Long-term survival outcomes and immune checkpoint inhibitor retreatment in patients with advanced cervical cancer treated with camrelizumab plus apatinib in the phase II CLAP study.

BACKGROUND: Camrelizumab plus apatinib have demonstrated robust antitumor activity and safety in patients with advanced cervical cancer (CLAP study; NCT03816553). We herein present the updated long-term results of the CLAP study and explore potential biomarkers for survival. The outcomes of patients who underwent immune checkpoint inhibitor (ICI) retreatment were also reported. METHODS: In this phase II trial, eligible patients received camrelizumab 200 mg intravenously every two weeks and apatinib 250 mg orally once daily in 4-week cycles for up to two years. Treatment was continued until disease progression, unacceptable toxicity, or withdrawal of consent. RESULTS: Between January 21 and August 1, 2019, a total of 45 patients were enrolled. Data were analyzed as of July 31, 2023, representing > 48 months since treatment initiation for all patients. Nine (20.0%) patients completed the 2-year study. The median duration of response (DOR) was 16.6 months, and 45.0% of patients achieved a DOR of ≥ 24 months. The 12-month progression-free survival (PFS) rate was 40.7% (95% confidence interval [CI], 25.2-55.6), with an 18-month PFS rate of 37.8% (95% CI, 22.7-52.8). The median overall survival (OS) was 20.3 months (95% CI, 9.3-36.9), and the 24-month OS rate was 47.8% (95% CI, 31.7-62.3). Age > 50 years, programmed death-ligand 1 (PD-L1) combined positive score (CPS) ≥ 1 (versus [vs.] < 1), CPS ≥ 10 (vs. < 1), high tumor mutational burden, and PIK3CA mutations were associated with improved PFS (hazard ratio [HR] < 1) and longer OS (HR < 1). Eight patients who initially responded in the CLAP trial but later experienced disease progression were retreated with ICIs. Among them, 2 (25.0%) achieved a partial response, while 5 (62.5%) had stable disease. Notably, four patients who received retreatment with ICIs survived for more than 45 months. No new safety signals were identified in the present study. CONCLUSION: Long-term survival follow-up data demonstrated that camrelizumab plus apatinib has robust, sustained, and durable efficacy in patients with advanced cervical cancer who progress after first-line platinum-based chemotherapy. No new safety signals were noted with long-term treatment.

Clinical features and comprehensive treatment of persistent corneal epithelial dysfunction after cataract surgery.

OBJECTIVE: Evaluation of clinical efficacy and safety of tobramycin/dexamethasone eye ointment in treating persistent corneal epithelial dysfunction (PED) after cataract surgery. METHODS: 26 cases diagnosed as PED after cataract surgery accept the tobramycin/dexamethasone ophthalmic ointment and intense pulse light treatment in the Xiamen University of Xiamen eye center between September 2016 and April 2022 were retrospectively analyzed, mainly including clinical manifestations, characteristics of morphological changes imaged by in vivo confocal microscopy, meibomian glands infrared photography, lipid layer thickness (LLT), management and therapeutic effects. RESULTS: There were 26 eyes, include 8(35%) males and 15(65%) females with an average age of 69.6 ± 5.2 years(50 to 78 years). The mean hospitalization time was (18.4 ± 7.5) days after cataract surgery. Twenty patients had meibomian gland dysfunction. Infrared photography revealed varying loss in the meibomian glands, with a mean score of 3.8 ± 1.2 for gland loss. The mean LLT was 61.6 ± 8.4 nm. After treatment, 20 patients were cured, and 3 received amniotic membrane transplantation. After treatment, the uncorrected visual acuity (UCVA) and best-corrected vision activity (BCVA) improved (P < 0.001), and there was no significant difference in intraocular pressure (IOP) before and after treatment (P > 0.05). CONCLUSIONS: The early manifestation of PED after surgery is punctate staining of the corneal epithelium. Tobramycin and dexamethasone eye ointment bandages have a good repair effect. The meibomian gland massage combined with intense pulse light treatment can effectively shorten the course of the disease.

The fatty acid-related gene signature stratifies poor prognosis patients and characterizes TIME in cutaneous melanoma.

