Digital reference object toolkit of breast DCE MRI for quantitative evaluation of image reconstruction and analysis methods.

PURPOSE: To develop a digital reference object (DRO) toolkit to generate realistic breast DCE-MRI data for quantitative assessment of image reconstruction and data analysis methods. METHODS: A simulation framework in a form of DRO toolkit has been developed using the ultrafast and conventional breast DCE-MRI data of 53 women with malignant (n = 25) or benign (n = 28) lesions. We segmented five anatomical regions and performed pharmacokinetic analysis to determine the ranges of pharmacokinetic parameters for each segmented region. A database of the segmentations and their pharmacokinetic parameters is included in the DRO toolkit that can generate a large number of realistic breast DCE-MRI data. We provide two potential examples for our DRO toolkit: assessing the accuracy of an image reconstruction method using undersampled simulated radial k-space data and assessing the impact of the B 1 + $$ {\mathrm{B}}_1^{+} $$ field inhomogeneity on estimated parameters. RESULTS: The estimated pharmacokinetic parameters for each region showed agreement with previously reported values. For the assessment of the reconstruction method, it was found that the temporal regularization resulted in significant underestimation of estimated parameters by up to 57% and 10% with the weighting factor λ = 0.1 and 0.01, respectively. We also demonstrated that spatial discrepancy of v p $$ {v}_p $$ and PS $$ \mathrm{PS} $$ increase to about 33% and 51% without correction for B 1 + $$ {\mathrm{B}}_1^{+} $$ field. CONCLUSION: We have developed a DRO toolkit that includes realistic morphology of tumor lesions along with the expected pharmacokinetic parameter ranges. This simulation framework can generate many images for quantitative assessment of DCE-MRI reconstruction and analysis methods.

FGL2 as a predictive biomarker for prognosis and immunotherapy in bladder cancer.

Background: Metastasis and immunosuppression result in unfavorable prognosis in bladder cancer (BLCA). FGL1 and FGL2 are two members of the fibrinogen-related proteins family, but their potential effects on BLCA remain elusive. Methods: The expression profile of FGL1 and FGL2 in BLCA was analyzed in multiple databases. Furthermore, the expression of FGL2 was validated in BLCA tissues. The predictive capability of FGL2 was evaluated by Kaplan-Meier analysis, univariate analysis, and multivariate Cox regression. A nomogram model was constructed based on FGL2 expression and clinicopathological parameters for clinical practice. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analyses (GSEA) were performed to investigate enrichment in the biological processes. In addition, the correlation between FGL2 and immunological characteristics in the BLCA tumor microenvironment (TME), including tumor-infiltrating immune cells (TICs), cancer-immunity cycles, immune checkpoint molecules (ICPs), immunophenoscores (IPS), and response to anti-PD-L1 immunotherapy was further analyzed. Results: FGL2 was found to be downregulated in BLCA due to hypermethylation of the FGL2 promoter region, which was associated with an unfavorable prognosis. Moreover, BLCA patients with high FGL2 expression exhibited better response to immunotherapy. Conclusions: Our research revealed that FGL2 was downregulated in BLCA and was negatively correlated with DNA methylation. High FGL2 expression was confirmed as an independent risk for prognosis. Moreover, FGL2 is a promising indicator for the response to immunotherapy in patients with BLCA.

A prognostic model based on necroptosis-related genes for prognosis and therapy in bladder cancer.

Bladder cancer, one of the most prevalent malignant cancers, has high rate of recurrence and metastasis. Owing to genomic instability and high-level heterogeneity of bladder cancer, chemotherapy and immunotherapy drugs sensitivity and lack of prognostic markers, the prognosis of bladder cancer is unclear. Necroptosis is a programmed modality of necrotic cell death in a caspase-independent form. Despite the fact that necroptosis plays a critical role in tumor growth, cancer metastasis, and cancer patient prognosis, necroptosis-related gene sets have rarely been studied in bladder cancer. As a result, the development of new necroptosis-related prognostic indicators for bladder cancer patients is critical. Herein, we assessed the necroptosis landscape of bladder cancer patients from The Cancer Genome Atlas database and classified them into two unique necroptosis-related patterns, using the consensus clustering. Then, using five prognosis-related genes, we constructed a prognostic model (risk score), which contained 5 genes (ANXA1, DOK7, FKBP10, MAP1B and SPOCD1). And a nomogram model was also developed to offer the clinic with a more useful prognostic indicator. We found that risk score was significantly associated with clinicopathological characteristics, TIME, and tumor mutation burden in patients with bladder cancer. Moreover, risk score was a valid guide for immunotherapy, chemotherapy, and targeted drugs. In our study, DOK7 was chosen to further verify our prognosis model, and functional assays indicated that knockdown the expression of DOK7 could prompt bladder cancer proliferation and migration. Our work demonstrated the potential role of prognostic model based on necroptosis genes in the prognosis, immune landscape and response efficacy of immunotherapy of bladder cancer.

Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging: Combining physics and machine learning for improved medical imaging.

Physics-driven deep learning methods have emerged as a powerful tool for computational magnetic resonance imaging (MRI) problems, pushing reconstruction performance to new limits. This article provides an overview of the recent developments in incorporating physics information into learning-based MRI reconstruction. We consider inverse problems with both linear and non-linear forward models for computational MRI, and review the classical approaches for solving these. We then focus on physics-driven deep learning approaches, covering physics-driven loss functions, plug-and-play methods, generative models, and unrolled networks. We highlight domain-specific challenges such as real- and complex-valued building blocks of neural networks, and translational applications in MRI with linear and non-linear forward models. Finally, we discuss common issues and open challenges, and draw connections to the importance of physics-driven learning when combined with other downstream tasks in the medical imaging pipeline.

Identification of ENO1 as a prognostic biomarker and molecular target among ENOs in bladder cancer.

BACKGROUND: Enolase is an essential enzyme in the process of glycolysis and has been implicated in cancer progression. Though dysregulation of ENOs has been reported in multiple cancers, their prognostic value and specific role in bladder cancer (BLCA) remain unclear. METHODS: Multiple databases were employed to examine the expression of ENOs in BLCA. The expression of ENO1 was also validated in BLCA cell lines and tissue samples by western blotting and immunohistochemistry. Kaplan-Meier analysis, ROC curve, univariate and multivariate Cox regression were performed to evaluate the predictive capability of the ENO1. Gene ontology (GO) and Gene Set Enrichment Analyses (GSEA) analysis were employed to perform the biological processes enrichment. Function experiments were performed to explore the biological role of ENO1 in BLCA. The correlation of ENO1 with immune cell infiltration was explored by CIBERSORT. RESULTS: By analyzing three ENO isoforms in multiple databases, we identified that ENO1 was the only significantly upregulated gene in BLCA. High expression level of ENO1 was further confirmed in BLCA tissue samples. Aberrant ENO1 overexpression was associated with clinicopathological characteristics and unfavorable prognosis. Functional studies demonstrated that ENO1 depletion inhibited cancer cell aggressiveness. Furthermore, the expression level of ENO1 was correlated with the infiltration levels of immune cells and immune-related functions. CONCLUSIONS: Taken together, our results indicated that ENO1 might serve as a promising prognostic biomarker for prognosticating prognosis associated with the tumor immune microenvironment, suggesting that ENO1 could be a potential immune-related target against BLCA.

Estimation of the capillary level input function for dynamic contrast-enhanced MRI of the breast using a deep learning approach.

PURPOSE: To develop a deep learning approach to estimate the local capillary-level input function (CIF) for pharmacokinetic model analysis of DCE-MRI. METHODS: A deep convolutional network was trained with numerically simulated data to estimate the CIF. The trained network was tested using simulated lesion data and used to estimate voxel-wise CIF for pharmacokinetic model analysis of breast DCE-MRI data using an abbreviated protocol from women with malignant (n = 25) and benign (n = 28) lesions. The estimated parameters were used to build a logistic regression model to detect the malignancy. RESULT: The pharmacokinetic parameters estimated using the network-predicted CIF from our breast DCE data showed significant differences between the malignant and benign groups for all parameters. Testing the diagnostic performance with the estimated parameters, the conventional approach with arterial input function (AIF) showed an area under the curve (AUC) between 0.76 and 0.87, and the proposed approach with CIF demonstrated similar performance with an AUC between 0.79 and 0.81. CONCLUSION: This study shows the feasibility of estimating voxel-wise CIF using a deep neural network. The proposed approach could eliminate the need to measure AIF manually without compromising the diagnostic performance to detect the malignancy in the clinical setting.

