development, mechanism and advantage of bacterial therapy against cancer and then systematically introduce the bacteria-based nanoprobes against cancer and the recent achievements in synergistic treatment strategies and clinical trials. We also discuss the advantages as well as the limitations of these bacteria-based nanoprobes, especially the questions that hinder their application in human, exhibiting this novel anti-cancer endeavor comprehensively.

Dynamic Homogenization of Internal Strain in Multi-Principal Element Alloy via High-Concentration Doping of Oxygen with Large Mobility.

Internal strain and its distribution within the crystal lattice play crucial roles in modulating dislocation activities, thereby affecting mechanical properties of materials. Through the synergistic application of integrated differential phase contrast, in situ transmission electron microscopy characterizations, and computational simulations, a method is unveiled for homogenizing dislocation pinning in NiCoCr multi-principal element alloy (MPEA) through the introduction of a high concentration of oxygen atoms with high diffusion mobility. The doping of massive oxygen atoms creates a high density of strong local pinning points for dislocation motion. Notably, oxygen interstitials exhibit remarkable diffusion and mobility across different octahedral and tetrahedral sites within the distorted crystal lattice of NiCoCrO alloy, even at room temperature. The capability allows for the release of severe stress concentrations arising from dislocation entanglement and the establishment of new strong local pinning points at alternative locations in a uniform way, enabling the material with high strength and outstanding deformability. These findings suggest that interstitial atoms can exhibit significant mobility, even at ambient temperature, in complex MPEAs with spreading lattice distortion, opening new possibilities for dislocation engineering.

Meningioma consistency assessment based on the fusion of deep learning features and radiomics features.

PURPOSE: This study aims to combine deep learning features with radiomics features for the computer-assisted preoperative assessment of meningioma consistency. METHODS: 202 patients with surgery and pathological diagnosis of meningiomas at our institution between December 2016 and December 2018 were retrospectively included in the study. The T2-fluid attenuated inversion recovery (T2-Flair) images were evaluated to classify meningioma as soft or hard by professional neurosurgeons based on Zada's consistency grading system. All the patients were split randomly into a training cohort (n = 162) and a testing cohort (n = 40). A convolutional neural network (CNN) model was proposed to extract deep learning features. These deep learning features were combined with radiomics features. After multiple feature selections, selected features were used to construct classification models using four classifiers. AUC was used to evaluate the performance of each classifier. A signature was further constructed by using the least absolute shrinkage and selection operator (LASSO). A nomogram based on the signature was created for predicting meningioma consistency. RESULTS: The logistic regression classifier constructed using 17 radiomics features and 9 deep learning features provided the best performance with a precision of 0.855, a recall of 0.854, an F1-score of 0.852 and an AUC of 0.943 (95 % CI, 0.873-1.000) in the testing cohort. The C-index of the nomogram was 0.822 (95 % CI, 0.758-0.885) in the training cohort and 0.943 (95 % CI, 0.873-1.000) in the testing cohort with good calibration. Decision curve analysis further confirmed the clinical usefulness of the nomogram for predicting meningioma consistency. CONCLUSIONS: The proposed method for assessing meningioma consistency based on the fusion of deep learning features and radiomics features is potentially clinically valuable. It can be used to assist physicians in the preoperative determination of tumor consistency.

Distinct MRI characteristics of spinal cord diffuse midline glioma, H3 K27-altered in comparison to spinal cord glioma without H3 K27-alteration and demyelination disorder.

