Effect of sacubitril/valsartan on inflammation and oxidative stress in doxorubicin-induced heart failure model in rabbits

Our study evaluates the effects of sacubitril/valsartan (SAC/VAL) in the rabbit model of doxorubicin-induced heart failure. Twenty rabbits (5 per group) were administered with doxorubicin (DOX, 1.5 mg kg–1, i.v.) to induce heart failure. Specific biomarkers such as BNP, CnT, CRP and ROMs were determined. The cardiac enzymatic antioxidant systems were recorded with their electrographic profiles. HR, SBP, DBP and MAP were restored at 5 or 10 mg kg–1 (p.o.) of SAC/VAL compared to DOX, followed by reduced levels of creatinine and BNP (p < 0.001). Significant improvements (p < 0.05) compared to DOX were also noticed in CAT, SOD and LPO with the same doses of SAC/VAL. Specific biomarkers such as BNP, CnT, CRP and ROMs descended significantly (p < 0.001) with treatment when compared to their baseline values. Our findings implied that SAC/VAL treatment reduced the inflammation and oxidative stress to improve the cardiac function

Surgical treatment of primary hepatic neuroendocrine tumor diagnosed by Al18F-NOTA-Octreotide PET/CT: a case report

Neuroendocrine tumors (NETs) are a heterogeneous group of tumors originating from peptide-producing neurons and neuroendocrine cells. The liver is the most common site of metastasis for NETs, while primary hepatic neuroendocrine tumors (PHNETs) are exceedingly rare. While somatostatin receptor scintigraphy (SRS) has demonstrated superior efficacy compared to [18F]FDG PET imaging in the diagnosis of neuroendocrine tumors, [18F]AlF-NOTA-Octreotide ([18F]AlF-OC) PET/CT also exhibits specific advantages over SRS. This article presents a case study of a patient with a liver mass who underwent sequential [18F]FDG and [18F]AlF-OC PET/CT scans, ruling out hepatocellular carcinoma and confirming the diagnosis of PHNETs. Subsequently, the patient underwent surgical treatment. From another perspective, [18F]AlF-OC exhibits distinct advantages. The postoperative pathology revealed a PHNETs, which further emphasizes its clinical rarity

Regional logistics, carbon emission index and green financial performance enhancement configuration: a comparative study based on 30 Chinese provinces

In recent years, because of the increasingly severe global environmental protection situation and the superimposed effect of the new crown epidemic, the importance of green finance has been highlighted and gradually elevated to an important future development strategy for the country. However, it is unclear how to improve the effectiveness of green finance in each province. Using 30 Chinese provinces and regions as research samples, this paper summarizes five influencing factors, including regional logistics, carbon emission index, regional finance, economic level, and environmental regulation. Considering the complex causal relationship between factors and green finance performance, fsQCA is used to explore the different configurations formed in the process of developing green finance in each province. The results comprise four different configurations for high performance and four types of configurations for the absence of high performance. Currently, with the regional green finance development model still in its infancy, regional logistics and carbon emission index factors play a key role in stimulating the development of green finance in the provinces and regions. This study has important theoretical and practical significance for the construction of regional green financial system and local government performance appraisal system with local characteristics in each province of China, and provides locally adapted policy suggestions for different provinces to achieve optimal allocation of resources

Overview of Academic Studies on Smart Care for the Elderly and Comprehensive Solution Design

Due to historical reasons and urbanization progress, demographic development change has promoted China to enter an aging society and the elders’ demand for medical care and health care has increased rapidly. Meanwhile, the rapid development of information technology is driving the “Smart Care for the Elderly” model which is based on the Internet and regards the internet of things as the medium which has gradually developed into a complete a system, and a series of solutions have been formed. This paper started with the analysis of China’s elderly population status quo, combed academic studies on domestic and foreign “Smart Care for the Elderly” and applications in recent fifteen years and explored how to build a comprehensive “Smart Care for Elderly” solution with improved functions which incorporates such key elements as information technology and social sciences

The global impact of the International Federation of Clinical Chemistry and Laboratory Medicine, Education and Management Division: engaging stakeholders and assessing HbA1c quality in a multicentre study across China

Background: Diabetes mellitus is a major global issue and high quality testing is essential for the diagnosis and treatment of the disease. The IFCC Committee for the Education in the Utility of Biomarkers in Diabetes (C-EUBD) plays a global role in improving knowledge and understanding around diabetes testing. This paper describes a multi-stakeholder approach, to improving diagnostic and therapeutic testing for diabetes, using a multicentre study in China as an example of the global impact of the group. Methods: Educational workshops were developed to support the scientific aims of the study in which 30 centres around China received identical, fresh frozen whole blood samples with values assigned using IFCC secondary reference methods and undertook precision (EP-5) and trueness studies. Performance was assessed using sigma metrics. Results: A successful multi-stakeholder group was developed and sustained throughout the study through several educational workshops, which enabled the formation of a long-term collaboration with key opinion leaders and policy makers in China. All 30 centres showed good performance with within and between laboratory coefficient of variations (CVs) below 3% in SI units at both low and high haemoglobin A1c (HbA1c) levels. All individual laboratories met the criteria of a sigma of two or more at a total allowable error (TAE) of 5 mmol/mol (0.46% NGSP). Conclusions: The study led to a successful multi-partner approach to improving diabetes testing in China. All centres involved in the study meeting the published IFCC quality criteria, paving the way for future clinical trials and an expanded role for HbA1c testing across the country

Explore postgraduate biomedical engineering course integration between medical signal processing and drug development: example for drug development in brain disease

Medical signal processing is a compulsory course in our university’s undergraduate biomedical engineering programme. Recently, application of medical signal processing in supporting new drug development has emerged as a promising strategy in neurosciences. Here, we discuss the curriculum reformation in biomedical signal processing course in the context of drug development and application in central nervous system, with a particular emphasis in knowledge integration

A novel artificial intelligence network to assess the prognosis of gastrointestinal cancer to immunotherapy based on genetic mutation features

BackgroundImmune checkpoint inhibitors (ICIs) have revolutionized gastrointestinal cancer treatment, yet the absence of reliable biomarkers hampers precise patient response prediction.MethodsWe developed and validated a genomic mutation signature (GMS) employing a novel artificial intelligence network to forecast the prognosis of gastrointestinal cancer patients undergoing ICIs therapy. Subsequently, we explored the underlying immune landscapes across different subtypes using multiomics data. Finally, UMI-77 was pinpointed through the analysis of drug sensitization data from the Genomics of Drug Sensitivity in Cancer (GDSC) database. The sensitivity of UMI-77 to the AGS and MKN45 cell lines was evaluated using the cell counting kit-8 (CCK8) assay and the plate clone formation assay.ResultsUsing the artificial intelligence network, we developed the GMS that independently predicts the prognosis of gastrointestinal cancer patients. The GMS demonstrated consistent performance across three public cohorts and exhibited high sensitivity and specificity for 6, 12, and 24-month overall survival (OS) in receiver operating characteristic (ROC) curve analysis. It outperformed conventional clinical and molecular features. Low-risk samples showed a higher presence of cytolytic immune cells and enhanced immunogenic potential compared to high-risk samples. Additionally, we identified the small molecule compound UMI-77. The half-maximal inhibitory concentration (IC50) of UMI-77 was inversely related to the GMS. Notably, the AGS cell line, classified as high-risk, displayed greater sensitivity to UMI-77, whereas the MKN45 cell line, classified as low-risk, showed less sensitivity.ConclusionThe GMS developed here can reliably predict survival benefit for gastrointestinal cancer patients on ICIs therapy