BACKGROUND: The aim of this study is to build a prognostic model for cutaneous melanoma (CM) using fatty acid-related genes and evaluate its capacity for predicting prognosis, identifying the tumor immune microenvironment (TIME) composition, and assessing drug sensitivity. METHODS: Through the analysis of transcriptional data from TCGA-SKCM and GTEx datasets, we screened for differentially expressed fatty acids-related genes (DEFAGs). Additionally, we employed clinical data from TCGA-SKCM and GSE65904 to identify genes associated with prognosis. Subsequently, utilizing all the identified prognosis-related fatty acid genes, we performed unsupervised clustering analysis using the ConsensusClusterPlus R package. We further validated the significant differences between subtypes through survival analysis and pathway analysis. To predict prognosis, we developed a LASSO-Cox prognostic signature. This signature's predictive ability was rigorously examined through multivariant Cox regression, survival analysis, and ROC curve analysis. Following this, we constructed a nomogram based on the aforementioned signature and evaluated its accuracy and clinical utility using calibration curves, cumulative hazard rates, and decision curve analysis. Using this signature, we stratified all cases into high- and low-risk groups and compared the differences in immune characteristics and drug treatment responsiveness between these two subgroups. Additionally, in this study, we provided preliminary confirmation of the pivotal role of CD1D in the TIME of CM. We analyzed its expression across various immune cell types and its correlation with intercellular communication using single-cell data from the GSE139249 dataset. RESULTS: In this study, a total of 84 DEFAGs were identified, among which 18 were associated with prognosis. Utilizing these 18 prognosis-related genes, all cases were categorized into three subtypes. Significant differences were observed between subtypes in terms of survival outcomes, the expression of the 18 DEFAGs, immune cell proportions, and enriched pathways. A LASSO-Cox regression analysis was performed on these 18 genes, leading to the development of a signature comprising 6 DEFAGs. Risk scores were calculated for all cases, dividing them into high-risk and low-risk groups. High-risk patients exhibited significantly poorer prognosis than low-risk patients, both in the training group (p < 0.001) and the test group (p = 0.002). Multivariate Cox regression analysis indicated that this signature could independently predict outcomes [HR = 2.03 (1.69-2.45), p < 0.001]. The area under the ROC curve for the training and test groups was 0.715 and 0.661, respectively. Combining risk scores with clinical factors including metastatic status and patient age, a nomogram was constructed, which demonstrated significant predictive power for 3  and 5 years patient outcomes. Furthermore, the high and low-risk subgroups displayed differences in the composition of various immune cells, including M1 macrophages, M0 macrophages, and CD8+ T cells. The low-risk subgroup exhibited higher StromalScore, ImmuneScore, and ESTIMATEScore (p < 0.001) and demonstrated better responsiveness to immune therapy for patients with PD1-positive and CTLA4-negative or positive expressions (p < 0.001). The signature gene CD1D was found to be mainly expressed in monocytes/macrophages and dendritic cells within the TIME. Through intercellular communication analysis, it was observed that cases with high CD1D expression exhibited significantly enhanced signal transductions from other immune cells to monocytes/macrophages, particularly the (HLA-A/B/C/E/F)-CD8A signaling from natural killer (NK) cells to monocytes/macrophages (p < 0.01). CONCLUSIONS: The prognostic signature constructed in this study, based on six fatty acid-related genes, exhibits strong capabilities in predicting patient outcomes, identifying the TIME, and assessing drug sensitivity. This signature can aid in patient risk stratification and provide guidance for clinical treatment strategies. Additionally, our research highlights the crucial role of CD1D in the CM's TIME, laying a theoretical foundation for future related studies.

Evaluation of lymphotoxin-alpha in pterygium and diagnostic value in active and inactive pterygium states.

To explore the correlation between tear LT-a, pterygium status, and dry eye indicators. We established a diagnostic model to evaluate active pterygium. A retrospective study was conducted between June 2021 and June 2023 on 172 patients, comprising 108 men and 64 women. The study analyzed LT-a and various ocular parameters in all participants. The data was collected using Excel software and analyzed using SPSS 25.0 statistical software and Medcalc. We made a nomogram diagnostic model to different diagnosed the state of pterygium. This study found that pterygium has progressive eye surface damage during the active state. There was no significant difference in dry eye indicators between the two groups. However, the concentration of LT-a in the active group was significantly lower than that in the inactive group (P < 0.001). We observed that increased pterygium grade corresponded to a worse ocular surface condition. In addition, LT-a was significantly positively correlated with disease duration, but negatively correlated with age, pterygium size, active pterygium state, and LLT value. The optimal intercept value for evaluating active pterygium in Lt-a was ≤ 0.49 dg/ml. We screened three variables for evaluating active pterygium through Single and Multiple regression analysis: LT-a grading, pterygium size, and congestion score. Finally, we made a reliable diagnostic nomogram model. Pterygium development triggers immune inflammation. Our model based on LT-a identifies active pterygium for personalized treatment options and new research directions.

Maternal exposure to dibutyl phthalate (DBP) impairs angiogenesis and AR signalling pathway through suppression of TGFB1I1 in hypospadias offspring.