Establishment of an optimized orthotopic bladder cancer model in mice.

BACKGROUND: Bladder cancer (BC) is one of the most common malignancies of the genitourinary system. Animal models offer an important tool to explore tumour initiation, progression, and therapeutic mechanisms. Our aim is to construct an optimized orthotopic BC model which is predictable, reproducible, and convenient. METHODS: The optimized orthotopic BC model was constructed in male C57BL/6 mice utilizing microsyringes to inoculate them with a murine BC cell line (MB49). Anesthetised mice were inoculated with an MB49 cell suspension (10 µL) at approximately 5 × 106/mL. The whole process of modelling was observed and monitored every 3 days for 21 days utilizing HE staining and transabdominal ultrasonography (TUS). RESULTS: In this study, the model showed excellent success rates for tumour formation (96.67%) and metastatic rate (89.66%). Compared to the control group (sham operation), mice in the modelling group had serous cachexia, visible haematuresis and weight loss (all P < 0.05). The lungs, liver, ureter and kidneys were found to have tumour metastasis. Moreover, the average survival time (19.73 ± 1.69 d) of modelling mice was significantly shorter than that of the control mice (P < 0.05), which remained alive. CONCLUSION: Our study established a method using microsyringes to inject murine BC cells into the bladder wall, creating a stable transplantable BC model in mice.

Using Deep Learning to Accelerate Knee MRI at 3 T: Results of an Interchangeability Study.

OBJECTIVE. Deep learning (DL) image reconstruction has the potential to disrupt the current state of MRI by significantly decreasing the time required for MRI examinations. Our goal was to use DL to accelerate MRI to allow a 5-minute comprehensive examination of the knee without compromising image quality or diagnostic accuracy. MATERIALS AND METHODS. A DL model for image reconstruction using a variational network was optimized. The model was trained using dedicated multisequence training, in which a single reconstruction model was trained with data from multiple sequences with different contrast and orientations. After training, data from 108 patients were retrospectively undersampled in a manner that would correspond with a net 3.49-fold acceleration of fully sampled data acquisition and a 1.88-fold acceleration compared with our standard twofold accelerated parallel acquisition. An interchangeability study was performed, in which the ability of six readers to detect internal derangement of the knee was compared for clinical and DL-accelerated images. RESULTS. We found a high degree of interchangeability between standard and DL-accelerated images. In particular, results showed that interchanging the sequences would produce discordant clinical opinions no more than 4% of the time for any feature evaluated. Moreover, the accelerated sequence was judged by all six readers to have better quality than the clinical sequence. CONCLUSION. An optimized DL model allowed acceleration of knee images that performed interchangeably with standard images for detection of internal derangement of the knee. Importantly, readers preferred the quality of accelerated images to that of standard clinical images.

Complete hazard ranking to analyze right-censored data: An ALS survival study.

Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS) Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

MiCroKiTS 4.0: a database of midbody, centrosome, kinetochore, telomere and spindle.

We reported an updated database of MiCroKiTS 4.0 (http://microkit.biocuckoo.org) for proteins temporally and spatially localized in distinct subcellular positions including midbody, centrosome, kinetochore, telomere and mitotic spindle during cell division/mitosis. The database was updated from our previously developed database of MiCroKit 3.0, which contained 1489 proteins mostly forming super-complexes at midbody, centrosome and kinetochore from seven eukaryotes. Since the telomere and spindle apparatus are critical for cell division, the proteins localized at the two positions were also integrated. From the scientific literature, we curated 1872 experimentally identified proteins which at least locate in one of the five positions from eight species. Then the ortholog detection was performed to identify potential MiCroKiTS proteins from 144 eukaryotic organisms, which contains 66, 45 and 33 species of animals, fungi and plants, respectively. In total, 87,983 unique proteins with corresponding localization information were integrated into the database. The primary references of experimentally identified localizations were provided and the fluorescence microscope figures for the localizations of human proteins were shown. The orthologous relations between predicted and experimental localizations were also present. Taken together, we anticipate the database can serve as a useful resource for further analyzing the molecular mechanisms during cell division.

