Objective Toa nalyzed ifferentialp roteine xpressiono fc holangiocarcinomai np eripheralb loodb yproteomics technology, and to investigate the significance of proteomics technology in early diagnosis of bile ductmalignancy.M ethods Serum proteinf rom 58p atientsw ithc holangiocarcinomaa nd5 8c ontrols( 20p atientsw ithcholecystolithiasis and 38 healthy people) were detected by surface enhanced laser desorption/ionization-time offlight-mass spectrometry (SELDI-TOF-MS). Ciphergen protein chip software was used to identify proteinic spectra.R esults Comparedw itht hes pectrao fs erum proteini nc ontrolg roup,t herew ere1 0d ifferentiallye xpressedproteins in bile duct carcinoma group, among which three proteins with relative molecular masses of 5. 900 X 10’，9.08 0X 1 0’a nd1 1.86 3X 1 0’w ereu p-regulated( Plt;1 0-’)ands evenp roteinsw ithr elativem olecularm asseso f6.9 59X 1 0’，14.0 00X 1 0’，14.1 29X 1 0’，14.3 02X 1 0’，17.5 57X 10’，17.6 90X 1 0’a nd2 8.5 52X 1 0’w ered ownregulated(Plt; 10-’)。The average concentration of protein with the relative molecular mass of 11. 863 X 10’ incholangiocarcinoma group was eight times more than that in controls group. At the stage I of cholangiocarcinoma,thee xpressiono fp roteinp ointw itha r elativem olecularm asso f5 .90 0X1 0’w ass ignificantlyh ighert hant hosep atientsat the stage III and stage fV (Plt;10-’)，while there were no statistical difference of expression between diffeent clinical stages for the other 9 proteins points. And there were no significant expression differences of the above10 proteins between the patients with and without jaundice following cholangiocarcinoma. Instead, another threeproteinsw ithr elativem olecularm asseso f7 .25 5X 1 03，12.36 4X 1 0’a nd1 5.8 73X 1 03w ered etectedt oh aved ifferentproteine xpressions.A nda llo fth em showedh ighe xpressionsin j aundiceg roup( Plt;10-5).C onclusion Thereare remarkable differences of the expressions of serum proteins in peripheral blood in patients with cholangiocarcinoma.T hep roteinp ointw itha r elativem olecularm asso f1 1.86 3X 1 0’m ayb ea p otentialb iomarkerfo re arlyd iagnosisof cholangiocarcinoma
ObjectiveTo summarize the current research progress in the prediction of the efficacy of neoadjuvant therapy of breast cancer based on the application of artificial intelligence (AI) and radiomics. MethodThe researches on the application of AI and radiomics in neoadjuvant therapy of breast cancer in recent 5 years at home and abroad were searched in CNKI, Google Scholar, Wanfang database and PubMed database, and the related research progress was reviewed. ResultsAI had developed rapidly in the field of medical imaging, and molybdenum target, ultrasound and magnetic resonance imaging combined with AI had been deepened and expanded in different degrees in the application research of breast cancer diagnosis and treatment. In the research of molybdenum target combined with AI, the high sensitivity of molybdenum target to microcalcification was mostly used to improve the accuracy of early detection and diagnosis of breast cancer, so as to achieve the clinical purpose of early detection and diagnosis. However, in terms of prediction of neoadjuvant efficacy research of breast cancer, ultrasound and magnetic resonance imaging combined with AI were more prevalent, and their popularity remained unabated. ConclusionIn the monitoring of neoadjuvant therapy for breast cancer, the use of properly designed AI and radiomics models can give full play to its role in the predicting the curative effect of neoadjuvant therapy, and help to guide doctors in clinical diagnosis and treatment and evaluate the prognosis of breast cancer patients.