Early exposure to dibutyl phthalate (DBP) can cause hypospadias in newborn foetuses. However, the underlying molecular mechanism is not well defined. Aberrant angiogenesis is associated with various dysplasias including urogenital deficits. In vivo and in vitro angiogenesis assays showed reduced angiogenesis in the hypospadias group and DBP exposed group. RNA-sequencing analysis of DBP-treated HUVECs revealed decreased expression of transforming growth factor beta 1-induced transcript 1 (TGFB1I1) and a significantly enriched angiogenesis-associated pathway. Further experiments revealed that decreased TGFB1I1 expression was associated with disrupted tube formation and migration, which resulted in decreased angiogenesis. Functional assays revealed that the overexpression of TGFB1I1 promoted tube formation and migration of HUVECs in the DBP-treated group. Moreover, we showed that the transcription factor AR was regulated by TGFB1I1 through inhibiting its translocation from the cytoplasm to the nucleus. Together, our results identified TGFB1I1 as a component of aberrant angiogenesis in hypospadias rats and its interaction with AR might be a potential target for hypospadias development.

Integrating single-cell and bulk RNA sequencing data unveils antigen presentation and process-related CAFS and establishes a predictive signature in prostate cancer.

BACKGROUND: Cancer-associated fibroblasts (CAFs) are heterogeneous and can influence the progression of prostate cancer in multiple ways; however, their capacity to present and process antigens in PRAD has not been investigated. In this study, antigen presentation and process-related CAFs (APPCAFs) were identified using bioinformatics, and the clinical implications of APPCAF-related signatures in PRAD were investigated. METHODS: SMART technology was used to sequence the transcriptome of primary CAFs isolated from patients undergoing different treatments. Differential expression gene (DEG) screening was conducted. A CD4 + T-cell early activation assay was used to assess the activation degree of CD4 + T cells. The datasets of PRAD were obtained from The Cancer Genome Atlas (TCGA) database and NCBI Gene Expression Omnibus (GEO), and the list of 431 antigen presentation and process-related genes was obtained from the InnateDB database. Subsequently, APP-related CAFs were identified by nonnegative matrix factorization (NMF) based on a single-cell seq (scRNA) matrix. GSVA functional enrichment analyses were performed to depict the biological functions. A risk signature based on APPCAF-related genes (APPCAFRS) was developed by least absolute shrinkage and selection operator (LASSO) regression analysis, and the independence of the risk score as a prognostic factor was evaluated by univariate and multivariate Cox regression analyses. Furthermore, a biochemical recurrence-free survival (BCRFS)-related nomogram was established, and immune-related characteristics were assessed using the ssGSEA function. The immune treatment response in PRAD was further analyzed by the Tumor Immune Dysfunction and Exclusion (TIDE) tool. The expression levels of hub genes in APPCAFRS were verified in cell models. RESULTS: There were 134 upregulated and 147 downregulated genes, totaling 281 differentially expressed genes among the primary CAFs. The functions and pathways of 147 downregulated DEGs were significantly enriched in antigen processing and presentation processes, MHC class II protein complex and transport vesicle, MHC class II protein complex binding, and intestinal immune network for IgA production. Androgen withdrawal diminished the activation effect of CAFs on T cells. NMF clustering of CAFs was performed by APPRGs, and pseudotime analysis yielded the antigen presentation and process-related CAF subtype CTSK + MRC2 + CAF-C1. CTSK + MRC2 + CAF-C1 cells exhibited ligand‒receptor connections with epithelial cells and T cells. Additionally, we found a strong association between CTSK + MRC2 + CAF-C1 cells and inflammatory CAFs. Through differential gene expression analysis of the CTSK + MRC2 + CAF-C1 and NoneAPP-CAF-C2 subgroups, 55 significant DEGs were identified, namely, APPCAFRGs. Based on the expression profiles of APPCAFRGs, we divided the TCGA-PRAD cohort into two clusters using NMF consistent cluster analysis, with the genetic coefficient serving as the evaluation index. Four APPCAFRGs, THBS2, DPT, COL5A1, and MARCKS, were used to develop a prognostic signature capable of predicting BCR occurrence in PRAD patients. Subsequently, a nomogram with stability and accuracy in predicting BCR was constructed based on Gleason grade (p = n.s.), PSA (p < 0.001), T stage (p < 0.05), and risk score (p < 0.01). The analysis of immune infiltration showed a positive correlation between the abundance of resting memory CD4 + T cells, M1 macrophages, resting dendritic cells, and the risk score. In addition, the mRNA expression levels of THBS2, DPT, COL5A1, and MARCKS in the cell models were consistent with the results of the bioinformatics analysis. CONCLUSIONS: APPCAFRS based on four potential APPCAFRGs was developed, and their interaction with the immune microenvironment may play a crucial role in the progression to castration resistance of PRAD. This novel approach provides valuable insights into the pathogenesis of PRAD and offers unexplored targets for future research.