BACKGROUND: An applicable magnetic resonance imaging (MRI) biomarker for diffuse midline glioma (DMG), H3 K27-altered of the spinal cord is important for non-invasive diagnosis. PURPOSE: To evaluate the efficacy of conventional MRI (cMRI) in distinguishing between DMGs, H3 K27-altered, gliomas without H3 K27-alteration, and demyelinating lesions in the spinal cord. MATERIAL AND METHODS: Between January 2017 and February 2023, patients with pathology-confirmed spinal cord gliomas (including ependymomas) with definite H3 K27 status and demyelinating diseases diagnosed by recognized criteria were recruited as the training set for this retrospective study. Morphologic parameter assessment was performed by two neuroradiologists on T1-weighted, T2-weighted, and contrast-enhanced T1-weighted imaging. Variables with high inter- and intra-observer agreement were included in univariable correlation analysis and multivariable logistic regression. The performance of the final model was verified by internal and external testing sets. RESULTS: The training cohort included 21 patients with DMGs (13 men; mean age = 34.57 ± 13.489 years), 21 with wild-type gliomas (10 men; mean age = 46.76 ± 17.017 years), and 20 with demyelinating diseases (5 men; mean age = 49.50 ± 18.872 years). A significant difference was observed in MRI features, including cyst(s), hemorrhage, pial thickening with enhancement, and the maximum anteroposterior diameter of the spinal cord. The prediction model, integrating age, age2, and morphological characteristics, demonstrated good performance in the internal and external testing cohort (accuracy: 0.810 and 0.800, specificity: 0.810 and 0.720, sensitivity: 0.872 and 0.849, respectively). CONCLUSION: Based on cMRI, we developed a model with good performance for differentiating among DMGs, H3 K27-altered, wild-type glioma, and demyelinating lesions in the spinal cord.

Multicenter Study of the Utility of Convolutional Neural Network and Transformer Models for the Detection and Segmentation of Meningiomas.

PURPOSE: This study aimed to investigate the effectiveness and practicality of using models like convolutional neural network and transformer in detecting and precise segmenting meningioma from magnetic resonance images. METHODS: The retrospective study on T1-weighted and contrast-enhanced images of 523 meningioma patients from 3 centers between 2010 and 2020. A total of 373 cases split 8:2 for training and validation. Three independent test sets were built based on the remaining 150 cases. Six convolutional neural network detection models trained via transfer learning were evaluated using 4 metrics and receiver operating characteristic analysis. Detected images were used for segmentation. Three segmentation models were trained for meningioma segmentation and were evaluated via 4 metrics. In 3 test sets, intraclass consistency values were used to evaluate the consistency of detection and segmentation models with manually annotated results from 3 different levels of radiologists. RESULTS: The average accuracies of the detection model in the 3 test sets were 97.3%, 93.5%, and 96.0%, respectively. The model of segmentation showed mean Dice similarity coefficient values of 0.884, 0.834, and 0.892, respectively. Intraclass consistency values showed that the results of detection and segmentation models were highly consistent with those of intermediate and senior radiologists and lowly consistent with those of junior radiologists. CONCLUSIONS: The proposed deep learning system exhibits advanced performance comparable with intermediate and senior radiologists in meningioma detection and segmentation. This system could potentially significantly improve the efficiency of the detection and segmentation of meningiomas.

miR-124 and VAMP3 Act Antagonistically in Human Neuroblastoma.

Neuroblastoma (NB) is the most common extracranial solid tumor that affects developing nerve cells in the fetus, infants, and children. miR-124 is a microRNA (miRNA) enriched in neuronal tissues, and VAMP3 (vesicle-associated membrane protein 3) has been reported to be an miR-124 target, although the relationship between NB and miR-124 or VAMP3 is unknown. Our current work identified that miR-124 levels are high in NB cases and that elevated miR-124 correlates with worse NB outcomes. Conversely, depressed VAMP3 correlates with worse NB outcomes. To investigate the mechanisms by which miR-124 and VAMP3 regulate NB, we altered miR-124 or VAMP3 expression in human NB cells and observed that increased miR-124 and reduced VAMP3 stimulated cell proliferation and suppressed apoptosis, while increased VAMP3 had the opposite effects. Genome-wide mRNA expression analyses identified gene and pathway changes which might explain the NB cell phenotypes. Together, our studies suggest that miR-124 and VAMP3 could be potential new markers of NB and targets of NB treatments.

The Preparation of Golgi Apparatus-Targeted Polymer Dots Encapsulated with Carbon Nanodots of Bright Near-Infrared Fluorescence for Long-Term Bioimaging.