Do bubbles matter amid PBC for trigeminal neuralgia?

BACKGROUND: As a simple and safe alternative intervention, percutaneous balloon compression (PBC) has been gradually adopted by a growing number of neurosurgeons to treat trigeminal neuralgia. A pear-shaped opacity observed fluoroscopically, which indicates full suffusion of Meckel's cave conducting sufficient pressure against Gasserian ganglion, is believed to be the key to its success. Sometimes, a bitten pear may appear due to bubbles in the balloon but is usually ignored. OBJECTIVE: This study aims to investigate the effects of the bubbles on postoperative outcomes. METHODS: Patient data were obtained from the consecutive cases undergoing PBCs in our department between 2019 and 2021. Among them, pain and numbness were used to assess the efficacy of PBC based on Barrow Neurology Institute (BNI) scoring system. It was defined as an effective outcome if the postoperative pain intensity grade was lower than II. And those with numbness grade > II were regarded as numb incidence. RESULTS: We eventually recruited 59 cases, including 42 in full pear and 17 in bitten pear groups with follow-up time up to 44 months. The early effective rates were 95.2% and 82.4%, respectively (p > 0.05), which turned to 88.1% and 52.9% during the last follow-up period (p < 0.01). This result indicated that the bitten pear gave rise to a significantly higher recurrence. In terms of numbness, there was no significant difference. CONCLUSION: Gas does not yield enough pressure as liquid, and cannot exert enough pressure to the semilunar ganglion. Therefore, air evacuation should not be ignored before injection.

The Value of a Headless Pear Shape in Percutaneous Balloon Compression for Trigeminal Neuralgia.

BACKGROUND AND OBJECTIVES: Percutaneous balloon compression (PBC) has been regarded as a simple and effective remedy for trigeminal neuralgia. This study aims to retrospectively analyze the correlation between intraoperative balloon shapes and postoperative outcomes. METHOD: Those consecutive PBC cases performed in our department between 2019 and 2022 were reviewed. According to the intraoperative balloon figures, they were cataloged as headless pear, slim pear, bottle gourd, and winter melon groups. The degree of pain or numbness was quantified using the visual analog scale. Those pain-free or pain score <3 and satisfied by the patient were called effective, and those numb score >3 were taken into account of numbness incidence. RESULTS: Except for missing cases, 160 were finally recruited in this study with a mean follow-up for 23.6 ± 12.8 months. Postoperatively, the pain score plunged from 8.8 ± 1.0 to 0.8 ± 2.0 immediately, which rose slightly over time and maintained at 2.4 ± 3.1. The maximal pain score drop occurred in the headless pear group ( P < .001) and the minimal in the winter melon group ( P < .001). The early efficacy of PBC was 100%, 84.1%, 91.4%, and 50.0%, respectively. However, the long-term efficacy was 88.2%, 75.0%, 82.1% and 25.0%. The ipsilateral numbness occurred in most of the cases immediately after PBC with a score of 3.5 ± 2.3, which decreased significantly within 3 months to 2.3 ± 2.0 and turned to 1.7 ± 1.8 finally ( P < .05). The highest and lowest numb score appeared in bottle gourd and winter melon groups, respectively ( P < .05). CONCLUSION: A headless pear shape emerged in lateral fluoroscopy as the balloon was fully inflated indicates that the entire Meckel cave is suffused, and hence, the anterior semilunar ganglion has been solidly compressed, which may lead to a successful outcome.

Mechanisms of Xiaozheng decoction for anti-bladder cancer effects via affecting the GSK3ß/ß-catenin signaling pathways: a network pharmacology-directed experimental investigation.