Clinical and Morphological in Vivo Confocal Microscopy Findings following a Modified Biphasic Higher Fluence Transepithelial Corneal Crosslinking.

Purpose: To compare the refractive efficacy and morphological changes in the cornea following a novel biphasic higher fluence transepithelial corneal crosslinking (BI-TE-CXL) and transepithelial corneal crosslinking (TE-CXL) in adults keratoconus.Methods: Patients with progressive keratoconus who required corneal crosslinking were assigned to the BI-TE-CXL group (32 eyes, phase 1: 7.2 J/cm2 for 5 min and 20 s of pulsed-light exposure, KXL, Glaukos-Avedro; phase 2: 3.6 J/cm2 for 6 min and 40 s of continuous light exposure at the front curvature apex with a 6 mm diameter light spot, UVX-2000, IROC) or the TE-CXL group (32 eyes, uniform 7.2 J/cm2 for 5 min and 20 s of pulsed-light exposure, KXL, Glaukos-Avedro). Uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), corneal fluorescein staining (CFS), corneal topography, anterior segment optical coherence tomography (AS-OCT), and in vivo corneal confocal microscopy (IVCM) were performed 3, 6, 12 and 24 months after surgery.Results: The CFS scores in the BI-TE-CXL group were significantly higher than those in the TE-CXL group on the first two days after surgery (p < 0.001). The Kmax (at 12 and 24 months) and CDVA (logMAR) were significantly lower in the BI-TE-CXL group than those in the TE-CXL group (p < 0.05). The corneal demarcation line under AS-OCT was visible in 81.3% of patients in the BI-TE-CXL group and 15.6% in the TE-CXL group. The depth of the demarcation line under IVCM was significantly deeper in the BI-TE-CXL group (248.3 ± 25.0 µm) than that of the TE-CXL group (136.5 ± 15.6 µm) in the central cornea (p < 0.001). The cross-linked collagen structures in the central cornea were still present after 12 months in the BI-TE-CXL group. No significant difference in sub-basal nerve density between the two groups (p > 0.05).Conclusions: Following BI-TE-CXL, CDVA was significantly improved, accompanied by deeper demarcation line depth and persistent crosslinked structures in the central corneal stroma.

Relation Between Corneal Dendritic Cell Density and Tear Film Stability in Patients with Epidemic Keratoconjunctivitis Associated Dry Eye.

PURPOSE: To clarify the ocular surface features of patients with recent history of epidemic keratoconjunctivitis (EKC) and the relation between corneal dendritic cells (DCs) and ocular discomfort. METHODS: Normal controls (NC) and dry eye (DE) patients without EKC were recruited. Patients with recent EKC history (onset >4 weeks, but <20 weeks) were recruited as EKC + DE group (with dry eye) or EKC-DE group (without dry eye). Ocular surface disease index (OSDI) questionnaire, tear film parameters including lipid layer thickness, first tear break-up time (fBUT), average tear break-up time (aBUT), tear meniscus height and Schirmer I test, meibomian gland parameters, and in vivo corneal confocal microscopy were evaluated. RESULTS: 50 subjects in the NC group, 83 patients in the DE group, 76 patients in the EKC + DE group, and 38 patients in the EKC-DE group were included. Compared with the NC, DE, and EKC-DE groups, the EKC + DE group represented higher OSDI, lid margin, and meibum score (p < 0.05). In the EKC + DE group, the tear volume (10.5 ± 3.7 mm) was significantly higher than in the DE group (8.1 ± 2.8 mm, p < 0.001). The DC density in the EKC + DE group (29.98 ± 15.38 cells/image) was significantly higher than in NC, DE, and EKC-DE groups (4.68 ± 4.05 cells/image) (p < 0.001). The DC density was positively correlated with OSDI, lid margin, and meibum score (all p < 0.01) while inversely correlated with fBUT, aBUT (all p < 0.001) in the EKC + DE group. CONCLUSIONS: Corneal DC density significantly correlates to ocular discomfort and tear film instability in patients with recent EKC history who suffer from DE without aqueous tear deficiency.

The clinicopathological analysis of ocular and orbit tumors in southeast of China.