As a vital organelle in eukaryotic cells, the Golgi apparatus is responsible for processing and transporting proteins in cells. Precisely monitoring the status of the Golgi apparatus with targeted fluorescence imaging technology is of enormous importance but remains a dramatically challenging task. In this study, we demonstrate the construction of the first Golgi apparatus-targeted near-infrared (NIR) fluorescent nanoprobe, termed Golgi-Pdots. As a starting point of our investigation, hydrophobic carbon nanodots (CNDs) with bright NIR fluorescence at 674 nm (fluorescence quantum yield: 12.18%), a narrow emission band of 23 nm, and excellent stability were easily prepared from Magnolia Denudata flowers using an ultrasonic method. Incorporating the CNDs into a polymer matrix modified with Golgi-targeting molecules allowed for the production of the water-soluble Golgi-Pdots, which showed high colloidal stability and similar optical properties compared with pristine CNDs. Further studies revealed that the Golgi-Pdots showed good biocompatibility and Golgi apparatus-targeting capability. Based on these fascinating merits, utilizing Golgi-Pdots for the long-term tracking of the Golgi apparatus inside live cells was immensely successful.

Magnetic field-assisted fabrication of quasi-bilayered, multi-responsive and patternable actuators.

Quasi-bilayered actuators composed of Fe3O4-decorated graphene oxide and polyvinylidene fluoride have been fabricated in a magnetic field. The actuators could stably respond to multiple stimuli including infrared light, acetone vapour and a magnetic field. The actuator is also patternable because of the magnetism-induced spatial distribution of fillers in the matrix.

The Use of Tricaine Methanesulfonate (MS-222) in Asian Seabass (Lates calcarifer) at Different Temperatures: Study of Optimal Doses, Minimum Effective Concentration, Blood Biochemistry, Immersion Pharmacokinetics, and Tissue Distributions.

This study was conducted to determine the optimal doses and minimum effective concentrations (MECs) of tricaine methanesulfonate (MS-222) in marketable-size Asian seabass reared at two temperatures (22 and 28 °C). Serum biochemical parameters, pharmacokinetics, and tissue distributions of MS-222 following immersion at the determined optimal doses were also evaluated in order to delineate possible mechanisms dictating the temperature difference. The definition of optimal dose is set as the dose when fish attain stage III anesthesia within 5 min, sustain this stage for 3 min, and re-attain equilibrium within 5 min. The MEC is the fish serum MS-222 concentration when stage III anesthesia is reached. The results showed that water temperature exerted no or minimal impact on the designated parameters. The optimal doses at 22 and 28 °C were 140 and 150 µg/mL, while the MECs were 70.48 and 78.27 µg/mL, respectively. Fish exposed to the optimal doses of MS-222 had significantly elevated blood concentrations of lactate, glucose, calcium, magnesium, and sodium, while the blood pH was significantly decreased. The fish eliminated MS-222 faster at 28 °C than at 22 °C, with serum half-lives of 18.43 and 37.01 h, respectively. Tissue-specific distribution patterns were evident. Irrespective of water temperature, MS-222 peaked at 5 min for the brain and gill but peaked slightly later at 10-20 min for the liver and kidney. Most tissues exhibit a gradual decline of drug concentration except for the gill, which was maintained at a steady level. Muscle is the least perfused tissue with the lowest drug concentration throughout the 90 min period. This study provided physiological and pharmacokinetic evidence contributing to a better understanding of the actions of MS-222 in Asian seabass at different temperatures.

He-ion Irradiation Effects on the Microstructures and Mechanical Properties of the Ti-Zr-Hf-V-Ta Low-Activation High-Entropy Alloys.