PURPOSE: The combination of Xiaozheng decoction with postoperative intravesical instillation has been shown to improve the prognosis of bladder cancer patients and prevent recurrence. However, the mechanisms underlying the efficacy of this herbal formula remain largely unclear. This research aims to identify the important components of Xiaozheng decoction and explore their anti-bladder cancer effect and mechanism using network pharmacology-based experiments. METHODS: The chemical ingredients of each herb in the Xiaozheng decoction were collected from the Traditional Chinese Medicine (TCM) database. Network pharmacology was employed to predict the target proteins and pathways of action. Disease databases were utilized to identify target genes associated with bladder cancer. A Protein-Protein Interaction (PPI) network was constructed to illustrate the interaction with intersected target proteins. Key targets were identified using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis. A compound-target-pathway network was established after molecular docking predictions. In vitro experiments with bladder cancer cell lines were conducted using core chemical components confirmed by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-qTOF-MS) to verify the conclusions of network pharmacology. RESULTS: 45 active compounds were extracted, and their relationships with Traditional Chinese Medicines (TCMs) and protein targets were presented, comprising 7 herbs, 45 active compounds, and 557 protein targets. The intersection between potential TCM target genes and bladder cancer-related genes yielded 322 genes. GO and KEGG analyses indicated that these targets may be involved in numerous cancer-related pathways. Molecular docking results showed that candidate compounds except mandenol could form stable conformations with the receptor. In vitro experiments on three bladder cancer cell lines demonstrated that quercetin and two other impressive new compounds, bisdemethoxycurcumin (BDMC) and kumatakenin, significantly promoted cancer cell apoptosis through the B-cell lymphoma 2/Bcl-2-associated X (Bcl-2/BAX) pathway and inhibited proliferation and migration through the glycogen synthase kinase 3 beta (GSK3ß)/ß-catenin pathway. CONCLUSION: By employing network pharmacology and conducting in vitro experiments, the mechanism of Xiaozheng decoction's effect against bladder cancer was tentatively elucidated, and its main active ingredients and targets were identified, providing a scientific basis for future research.

Lumbar Endoscopic Unilateral Laminotomy With Bilateral Decompression Surgery in Severe Lumbar Stenosis Under Electrophysiological Monitoring-Focused on Full-Visualized Trephine/Osteotome.

OBJECTIVE: Although endoscopic drill has the advantages in manipulation and hemostasis, whose low efficiency and blurred vision reduce the efficacy of lumbar endoscopic unilateral laminotomy with bilateral decompression (LE-ULBD). The present study was designed to evaluate the safety and efficacy of full-visualized trephine/osteotome in the LE-ULBD surgery for severe lumbar stenosis. METHODS: Fifty-seven severe lumbar stenosis patients who underwent LE-ULBD between January 2020 to January 2023 were enrolled, who were divided into drill and visualized trephine groups. The medical records including demographics, operative duration, intraoperative electrophysiological findings, postoperative hospital stay or hospital stay, postoperative outcomes and complications were retrospectively reviewed and analyzed. RESULTS: A total of 57 patients included 15 in drill and 42 in trephine group were enrolled in the study. There was significant difference in the pre- and postoperative visual analogue scale and Oswestry Disability Index scores in both groups (p < 0.05). The mean operative duration in the trephine group (101.05 ± 12.18 minutes) was shorter than that in the drill group (134.67 ± 9.68 minutes) (p < 0.05). There was no statistical difference between the 2 groups in electrophysiological monitoring, posthospital stays, postoperative outcomes and complications. Abnormal free-electromyography (EMG) were recorded in 2 (13.3%) and 5 patients (11.9%) in the drill and trephine group. Intraoperative somatosensory evoked potential changes occurred in 3 (20%) and 3 patients (7.1%) in the drill and trephine group and all patients recovered immediately when surgery ended. No serious complications and recurrence occurred in all the patients. CONCLUSION: Full-visualized trephine/osteotome has been approved to be convenient, safe and efficient in our study, which combined with translaminar inside-out technique and EMG monitoring especially free-EMG may offer a new choice in LE-ULBD surgery for lumbar stenosis patients.

Pyroptosis-Related Patterns Predict Tumor Immune Landscape and Immunotherapy Response in Bladder Cancer.