ObjectiveTo characterize proteomic profile in aqueous humor of patients with pathologic myopia (PM) using quantitative proteomic analysis, which may provide new clues to understand the mechanisms and possible treatments of PM.MethodsA cross-sectional study. From January 2019 to August 2019, aqueous humor samples (32 cataract patients) were collected for quantitative proteomic analysis using liquid chromatography tandem mass spectrometry at Tianjin Medical University Eye Hospital. There were 11 males and 21 females. They were 58-76 years old with an average age of 68.41±6.09 years old. Sixteen patients with PM were regarded as PM group, 16 patients without myopia were regarded as the control group. The aqueous humor samples (100-150 μl ) were collected from all patients before cataract surgery. Using protein quantification and non-labeled liquid chromatography tandem mass spectrometry analysis, differentially expressed proteins were obtained. Five different proteins were randomly selected for ELISA verification. The differentially expressed proteins were further analyzed by gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes, which were validated using ELISA in the other twenty samples of each group.ResultsA total of 583 proteins were identified and 101 proteins were found to be differentially expressed, including 63 up-regulated proteins and 38 down-regulated proteins. ELISA verification results showed that the expression trend of the 5 differentially expressed proteins between the PM group and the control group was consistent with the results of Label-free quantitative proteomics analysis. The main classifications of these differentially expressed proteins were protein-binding activity modulator, defense/immunity protein, protein modifying enzyme, metabolite interconversion enzyme, extracellular matrix protein, transfer/carrier protein and so on. The bioinformatics analysis suggested that PM was closely associated with inflammation and immune interactions, and remodeling of extracellular matrix.ConclusionsCompared with the control group, the protein expression profile of PM patients' aqueous humor specimens has obvious changes. These differences indicate that PM is closely related to inflammation and immune interaction and extracellular matrix remodeling.
Objective To construct a radiomics model for identifying clinical high-risk carotid plaques. Methods A retrospective analysis was conducted on patients with carotid artery stenosis in China-Japan Friendship Hospital from December 2016 to June 2022. The patients were classified as a clinical high-risk carotid plaque group and a clinical low-risk carotid plaque group according to the occurrence of stroke, transient ischemic attack and other cerebrovascular clinical symptoms within six months. Six machine learning models including eXtreme Gradient Boosting, support vector machine, Gaussian Naive Bayesian, logical regression, K-nearest neighbors and artificial neural network were established. We also constructed a joint predictive model combined with logistic regression analysis of clinical risk factors. ResultsFinally 652 patients were collected, including 427 males and 225 females, with an average age of 68.2 years. The results showed that the prediction ability of eXtreme Gradient Boosting was the best among the six machine learning models, and the area under the curve (AUC) in validation dataset was 0.751. At the same time, the AUC of eXtreme Gradient Boosting joint prediction model established by clinical data and carotid artery imaging data validation dataset was 0.823. Conclusion Radiomics features combined with clinical feature model can effectively identify clinical high-risk carotid plaques.
ObjectiveTo introduce economic evaluation methods for anticancer-drugs with basket trial design, and to provide references for related research and decision-making. MethodsA case analysis was conducted on economic evaluation methods for anticancer-drugs with basket trial design, which was issued by Canadian Agency for Drugs and Technologies in Health (CADTH) in the Economic Guidance Report. Moreover, both the advantages and disadvantages of the methods were analyzed in accordance with the characteristics of basket trials. ResultsPooled analysis and tumor-specific analysis were two methods frequently employed in the case analysis. However, great uncertainties were available in both of them. The uncertainty of the former was mainly reflected in the heterogeneity of the targeted population, while the uncertainty of the latter was mainly shown in the insufficient sample size of the subgroup. ConclusionCurrently, economic evaluation methods for anticancer-drugs with basket trial design are immature. Thus, researchers are required to explore the methods of innovation evaluation with lower uncertainty; reimbursement decision-makers should fully consider the uncertainty of evaluation results and enterprises should collect the real-world data for the demands of evaluation to promote the reasonable allocation of healthcare resources in China.
ObjectiveTo evaluate the effect of health economics of census versus high-risk population screening for tuberculosis in Mianyan city, in order to provide references for the selection of suitable tuberculosis screening method in western region of China. MethodsWe included active tuberculosis patients by residents health screening of 21 villages and towns in Mianyan city from June 2013 to March 2013. Relevant data was analyzed by referencing the National Assessment of Tuberculosis Control Program in 2001-2010. Results184047 residents were screened by tuberculosis census and 128 active tuberculosis patients were diagnosed while 61045 residents were screened by high-risk population screening and 76 active tuberculosis patients were diagnosed. The cost-utility ratio and benefit-cost ratio of tuberculosis census were 6174.17 and 3.84, respectively. The cost-utility ratio and benefit-cost ratio of high risk population screening were 3106.16 and 7.62, respectively. ConclusionHigh-risk population screening has higher cost-utility ratio and benefit-cost ratio than tuberculosis census with higher missed diagnosis. Benefits and harms of tuberculosis detection rate and cost should be fully balanced before tuberculosis screening method were chosen in western underdeveloped region of China.