High-entropy alloys (HEAs) have shown promising potential applications in advanced reactors due to the outstanding mechanical properties and irradiation tolerance at elevated temperatures. In this work, the novel low-activation Ti2ZrHfxV0.5Ta0.2 HEAs were designed and prepared to explore high-performance HEAs under irradiation. The microstructures and mechanical properties of the Ti2ZrHfxV0.5Ta0.2 HEAs before and after irradiation were investigated. The results showed that the unirradiated Ti2ZrHfxV0.5Ta0.2 HEAs displayed a single-phase BCC structure. The yield strength of the Ti2ZrHfxV0.5Ta0.2 HEAs increased gradually with the increase of Hf content without decreasing the plasticity at room and elevated temperatures. After irradiation, no obvious radiation-induced segregations or precipitations were found in the transmission electron microscope results of the representative Ti2ZrHfV0.5Ta0.2 HEA. The size and number density of the He bubbles in the Ti2ZrHfV0.5Ta0.2 HEA increased with the improvement of fluence at 1023 K. At the fluences of 1 × 1016 and 3 × 1016 ions/cm2, the irradiation hardening fractions of the Ti2ZrHfV0.5Ta0.2 HEA were 17.7% and 34.1%, respectively, which were lower than those of most reported conventional low-activation materials at similar He ion irradiation fluences. The Ti2ZrHfV0.5Ta0.2 HEA showed good comprehensive mechanical properties, structural stability, and irradiation hardening resistance at elevated temperatures, making it a promising structural material candidate for advanced nuclear energy systems.

Predicting peritumoral edema development after gamma knife radiosurgery of meningiomas using machine learning methods: a multicenter study.

OBJECTIVES: Edema is a complication of gamma knife radiosurgery (GKS) in meningioma patients that leads to a variety of consequences. The aim of this study is to construct radiomics-based machine learning models to predict post-GKS edema development. METHODS: In total, 445 meningioma patients who underwent GKS in our institution were enrolled and partitioned into training and internal validation datasets (8:2). A total of 150 cases from multicenter data were included as the external validation dataset. In each case, 1132 radiomics features were extracted from each pre-treatment MRI sequence (contrast-enhanced T1WI, T2WI, and ADC maps). Nine clinical features and eight semantic features were also generated. Nineteen random survival forest (RSF) and nineteen neural network (DeepSurv) models with different combinations of radiomics, clinical, and semantic features were developed with the training dataset, and evaluated with internal and external validation. A nomogram was derived from the model achieving the highest C-index in external validation. RESULTS: All the models were successfully validated on both validation datasets. The RSF model incorporating clinical, semantic, and ADC radiomics features achieved the best performance with a C-index of 0.861 (95% CI: 0.748-0.975) in internal validation, and 0.780 (95% CI: 0.673-0.887) in external validation. It stratifies high-risk and low-risk cases effectively. The nomogram based on the predicted risks provided personalized prediction with a C-index of 0.962 (95%CI: 0.951-0.973) and satisfactory calibration. CONCLUSION: This RSF model with a nomogram could represent a non-invasive and cost-effective tool to predict post-GKS edema risk, thus facilitating personalized decision-making in meningioma treatment. CLINICAL RELEVANCE STATEMENT: The RSF model with a nomogram built in this study represents a handy, non-invasive, and cost-effective tool for meningioma patients to assist in better counselling on the risks, appropriate individual treatment decisions, and customized follow-up plans. KEY POINTS: • Machine learning models were built to predict post-GKS edema in meningioma. The random survival forest model with clinical, semantic, and ADC radiomics features achieved excellent performance. • The nomogram based on the predicted risks provides personalized prediction with a C-index of 0.962 (95%CI: 0.951-0.973) and satisfactory calibration and shows the potential to assist in better counselling, appropriate treatment decisions, and customized follow-up plans. • Given the excellent performance and convenient acquisition of the conventional sequence, we envision that this non-invasive and cost-effective tool will facilitate personalized medicine in meningioma treatment.

Glioblastomas with and without peritumoral fluid-attenuated inversion recovery (FLAIR) hyperintensity present morphological and microstructural differences on conventional MR images.