Purpose: The purpose of this study is to describe the clinicopathologic characteristics of ocular surface and orbit tumors in the Southeast of China and explore the method to differentiate the benign and malignant masses. Materials and methods: 3468 patients undergoing mass resection from January 2015 to December 2020 were selected as observation subjects and were classified into benign and malignant masses according to postoperative pathology. The clinicopathologic characteristics were collected, including gender, age, pathological tissue signs, and pathological signs. Multivariate Logistic regression analysis of independent risk factors of malignant mass was applied to establish a diagnostic model and the efficacy was evaluated by the subject working characteristics (ROC) curve. Results: Benign tumors accounted for 91.5% of all cases, and malignant tumors accounted for 8.5%. The most common ocular benign tumors were nevi (24.2%), granuloma (17.1%), and cysts (16.4%). The most common ocular malignant tumors were malignant lymphoma (32.1%) and Basal cell carcinoma (20.2%). As for the histologic origin, melanocytic origin was on the list with 819 (23.6%), mesenchymal 661 (19.1%), epithelial 568 (16.3%), cystic 521 (15.0%), skin adnexal 110 (3.1%), lymphoid 94 (2.8%), and Neural 25(0.8%). Based on the gender, age, tumor location, and the pathological tissue image feature (including differentiation, structural atypia, covering epithelial, keratosis, nest structure/distribution, nuclear atypia, cytoplasmic change and nuclear division), the diagnostic model had predictive value to differentiate the benign and malignant masses. Conclusion: Most ocular surface and orbit tumors are benign. Tumor diagnosis is relative to the patient's age, gender, tumor location, and pathologic characteristics. We generated a satisfactory diagnostic model to differential diagnosis of benign and malignant masses.

Identification and validation of cancer-associated fibroblast-related subtypes and the prognosis model of biochemical recurrence in prostate cancer based on single-cell and bulk RNA sequencing.

BACKGROUND: Cancer-associated fibroblasts (CAFs) are an essential component of the tumor immune microenvironment that are involved in extracellular matrix (ECM) remodeling. We aim to investigate the characteristics of CAFs in prostate cancer and develop a biochemical recurrence (BCR)-related CAF signature for predicting the prognosis of PCa patients. METHODS: The bulk RNA-seq and relevant clinical information were obtained from the TCGA and GEO databases, respectively. The infiltration scores of CAFs in prostate cancer patients were calculated using the MCP counter and EPIC algorithms. The single-cell RNA sequencing (scRNA-seq) was downloaded from the GEO database. Subsequently, univariate Cox regression analysis was employed to identify prognostic genes associated with CAFs. We identified two subtypes (C1 and C2) of prostate cancer that were associated with CAFs via non-negative matrix factorization (NMF) clustering. In addition, the BCR-related CAF signatures were constructed using Lasso regression analysis. Finally, a nomogram model was established based on the risk score and clinical characteristics of the patients. RESULTS: Initially, we found that patients with high CAF infiltration scores had shorter biochemical recurrence-free survival (BCRFS) times. Subsequently, CAFs in four pairs of tumors and paracancerous tissues were identified. We discovered 253 significantly differentially expressed genes, of which 13 had prognostic significance. Using NMF clustering, we divided PCa patients into C1 and C2 subgroups, with the C1 subgroup having a worse prognosis and substantially enriched cell cycle, homologous recombination, and mismatch repair pathways. Furthermore, a BCR-related CAFs signature was established. Multivariate COX regression analysis confirmed that the BCR-related CAFs signature was an independent prognostic factor for BCR in PCa. In addition, the nomogram was based on the clinical characteristics and risk scores of the patient and demonstrated high accuracy and reliability for predicting BCR. Lastly, our findings indicate that the risk score may be a useful tool for predicting PCa patients' sensitivity to immunotherapy and drug treatment. CONCLUSION: NMF clustering based on CAF-related genes revealed distinct TME immune characteristics between groups. The BCR-related CAF signature accurately predicted prognosis and immunotherapy response in prostate cancer patients, offering a promising new approach to cancer treatment.

A nomogram for predicting the risk of residual stone fragments after ureteroscopy.

