modeling-and-evaluation-of-murine-diabetic-cardiomyopathy-model

Modeling and Evaluation of Murine Diabetic Cardiomyopathy Model

The underlying pathophysiological mechanisms of diabetic cardiomyopathy (DbCM), a leading cause of mortality among patients with type 2 diabetes mellitus ...

Sichuan University

 Bladder cancer (BCa), among the world's most common malignant tumors in the urinary system, has a high morbidity and mortality. Though cuproptosis is a new type of cell death mediated by lipoylated tricarboxylic acid (TCA) cycle proteins, the role of cuproptosis-related long noncoding RNAs (crlncRNAs) in bladder tumors awaits further elucidation. In this paper, we tried to explore how important crlncRNAs are for BCa.  The crlncRNAs were first obtained through Pearson correlation analysis of the RNA-seq data and corresponding clinical data downloaded from The Cancer Genome Atlas (TCGA). Then, three lncRNAs were acquired by Cox regression and Lasso regression to build a prognostic model of crlncRNAs for verification. In the meantime, clinicopathological correlation analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, principal component analysis (PCA), immunoassay, and half-maximal inhibitory concentration prediction (IC50) were carried out. Then, an entire tumor was classified into two clusters by crlncRNA expression to further discuss the differences in prognosis, immune status and drug susceptibility among different subgroups.  We obtained a total of 152 crlncRNAs and built a risk model for screened crlncRNAs. We validated the model and found that calibration charts feature a high consistency in verifying nomogram prediction. Receiver operating characteristic (ROC) curve and univariate and multivariate Cox regression suggested that this model can be applied as an independent prognostic factor of bladder cancer due to its high accuracy. According to KEGG analysis, high-risk groups were enriched in cancer and immune-related pathways. During tumor immunoassay, noticeable differences were observed in both immune infiltration and checkpoints between high- and low-risk patients. Of the two subgroups divided among patients by consensus clustering, cluster 2 had a better prognosis, whereas cluster 1 had higher immunoreactivity scores, more immune cell infiltrations and immune checkpoint expressions, and different sensitivities to drugs.  The research findings demonstrate that crlncRNAs can be used to predict the prognosis and immune microenvironment of patients suffering from BCa, and differentiate between BCa subgroups to improve the individual therapy of BCa.

Comprehensive analysis of cuproptosis-related long noncoding RNA immune infiltration and prediction of prognosis in patients with bladder cancer.

C-H dissociation and C-C coupling are two key steps in converting CH into multi-carbon compounds. Here we report a synergy of Au and Ag to greatly promote C H formation over Au Ag single-atom alloy nanoparticles (Au Ag NPs)-modified ZnO catalyst via photocatalytic oxidative coupling of methane (POCM) with O and H O. Atomically dispersed Au in Au Ag NPs effectively promotes the dissociation of O and H O into *OOH, promoting C-H activation of CH on the photogenerated O to form *CH . Electron-deficient Au single atoms, as hopping ladders, also facilitate the migration of electron donor *CH from ZnO to Au Ag NPs. Finally, *CH coupling can readily occur on Ag atoms of Au Ag NPs. An excellent C H yield of 14.0 mmol g  h with a selectivity of 79 % and an apparent quantum yield of 14.6 % at 350 nm is obtained via POCM with O and H O, which is at least two times that of the photocatalytic system. The bimetallic synergistic strategy offers guidance for future catalyst design for POCM with O and H O.

Photocatalytic Oxidative Coupling of Methane over Au Ag Single-Atom Alloy Modified ZnO with Oxygen and Water Vapor: Synergy of Gold and Silver.

. Follow-up computed tomography angiography (CTA) is necessary for ensuring occlusion effect of endovascular coiling. However, the implanted metal coil will introduce artifacts that have a negative spillover into radiologic assessment.. A framework named ReMAR is proposed in this paper for metal artifacts reduction (MARs) from follow-up CTA of patients with coiled aneurysms. It employs preoperative CTA to provide the prior knowledge of the aneurysm and the expected position of the coil as a guidance thus balances the metal artifacts removal performance and clinical feasibility. The ReMAR is composed of three modules: segmentation, registration and MAR module. The segmentation and registration modules obtain the metal coil knowledge via implementing aneurysms delineation on preoperative CTA and alignment of follow-up CTA. The MAR module consisting of hybrid convolutional neural network- and transformer- architectures is utilized to restore sinogram and remove the artifact from reconstructed image. Both image quality and vessel rendering effect after metal artifacts removal are assessed in order to responding clinical concerns.. A total of 137 patients undergone endovascular coiling have been enrolled in the study: 13 of them have complete diagnosis/follow-up records for end-to-end validation, while the rest lacked of follow-up records are used for model training. Quantitative metrics show ReMAR significantly reduced the metal-artifact burden in follow-up CTA. Qualitative ranks show ReMAR could preserve the morphology of blood vessels during artifact removal as desired by doctors.. The ReMAR could significantly remove the artifacts caused by implanted metal coil in the follow-up CTA. It can be used to enhance the overall image quality and convince CTA an alternative to invasive follow-up in treated intracranial aneurysm.

ReMAR: a preoperative CT angiography guided metal artifact reduction framework designed for follow-up CTA of endovascular coiling.

Anoikis is a distinct type of programmed cell death and a unique mechanism for tumor progress. However, its exact function in gastric cancer (GC) remains unknown. This study aims to investigate the function of anoikis-related lncRNA (ar-lncRNA) in the prognosis of GC and its immunological infiltration. The ar-lncRNAs were derived from RNA sequencing data and associated clinical information obtained from The Cancer Genome Atlas. Pearson correlation analysis, differential screening, LASSO and Cox regression were utilized to identify the typical ar-lncRNAs with prognostic significance, and the corresponding risk model was constructed, respectively. Comprehensive methods were employed to assess the clinical characteristics of the prediction model, ensuring the accuracy of the prediction results. Further analysis was conducted on the relationship between immune microenvironment and risk features, and sensitivity predictions were made about anticancer medicines. A risk model was built according to seven selected ar-lncRNAs. The model was validated and the calibration plots were highly consistent in validating nomogram predictions. Further analyses revealed the great accuracy of the model and its ability to serve as a stand-alone GC prognostic factor. We subsequently disclosed that high-risk groups display significant enrichment in pathways related to tumors and the immune system. Additionally, in tumor immunoassays, notable variations in immune infiltrates and checkpoints were noted between different risk groups. This study proposes, for the first time, that prognostic signatures of ar-lncRNA can be established in GC. These signatures accurately predict the prognosis of GC and offer potential biomarkers, suggesting new avenues for basic research, prognosis prediction and personalized diagnosis and treatment of GC.

Anoikis-Related Long Non-Coding RNA Signatures to Predict Prognosis and Immune Infiltration of Gastric Cancer.

Kidney transplantation (KT) is the best treatment for patients with end-stage renal disease. However, postoperative complications remain the main issues faced during KT recovery period. Posttransplant lymphoproliferative disorders (PTLD) are one of the severe and life-threatening complications that occur after KT while the recipient is undergoing immunosuppressive therapy. PTLD risk factors include Epstein-Barr virus (EBV) infection, the cumulative degree of immunosuppression, as well as genetic aspects. PTLD is more common in the transplanted organ itself and its surroundings, and the central nervous system, while PTLD involving the pharyngeal soft tissue is relatively rare, with only a few reported case reports. Therefore, systematic experience is scarce regarding whether the treatment or the care.

Yaoyu Zhang

Sichuan University

Modeling and Evaluation of Murine Diabetic Cardiomyopathy Model