ObjectiveTo systematically review the effectiveness and safety of salvianolate injection and Danshen injection for patients with angina pectoris, and evaluate the cost of drug. MethodsWe electronically searched databases including PubMed, CENTRAL (Issue 4, 2013), CNKI, VIP and WanFang Data (2004.1 to 2013.5) for the randomized controlled trials (RCTs) on the comparison between salvianolate injection and Danshen injection for angina pectoris from January 2004 to May 2013. Relevant journals and conference proceedings were also manually retrieved. Two reviewers independently screened literature in accordance with the inclusion and exclusion criteria, extracted the data and assess the methodological quality of included studies. Then, meta-analysis was performed using RevMan 5.2 software. ResultsA total of 10 RCTs involving 1 196 patients were included. The results of meta-analysis showed that, salvianolate injection was obviously superior to Danshen injection in the effectiveness (OR=3.79, 95%CI 2.78 to 5.17, P < 0.000 01) and safety (OR=0.24, 95%CI 0.09 to 0.64, P=0.004), but lack of economic advantages in the treatment of the angina pectoris diseases. ConclusionCurrent evidence indicates that, salvianolate injection is a safe and effective scheme for angina pectoris, and Danshen injection is considered as a economic method. Because of the limited quantity and quality of currently-available research, the aforementioned conclusion should be verified by strictly-designed and large-scale sample RCTs.
ObjectiveTo systematically review the value of radiomics in the diagnosis of glioblastoma. MethodsPubMed, EMbase, Web of Science and The Cochrane Library databases were electronically searched to collect studies on radiomics in the grading of gliomas or the differentiation diagnosis from inception to May 30th, 2021. Two reviewers independently screened literature, extracted data, and assessed the risk of bias and the quality of the included studies. Meta-analysis was then performed using Meta-Disc 1.4 software and RevMan 5.3 software. ResultsA total of 37 studies involving 2 746 subjects were included. The results of meta-analysis showed that the pooled sensitivity, specificity, and diagnostic odds ratio for the diagnosis of glioblastoma by radiomics were 0.91 (95%CI 0.89 to 0.92), 0.88 (95%CI 0.87 to 0.90), and 78.00 (95%CI 50.81 to 119.72), respectively. The area under the summary receiver operating characteristic (SROC) curve was 0.95. The key radiomic features for correct diagnosis of glioblastoma included intensity features and texture features of the lesions. ConclusionThe current evidence shows that radiomics provides good diagnostic accuracy for glioblastoma. Due to the limited quality and quantity of the included studies, more high-quality studies are required to verify the above conclusions.
Due to the high dimensionality and complexity of the data, the analysis of spatial transcriptome data has been a challenging problem. Meanwhile, cluster analysis is the core issue of the analysis of spatial transcriptome data. In this article, a deep learning approach is proposed based on graph attention networks for clustering analysis of spatial transcriptome data. Our method first enhances the spatial transcriptome data, then uses graph attention networks to extract features from nodes, and finally uses the Leiden algorithm for clustering analysis. Compared with the traditional non-spatial and spatial clustering methods, our method has better performance in data analysis through the clustering evaluation index. The experimental results show that the proposed method can effectively cluster spatial transcriptome data and identify different spatial domains, which provides a new tool for studying spatial transcriptome data.
Diabetic retinopathy (DR) is one of the microvascular complications of diabetes mellitus causing severe visual impairment, and it is the main cause of blindness in adults. Metabolic abnormalities play an important role in the occurrence and development of DR, including the abnormal levels of glucose metabolism, lipid metabolism, amino acid metabolism and purine metabolism, which indicate that there are disorders of phosphopentose pathway, arginine metabolism pathway, polyol pathway and ascorbic acid pathway in the progression of DR. Metabolomics has great advantages in exploring the pathogenesis and diagnosis of DR, helping to identify the characteristic metabolic changes of DR And discover potential biomarkers. However, the existing metabolomics studies on DR have some limitations, such as the potential biomarkers found in some studies are difficult to verify in other studies due to differences in race, age, gender and sample size. There are few studies on biomarkers at different stages of DR. Therefore, in the future, multi-center and large-scale clinical studies are needed to screen out biomarkers with practical clinical diagnostic value.