Background: The residual stone fragment is a tremendous issue after ureteroscopic lithotripsy and requires urologists to evaluate the condition of patients comprehensively. Our study aimed to construct a nomogram to make a personalized prediction of postoperative residual stone rate (RSR). Methods: We implemented a retrospective cohort study in the Department of Urology, Shanghai General Hospital. A total of 277 patients undergoing ureteroscopy (URS) were enrolled in our study. Among them, 186 patients were included in the training group and the remaining 91 patients comprised the testing group. We utilized stepwise forward algorithm and logistic regression analysis to build predictive models and selected the best model based on Akaike's information criterion (AIC). The model was assessed by receiver operating characteristic (ROC) curves and the Hosmer-Lemeshow (HL) test. We also conducted decision curve analysis (DCA) to demonstrate the net benefit of the model. The independent testing group was used to validate the practicability of the nomogram. Results: The severity of hydronephrosis, stone location, the transverse diameter of stone, hypertension, and white blood cell (WBC) were found to be significant predictive variables for RSR after URS. The area under the curve (AUC) of the training group was 0.7203 and that of the testing group was 0.7280. Besides, the nomogram also presented great calibration and accepted net benefit in a wide range of probabilities. Conclusions: Our study achieved a predictive nomogram with excellent application value for urologists to assess RSR and make personalized treatment decisions.

Di-n-butyl phthalate induces oversecretion of vascular endothelium-derived NAP-2 and promotes epithelial-mesenchymal transition of urothelial cells in newborn hypospadias rats.

Di-n-butyl phthalate (DBP) is a plasticizer commonly used in industrial production and is present in our daily life. It has been confirmed that DBP causes genitourinary malformations, especially hypospadias. However, the research of hypospadias mainly focusses on the genital tubercle in previous studies. In this study, we found DBP could affect the exocrine function of the vascular endothelium which disturb the development of genital nodules and induced hypospadias. We used cytokine array to find that vascular endothelium-derived NAP-2 may be a major abnormal secreted cytokine with biological functions. The transcriptomic sequencing analysis showed that abnormal activation of the RhoA/ROCK signaling pathway was the main reason for increased NAP-2 secretion. The expression levels of epithelial-mesenchymal transition (EMT) biomarkers and NAP-2 in hypospadias animal models were detected with Immunohistochemistry, Western blot, Immunofluorescence, and ELISA methods. The expression levels of NAP-2, RhoA/ROCK signaling pathway related proteins, reactive oxygen species (ROS) levels in HUVEC cells, EMT biomarkers and migration capacity of urothelial cells cocultured with HUVEC were measured with ELISA, flow cytometry, Western blot or Transwell assay for further cell experiments. The results showed that DBP leaded to NAP-2 oversecretion from vascular endothelium mainly rely on the activation of RhoA/ROCK signaling pathway and ROS accumulation. The RhoA/ROCK inhibitor fasudil could partially decrease ROS production, and both fasudil and N-acetyl-L-cysteine (NAC) could decrease NAP-2 secretion. Meanwhile, the oversecretion of NAP-2 from HUVEC in coculture system promoted EMT and migration capacity of urothelial cells, and TGF-ß inhibitor LY219761 could block the aberrant activation of EMT process. Therefore, it could be concluded that DBP increase NAP-2 secretion from vascular endothelium by RhoA/ROCK/ROS pathway, and further promote EMT in urothelial cells through TGF-ß pathway. This study provided a novel direction for studying the occurrence of hypospadias and may provide a hypospadias predictive marker in the future.

Histopathology-based diagnosis of Mooren's ulcer concealed beneath the pterygium on eye.

Mooren's ulcer (MU) is a chronic and painful ulcerative keratitis that is difficult to diagnose, especially when concealed beneath the pterygium, which is a common, benign, wedge-shaped, fleshy tissue growth of the conjunctiva extending onto the cornea. The coexistence of MU and pterygium is extremely rare. A 41-year-old man presented with a 2-month history of unprovoked redness, pain, and blurred vision in the right eye. Corneal epithelial defects around the pterygium head were noted upon slit-lamp examination and fluorescein staining. The patient was initially misdiagnosed with a corneal epithelial defect and pterygium. The initial treatments with anti-inflammatory and corneal epithelial growth promotion tear agents failed. Anterior segment optical coherence tomography (AS-OCT) showed corneal stromal lysis thinning, and in vivo confocal microscopy (IVCM) revealed marked inflammatory cell infiltration and stromal degeneration. We suspected the pathology was an immune-related or tumor-related corneal ulcer. The MU concealed beneath the pterygium was diagnosed by histopathological examination of a biopsy specimen that presented typical localized loss of the corneal epithelium and Bowman's layer, stromal degeneration, and inflammatory cell infiltration. Finally, we performed lamellar keratoplasty (LKP) combined with pterygium excision surgery. The patient recovered with no complications or recurrence during the 1-year follow-up period. Few cases of MU concealed beneath the pterygium have been reported. It is beneficial to rule out the pathological changes concealed beneath the pterygium, combined with multiple means of examination such as slit-lamp examination, AS-OCT, and IVCM. A histopathological examination should be performed to establish a diagnosis.