Background: Bladder cancer (BC) is a leading cause of death from malignancy, with significant heterogeneity in the immunotherapeutic responsiveness of advanced status. Pyroptosis, a newly discovered inflammatory programmed cell death, is confirmed to play an indispensable role in tumorigenesis and anti-tumor activity. However, the effect of pyroptosis on the tumor-immune landscape remodeling and immunotherapy in BC remains elusive. Methods: We comprehensively evaluated the mRNA expression and genomic alterations of 33 pyroptosis-related genes (PRGs) in BC and evaluated the patterns of pyroptosis in publicly available BC datasets. An unsupervised clustering method was used to classify patients into distinct patterns. Then, we established a pyroptosis-related signature score (PS-score) model to quantify the pyroptosis-related patterns of individual BC patients using principal component analysis. Furthermore, we correlated the patterns with the immune landscape and response efficacy of immunotherapy. Results: Two pyroptosis-related patterns were identified in BC, and distinct patterns showed various immune characteristics. Patterns with a high expression level of PRGs exhibited a survival advantage and showed higher infiltration of cytotoxic lymphocytes. Tumors with a low PS-score were characterized by high tumor-infiltrating lymphocytes and considered "hot." Further analysis revealed that the PS-score was an independent prognostic factor and could predict the response to immunotherapy for patients with advanced BC. We found a significant positive association between AHNAK2, AHNAK nucleoprotein 2, expression, and PS-score. Functional assays showed that AHNAK2 knockdown was correlated with attenuated invasive ability. Conclusion: This work comprehensively demonstrated the potential function of pyroptosis-related patterns in the bladder tumor-immune landscape and identified their therapeutic liability in immunotherapy. Our study enhanced our understanding of the immune landscape and provided a new approach toward more effective immunotherapy strategies.

fastMRI+, Clinical pathology annotations for knee and brain fully sampled magnetic resonance imaging data.

Improving speed and image quality of Magnetic Resonance Imaging (MRI) using deep learning reconstruction is an active area of research. The fastMRI dataset contains large volumes of raw MRI data, which has enabled significant advances in this field. While the impact of the fastMRI dataset is unquestioned, the dataset currently lacks clinical expert pathology annotations, critical to addressing clinically relevant reconstruction frameworks and exploring important questions regarding rendering of specific pathology using such novel approaches. This work introduces fastMRI+, which consists of 16154 subspecialist expert bounding box annotations and 13 study-level labels for 22 different pathology categories on the fastMRI knee dataset, and 7570 subspecialist expert bounding box annotations and 643 study-level labels for 30 different pathology categories for the fastMRI brain dataset. The fastMRI+ dataset is open access and aims to support further research and advancement of medical imaging in MRI reconstruction and beyond.

The Mechanism of Volatile Oil of Rhodiola tangutica against Hypoxia-Induced Pulmonary Hypertension in Rats Based on RAS Pathway.

Materials and Methods: Seventy-five male Sprague-Dawley (SD) rats were separated into control (Ctr), hypoxia (Hyp), and Hyp+VORA treatment (100 mg/kg/d, 80 mg/kg/d, and 40 mg/kg/d) groups in random. To achieve the chronic hypoxia condition, rats were kept inside the hypobaric chamber with automatically adjusted inner pressure as well as oxygen content equal to those of 4500 m in altitude for 4 continuous weeks. After 4 weeks, the rats' physiological parameters were determined (mean pulmonary artery pressure (mPAP); right ventricular hypertrophy index (RVHI)). Based on hematoxylin and eosin (HE) staining and transmission electron microscope (TEM), morphological features of their lung tissues were also analyzed. Proliferation of pulmonary arterial smooth muscle cells (PASMCs) was detected by MTS Cell Proliferation Colorimetric assay. The levels of glutathione (GSH), malondialdehyde (MDA), and superoxide dismutase (SOD) in PASMCs were detected through corresponding kits, respectively. The protein levels in PASMCs and HPH rats were evaluated by Western blot (WB). Chemical components of VORA were detected through gas chromatography-mass spectrometer (GC-MS). Results: After induced by hypoxia for 4 weeks, the mPAP and RVHI levels were increased significantly in hypoxia group in contrast to the Ctr group, indicating the establishment of HPH rat model. The subsequent administration of VORA decreased the mPAP and RVHI level. The vascular wall thickness and lumen size were also decreased after treated by VORA compared with Hyp group. Meanwhile, VORA suppressed the proliferation and oxidant stress in PASMCs. Therefore, the effect of VORA on decreasing vascular wall thickening and lumen size could be related to its antiproliferation effect on PASMCs. In addition, compared to the Hyp group, VORA downregulated the ACE, AngII, and AT1R protein expressions but increased ACE2 and MAS protein expressions (P < 0.05). A total of 48 constituents in VORA were identified by GC-MS in comparison with reference standards as well as the reference pieces of literatures. Conclusions: HPH rat model as established based on the significant increased mPAP and RVHI. VORA presented a significant antihypoxia function plus an inhibiting effect on PASMC proliferation induced by hypoxia. Moreover, VORA treatment inhibited oxidative stress among PASMCs. With regard to the mechanism, VORA reduced ACE, AngII, and AT1R protein expressions but increased ACE2 and MAS protein expressions. There were 48 constituents in VORA identified by GC-MS.

