The invasive fractional flow reserve has been considered the gold standard for identifying ischaemia-related stenosis in patients with suspected coronary artery disease. Determining non-invasive FFR based on coronary computed tomographic angiography datasets using computational fluid dynamics tends to be a demanding process. Therefore, the diagnostic performance of a simplified method for the calculation of FFRCTA requires further evaluation.The aim of this study was to investigate the diagnostic performance of FFRCTA calculated based on a simplified method by referring to the invasive FFR in patient-specific coronary arteries and clinical decision-making.Twenty-nine subjects included in this study underwent CCTA before undergoing clinically indicated invasive coronary angiography for suspected coronary artery disease. Pulsatile flow simulation and a novel boundary condition were used to obtain FFRCTA based on the CCTA datasets. The Pearson correlation, Bland-Altman plots and the diagnostic performance of FFRCTA and CCTA stenosis were analyzed by comparison to the invasive FFR reference standard. Ischaemia was defined as an FFR or FFRCTA ≤0.80, and anatomically obstructive CAD was defined as a CCTA stenosis >50%.FFRCTA and invasive FFR were well correlated (r = 0.742, P = 0.001). Slight systematic underestimation was found in FFRCTA (mean difference 0.03, standard deviation 0.05, P = 0.001). The area under the receiver-operating characteristic curve was 0.93 for FFRCTA and 0.75 for CCTA on a per-vessel basis. Per-patient accuracy, sensitivity and specificity were 79.3, 93.7 and 61.5%, respectively, for FFRCTA and 62.1, 87.5 and 30.7%, respectively, for CCTA. Per-vessel accuracy, sensitivity and specificity were 80.6, 94.1 and 68.4%, respectively, for FFRCTA and 61.6, 88.2 and 36.8%, respectively, for CCTA.FFRCTA derived from pulsatile simulation with a simplified novel boundary condition was in good agreement with invasive FFR and showed better diagnostic performance compared to CCTA, suggesting that the simplified method has the potential to be an alternative and accurate way to assess the haemodynamic characteristics for coronary stenosis.
Abstract Colorectal cancer (COAD) ranks as the second leading cause of global cancer-related deaths. However, effective therapeutic strategies for advanced colorectal cancer remain limited. Despite the success of immunotherapy in cancer treatment, its applicability is significantly constrained by the heterogeneity of the tumor microenvironment. Therefore, the aim of this study is to develop an immune-related feature model at the single-cell level, categorize colorectal cancer patients based on gene transcription levels, and predict patients' prognosis, immune status, and treatment response. By analyzing single-cell transcriptomic data (scRNA-seq) of COAD, we identified eight cell types and selected immune cell marker genes (IRGs) for subsequent analysis. Utilizing these IRGs, we established an immune-related model to classify patients into high and low-risk groups for predicting overall survival (OS). The low-risk group exhibited high tumor mutation burden (TMB), increased immune activation, high microsatellite instability (MSI-H), longer overall survival (OS), and better response to immunotherapy. Conversely, the high-risk group displayed microsatellite stability (MSS), low TMB, immune suppression, and other characteristics. Additionally, we validated the model's performance in predicting immune treatment responses using external data from the IMvigor210 cohort. In summary, combining single-cell and bulk tissue transcriptome sequencing, we constructed a survival risk prognosis model that categorizes patients into high and low-risk groups. This model enables the prediction of patients' immune cell status, immune-related functions, and immunotherapy effectiveness. These findings provide valuable insights into the immune status, prognosis assessment, and the development of effective immunotherapeutic approaches for colorectal cancer.
Radiotherapy (RT) is a primary clinical approach for cancer treatment, but its efficacy is often hindered by various challenges, especially radiation resistance, which greatly compromises the therapeutic effectiveness of RT. Mitochondria, central to cellular energy metabolism and regulation of cell death, play a critical role in mechanisms of radioresistance. In this context, cuproptosis, a novel copper-induced mitochondria-respiratory-dependent cell death pathway, offers a promising avenue for radiosensitization. In this study, an innovative theranostic nanoplatform was designed to induce cuproptosis in synergy with low-dose radiation therapy (LDRT, i.e., 0.5–2 Gy) for the treatment of in situ hepatocellular carcinoma (HCC). This approach aims to reverse the hypoxic tumor microenvironment, promoting a shift in cellular metabolism from glycolysis to oxidative phosphorylation (OXPHOS), thereby enhancing sensitivity to cuproptosis. Concurrently, the Fenton-like reaction ensures a sustained supply of copper and depletion of glutathione (GSH), inducing cuproptosis, disrupting mitochondrial function, and interrupting the energy supply. This strategy effectively overcomes radioresistance and enhances the therapeutic efficacy against tumors. In conclusion, this study elucidates the intricate interactions among tumor hypoxia reversal, cuproptosis, metabolic reprogramming, and radiosensitization, particularly in the context of treating in situ hepatocellular carcinoma, thereby providing a novel paradigm for radiotherapy.
BACKGROUND Chinese health insurance system faces resource distribution challenges. A patient-centric approach allows decision-makers to be keenly aware of optimized medical resource allocation. OBJECTIVE This study aims to use the discrete choice model to determine the main factors affecting the healthcare preferences of the general Chinese population and their weights in the three scenarios (chronic non-communicable diseases, acute infectious diseases, and major diseases). METHODS This study firstly identified the key factors affecting people's healthcare preferences through literature review and qualitative interviews, and then designed the DCE questionnaire. An online questionnaire produced by Lighthouse Studio (version 9.9.1) software was distributed to voluntary respondents recruited from mainland China’s entire population from January 2021 to June 2021. Participants were required to answer a total of 21 questions of three scenarios in the questionnaire. The multinomial logit model and latent class model were used to analyze the collected data. RESULTS A total of 4156 participants from mainland China were included in this study. The multinomial logit and latent class model analyses showed that medical insurance reimbursement is the most important attribute in all three disease scenarios. In the scenario of ‘non-communicable diseases’, the attributes that participants valued were, from the most to the least, medical insurance reimbursement (45.0%), hospital-level (21.6%), distance (14.4%), cost (9.7%), waiting time (8.3%), and care provider (1.0%). As for willingness to pay (WTP), participants were willing to pay 204.5 yuan, or 1743.8 yuan, to change from private hospitals or community hospitals to tertiary hospitals, respectively. CONCLUSIONS This study explores the healthcare preferences of Chinese residents from a new perspective, which can provide theoretical reference for the refinement of many disease medical reimbursement policies, such as developing different reimbursement ratios for various common diseases and realizing rational configuration of medical resources.
To investigate the expression of the ubiquitination enzyme UBE2S in different cell types in hepatocellular carcinoma (HCC) microenvironment and its impact on proliferation and stemness of HCC cells.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)