A novel diagnostic four-gene signature for hepatocellular carcinoma based on artificial neural network: Development, validation, and drug screening.

Background: Hepatocellular carcinoma (HCC) is one of the most common cancers with high mortality in the world. HCC screening and diagnostic models are becoming effective strategies to reduce mortality and improve the overall survival (OS) of patients. Here, we expected to establish an effective novel diagnostic model based on new genes and explore potential drugs for HCC therapy. Methods: The gene expression data of HCC and normal samples (GSE14811, GSE60502, GSE84402, GSE101685, GSE102079, GSE113996, and GSE45436) were downloaded from the Gene Expression Omnibus (GEO) dataset. Bioinformatics analysis was performed to distinguish two differentially expressed genes (DEGs), diagnostic candidate genes, and functional enrichment pathways. QRT-PCR was used to validate the expression of diagnostic candidate genes. A diagnostic model based on candidate genes was established by an artificial neural network (ANN). Drug sensitivity analysis was used to explore potential drugs for HCC. CCK-8 assay was used to detect the viability of HepG2 under various presentative chemotherapy drugs. Results: There were 82 DEGs in cancer tissues compared to normal tissue. Protein-protein interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and infiltrating immune cell analysis were administered and analyzed. Diagnostic-related genes of MT1M, SPINK1, AKR1B10, and SLCO1B3 were selected from DEGs and used to construct a diagnostic model. The receiver operating characteristic (ROC) curves were 0.910 and 0.953 in the training and testing cohorts, respectively. Potential drugs, including vemurafenib, LOXO-101, dabrafenib, selumetinib, Arry-162, and NMS-E628, were found as well. Vemurafenib, dabrafenib, and selumetinib were observed to significantly affect HepG2 cell viability. Conclusion: The diagnostic model based on the four diagnostic-related genes by the ANN could provide predictive significance for diagnosis of HCC patients, which would be worthy of clinical application. Also, potential chemotherapy drugs might be effective for HCC therapy.

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.

Identification and validation of an immune-related gene prognostic signature for clear cell renal carcinoma.

Clear Cell Renal Carcinoma (ccRCC) accounts for nearly 80% of renal carcinoma cases, and immunotherapy plays an important role in ccRCC therapy. However, the responses to immunotherapy and overall survival for ccRCC patients are still hard to predict. Here, we constructed an immune-related predictive signature using 19 genes based on TCGA datasets. We also analyzed its relationships between disease prognosis, infiltrating immune cells, immune subtypes, mutation load, immune dysfunction, immune escape, etc. We found that our signature can distinguish immune characteristics and predict immunotherapeutic response for ccRCC patients with better prognostic prediction value than other immune scores. The expression levels of prognostic genes were determined by RT-qPCR assay. This signature may help to predict overall survival and guide the treatment for patients with ccRCC.

GFCNet: Utilizing graph feature collection networks for coronavirus knowledge graph embeddings.

In response to fighting COVID-19 pandemic, researchers in machine learning and artificial intelligence have constructed some medical knowledge graphs (KG) based on existing COVID-19 datasets, however, these KGs contain a considerable amount of semantic relations which are incomplete or missing. In this paper, we focus on the task of knowledge graph embedding (KGE), which serves an important solution to infer the missing relations. In the past, there have been a collection of knowledge graph embedding models with different scoring functions to learn entity and relation embeddings published. However, these models share the same problems of rarely taking important features of KG like attribute features, other than relation triples, into account, while dealing with the heterogeneous, complex and incomplete COVID-19 medical data. To address the above issue, we propose a graph feature collection network (GFCNet) for COVID-19 KGE task, which considers both neighbor and attribute features in KGs. The extensive experiments conducted on the COVID-19 drug KG dataset show promising results and prove the effectiveness and efficiency of our proposed model. In addition, we also explain the future directions of deepening the study on COVID-19 KGE task.

Identification and Validation of Prognostic Model for Pancreatic Ductal Adenocarcinoma Based on Necroptosis-Related Genes.