OBJECTIVES: Glioblastoma (GB) without peritumoral fluid-attenuated inversion recovery (FLAIR) hyperintensity is atypical and its characteristics are barely known. The aim of this study was to explore the differences in pathological and MRI-based intrinsic features (including morphologic and first-order features) between GBs with peritumoral FLAIR hyperintensity (PFH-bearing GBs) and GBs without peritumoral FLAIR hyperintensity (PFH-free GBs). METHODS: In total, 155 patients with pathologically diagnosed GBs were retrospectively collected, which included 110 PFH-bearing GBs and 45 PFH-free GBs. The pathological and imaging data were collected. The Visually AcceSAble Rembrandt Images (VASARI) features were carefully evaluated. The first-order radiomics features from the tumor region were extracted from FLAIR, apparent diffusion coefficient (ADC), and T1CE (T1-contrast enhanced) images. All parameters were compared between the two groups of GBs. RESULTS: The pathological data showed more alpha thalassemia/mental retardation syndrome X-linked (ATRX)-loss in PFH-free GBs compared to PFH-bearing ones (p < 0.001). Based on VASARI evaluation, PFH-free GBs had larger intra-tumoral enhancing proportion and smaller necrotic proportion (both, p < 0.001), more common non-enhancing tumor (p < 0.001), mild/minimal enhancement (p = 0.003), expansive T1/FLAIR ratio (p < 0.001) and solid enhancement (p = 0.009), and less pial invasion (p = 0.010). Moreover, multiple ADC- and T1CE-based first-order radiomics features demonstrated differences, especially the lower intensity heterogeneity in PFH-free GBs (for all, adjusted p < 0.05). CONCLUSIONS: Compared to PFH-bearing GBs, PFH-free ones demonstrated less immature neovascularization and lower intra-tumoral heterogeneity, which would be helpful in clinical treatment stratification. CLINICAL RELEVANCE STATEMENT: Glioblastomas without peritumoral FLAIR hyperintensity show less immature neovascularization and lower heterogeneity leading to potential higher treatment benefits due to less drug resistance and treatment failure. KEY POINTS: • The study explored the differences between glioblastomas with and without peritumoral FLAIR hyperintensity. • Glioblastomas without peritumoral FLAIR hyperintensity showed less necrosis and contrast enhancement and lower intensity heterogeneity. • Glioblastomas without peritumoral FLAIR hyperintensity had less immature neovascularization and lower tumor heterogeneity.

Oligodendrocyte Transcription Factor 2 as a Potential Prognostic Biomarker of Glioblastoma: Kaplan-Meier Analysis and the Development of a Binary Predictive Model Based on Visually Accessible Rembrandt Image and Magnetic Resonance Imaging Radiomic Features.

OBJECTIVE: Oligodendrocyte transcription factor 2 (OLIG2) is universally expressed in human glioblastoma (GB). Our study explores whether OLIG2 expression impacts GB patients' overall survival and establishes a machine learning model for OLIG2 level prediction in patients with GB based on clinical, semantic, and magnetic resonance imaging radiomic features. METHODS: Kaplan-Meier analysis was used to determine the optimal cutoff value of the OLIG2 in 168 GB patients. Three hundred thirteen patients enrolled in the OLIG2 prediction model were randomly divided into training and testing sets in a ratio of 7:3. The radiomic, semantic, and clinical features were collected for each patient. Recursive feature elimination (RFE) was used for feature selection. The random forest (RF) model was built and fine-tuned, and the area under the curve was calculated to evaluate the performance. Finally, a new testing set excluding IDH-mutant patients was built and tested in a predictive model using the fifth edition of the central nervous system tumor classification criteria. RESULTS: One hundred nineteen patients were included in the survival analysis. Oligodendrocyte transcription factor 2 was positively associated with GB survival, with an optimal cutoff of 10% ( P = 0.00093). One hundred thirty-four patients were eligible for the OLIG2 prediction model. An RFE-RF model based on 2 semantic and 21 radiomic signatures achieved areas under the curve of 0.854 in the training set, 0.819 in the testing set, and 0.825 in the new testing set. CONCLUSIONS: Glioblastoma patients with ≤10% OLIG2 expression tended to have worse overall survival. An RFE-RF model integrating 23 features can predict the OLIG2 level of GB patients preoperatively, irrespective of the central nervous system classification criteria, further guiding individualized treatment.