A novel cuproptosis-related lncRNA signature predicts prognosis and therapeutic response in bladder cancer.

Bladder cancer (BC) ranks the tenth in the incidence of global tumor epidemiology. LncRNAs and cuproptosis were discovered to regulate the cell death. Herein, we downloaded transcriptome profiling, mutational data, and clinical data on patients from The Cancer Genome Atlas (TCGA). High- and low-risk BC patients were categorized. Three CRLs (AL590428.1, AL138756.1 and GUSBP11) were taken into prognostic signature through least absolute shrinkage and selection operator (LASSO) Cox regression. Worse OS and PFS were shown in high-risk group (p < 0.05). ROC, independent prognostic analyses, nomogram and C-index were predicted via CRLs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated IncRNAs play a biological role in BC progression. Immune-related functions showed the high-risk group received more benefit from immunotherapy and had stronger immune responses, and the overall survival was better (p < 0.05). Finally, a more effective outcome (p < 0.05) was found from clinical immunotherapy via the TIDE algorithm and many potential anti-tumor drugs were identified. In our study, the cuproptosis-related signature provided a novel tool to predict the prognosis in BC patients accurately and provided a novel strategy for clinical immunotherapy and clinical applications.

A Novel Ferroptosis-Related Prognostic Signature Reveals Macrophage Infiltration and EMT Status in Bladder Cancer.

Bladder cancer (BC) belongs to one of the most common and highly heterogeneous malignancies. Ferroptosis is a newly discovered regulated cell death (RCD), characterized by accumulation of toxic lipid peroxides, and plays a crucial role in tumor progression. Here, we conducted a comprehensive analysis on the transcriptomics data of ferroptosis-related genes in BC based on The Cancer Genome Atlas (TCGA) and three Gene Expression Omnibus (GEO) datasets. In our study, a 6-gene signature was identified based on the potential prognostic ferroptotic regulatory genes. Furthermore, our signature revealed a good independent prognostic ability in BC. Patients with low-risk score exhibited higher FGFR3 mutation rates while high risk score had a positive association with higher RB1 mutation rates. Meanwhile, higher proportions of macrophages were observed in high BC risk group simultaneously with four methods. Unexpectedly, the risk score showed a significant positive correlation with epithelial-mesenchymal transition (EMT) status. Functional assays indicated that CRYAB and SQLE knockdown was associated with attenuated invasion capacity. Our study revealed a ferroptosis-related risk model for predicting prognostic and BC progression. Our results indicate that targeting ferroptosis may be a therapeutic strategy for BC.

PDE4B Induces Epithelial-to-Mesenchymal Transition in Bladder Cancer Cells and Is Transcriptionally Suppressed by CBX7.

Urinary bladder cancer (UBC) is a common malignant tumor with high incidence. Advances in the diagnosis and treatment of this disease demand the identification of novel therapeutic targets. Multiple studies demonstrated that PDE4B level was upregulated in malignancies and high PDE4B expression was correlated with poor outcomes. Herein, we identified that PDE4B was a potential therapeutic target in UBC. We confirmed that PDE4B expression was correlated with aggressive clinicopathological characteristics and unfavorable prognosis. Functional studies demonstrated that ectopic expression of PDE4B promoted UBC cells proliferation, migration and invasion, whereas PDE4B depletion suppressed cancer cell aggressiveness. We also identified CBX7 as a regulator of PDE4B to suppress the expression of PDE4B at the transcription level in a PRC1-dependent manner. Moreover, our results indicated that PDE4B induced epithelial-to-mesenchymal transition (EMT) in UBC cells via ß-catenin pathway, whereas inhibition of PDE4B by its small molecule inhibitor, rolipram, effectively reversed the PDE4B overexpression-induced effects. To sum up, our results indicated that PDE4B acts as an oncogene by promoting UBC cell migration and invasion via ß-catenin/EMT pathway.