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors with a poor prognosis. Recently, necroptosis has been reported to participate in the progression of multiple tumors. However, few studies have revealed the relationship between necroptosis and PDAC, and the role of necroptosis in PDAC has not yet been clarified. Methods: The mRNA expression data and corresponding clinical information of PDAC patients were downloaded from the TCGA and GEO databases. The necroptosis-related genes (NRGs) were obtained from the CUSABIO website. Consensus clustering was performed to divide PDAC patients into two clusters. Univariate and LASSO Cox regression analyses were applied to screen the NRGs related to prognosis to construct the prognostic model. The predictive value of the prognostic model was evaluated by Kaplan-Meier survival analysis and ROC curve. Univariate and multivariate Cox regression analyses were used to evaluate whether the risk score could be used as an independent predictor of PDAC prognosis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and single-sample gene set enrichment analysis (ssGSEA) were used for functional enrichment analysis. Finally, using qRT-PCR examined NRGs mRNA expression in vitro. Results: Based on the TCGA database, a total of 22 differential expressed NRGs were identified, among which eight NRGs (CAPN2, CHMP4C, PLA2G4F, PYGB, BCL2, JAK3, PLA2G4C and STAT4) that may be related to prognosis were screened by univariate Cox regression analysis. And CAPN2, CHMP4C, PLA2G4C and STAT4 were further selected to construct the prognostic model. Kaplan-Meier survival analysis and ROC curve showed that there was a significant correlation between the risk model and prognosis. Univariate and multivariate Cox regression analyses showed that the risk score of the prognostic model could be used as an independent predictor. The model efficacy was further demonstrated in the GEO cohort. Functional analysis revealed that there were significant differences in immune status between high and low-risk groups. Finally, the qRT-PCR results revealed a similar dysregulation of NRGs in PDAC cell lines. Conclusion: This study successfully constructed and verified a prognostic model based on NRGs, which has a good predictive value for the prognosis of PDAC patients.

Identification of Feature Genes of a Novel Neural Network Model for Bladder Cancer.

Background: The combination of deep learning methods and oncogenomics can provide an effective diagnostic method for malignant tumors; thus, we attempted to construct a reliable artificial neural network model as a novel diagnostic tool for Bladder cancer (BLCA). Methods: Three expression profiling datasets (GSE61615, GSE65635, and GSE100926) were downloaded from the Gene Expression Omnibus (GEO) database. GSE61615 and GSE65635 were taken as the train group, while GSE100926 was set as the test group. Differentially expressed genes (DEGs) were filtered out based on the logFC and FDR values. We also performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to explore the biological functions of the DEGs. Consequently, we utilized a random forest algorithm to identify feature genes and further constructed a neural network model. The test group was given the same procedures to validate the reliability of the model. We also explored immune cells' infiltration degree and correlation coefficients through the CiberSort algorithm and corrplot R package. The qRT-PCR assay was implemented to examine the expression level of the feature genes in vitro. Results: A total of 265 DEGs were filtered out and significantly enriched in muscle system processes, collagen-containing and focal adhesion signaling pathways. Based on the random forest algorithm, we selected 14 feature genes to construct the neural network model. The area under the curve (AUC) of the training group was 0.950 (95% CI: 0.850-1.000), and the AUC of the test group was 0.667 (95% CI: 0.333-1.000). Besides, we observed significant differences in the content of immune infiltrating cells and the expression levels of the feature genes. Conclusion: After repeated verification, our neural network model had clinical feasibility to identify bladder cancer patients and provided a potential target to improve the management of BLCA.

Wear Resistance and Biocompatibility of Co-Cr Dental Alloys Fabricated with CAST and SLM Techniques.

Cobalt-chromium (Co-Cr) alloys have been widely used as dental-restoration materials for many years. This study sought to investigate whether selective laser melting (SLM) is a more appropriate process than traditional casting (CAST) for fabricating dental Co-Cr alloys. Metallurgical microscopy, X-ray photoelectron spectroscopy (XPS), Vickers hardness and nanoindentation tests, and friction and wear tests were used to evaluate the microstructure, surface compositions, mechanical properties, and wear resistance, respectively. Additionally, the biocompatibilities and cell adhesion of the alloys were evaluated with L-929 fibroblasts via CCK-8 assay, Live/Dead staining, flow cytometric analysis, scanning electron microscopy (SEM) observation and real-time PCR (RT-PCR) assay. The XPS results showed that the two alloys were all mainly comprised of Co, Cr, and O. The hardness in the CAST group equaled 7.15 ± 0.48 GPa, while in the SLM group, it equaled 9.06 ± 0.49 GPa. The friction coefficient of SLM alloys remained at approximately 0.46, but the CAST specimens fluctuated significantly. SLM alloys exhibited shallower wear scars and less wear debris compared with CAST alloys, simultaneously. Additionally, there were higher survival and expression of cell-adhesion-related genes on SLM alloys of L-929 cells, which meant that the deleterious effect on L-929 cells was significantly reduced compared with that for the CAST alloys. Overall, the wear resistances and biocompatibilities of the Co-Cr dental alloys were dramatically affected by the fabrication technique. The SLM technique is advantageous over the CAST technique for fabricating Co-Cr dental alloys.