Sauchinone Inhibits the Proliferation and Immune Invasion Capacity of Colorectal Cancer Cells through the Suppression of PD-L1 and MMP2/MM9.

BACKGROUND: Colorectal cancer (CRC) is one of the most common tumors globally and a leading cause of cancer-related death. In China, CRC is the third most common cancer type. Sauchinone is known to exhibit anti-tumor and anti-inflammatory activity, but its effects on CRC have not been investigated to-date Objective: To investigate the effects of Sauchinone on CRC development and metastasis and its underlying mechanism( s) of action. METHODS: SW480 and HCT116 cells were treated with a range of concentrations of Sauchinone. Cell proliferation was measured using EDU assays and flow cytometry. RESULTS: Treatment with 50 µM Sauchinone decreased the expression of MMP2 and MMP9 and downregulated PD-L1 expression (PD-1/PD-L1) leading to checkpoint inhibition. Sauchinone treatment also enhanced the cytotoxicity of SW840 and HCT116 cells co-cultured with CD8+ T cells. The overexpression of PD-L1 rescued the anti-proliferative and cytotoxic effects of Sauchinone in both types. CONCLUSIONS: We show that Sauchinone suppresses CRC cell growth through the downregulation of MMP2 and MM9 expression and PD-1/PD-L1 mediated checkpoint inhibition. Collectively, these data highlight the promise of Sauchinone as a future anti-CRC therapeutic.

Polymorphism of E6 and E7 Genes in Human Papillomavirus Types 31 and 33 in Northeast China.

Persistent infection with human papillomavirus (HPV) types 31 and 33 is an important causative factor for cervical cancer. The E6/E7 genes are key oncogenes involved in the immortalization and transformation of human epithelial cells. Genetic polymorphism may lead to differences in the virus' carcinogenic potential, the immune reaction of the host, and the potencies of vaccines. Few studies on HPV31/33 E6/E7 genetic polymorphism have been carried out. To study the genetic polymorphism of HPV31 and HPV33 E6/E7 genes in northeast China, these genes (HPV31 E6/E7, n = 151; HPV33 E6/E7, n = 136) were sequenced and compared to reference sequences (J04353.1, M12732.1) using BioEdit. Phylogenetic trees were constructed by the neighbor-joining method using MegaX. The diversity of the secondary structure was estimated using the PSIPred server. The positively selected sites were analyzed using PAML4.9. The major histocompatibility complex (MHC) class I and MHCII epitopes were predicted using the ProPred-I server and ProPredserver. B-cell epitopes were predicted using the ABCpred server. In the 151 HPV31E6 sequences, 25 (25/450) single-nucleotide mutations were found, 14 of which were synonymous mutations and 11 were nonsynonymous. In the 151 HPV31E7 sequences, 8 (8/297) nucleotide mutations were found, 3 of which were synonymous mutations and 5 were nonsynonymous. In the 136 HPV33E6 sequences, 17 (17/450) nucleotide mutations were observed, 7 of which were synonymous mutations and 10 were nonsynonymous. C14T/G (T5I/S) was a triallelic mutation. Finally, in the 136 HPV33E7 sequences, 9 (9/294) nucleotide mutations were observed, 3 of which were synonymous mutations and 6 were nonsynonymous. C134T/A (A45V/E) and C278G/A (T93S/N) were triallelic mutations. Lineage A was the most common lineage in both HPV31 and HPV33. In all of the sequences, we only identified one positively selected site, HPV33 E6 (K93N). Most nonsynonymous mutations were localized at sites belonging to MHC and/or B-cell predicted epitopes. Data obtained in this study should contribute to the development and application of detection probes, targeted drugs, and vaccines.