Abstract The serum nanoparticle‐protein corona (NPC) provides specific disease information, thus opening a new avenue for high‐throughput in‐depth proteomics to facilitate biomarker discovery. Yet, little is known about the interactions between NPs and proteins, and its role in enhanced depth of serum proteomics. Herein, a series of protein spike‐in experiments are conducted to systematically investigate protein depletion and enrichment during NPC formation. Proteomic depth is serum concentration‐dependent, and NPC exhibits powerful tolerance to ultra‐high abundant proteins. In addition, protein‐protein interactions (PPI), especially those involving albumin, play a pivotal role in promoting proteomic depth. Furthermore, a triple‐protein assay is established to interrogate the relationship between protein binding affinity and concentration. NPC formation is a product of balancing binding affinity, concentration, and PPI. Overall, this study elucidates how NPs achieve protein depletion and enrichment for enhanced serum proteomic depth to gain a better understanding of NPC as an essential tool of proteome profiling.
Highly abundant proteins present in biological fluids and tissues significantly interfere with low-abundance protein identification by mass spectrometry (MS), limiting proteomic depth and hindering protein biomarker discovery. Herein, to enhance the coverage of tissue proteomics, we developed a nanoparticle-protein corona (NP-PC)-based method for the aging mouse proteome atlas. Based on this method, we investigated the complexity of life process of 5 major organs, including the heart, liver, spleen, lungs, and kidneys, from 4 groups of mice at different ages. Compared with the conventional strategy, NP-PC-based proteomics significantly increased the number of identified protein groups in the heart (from 3007 to 3927; increase of 30.6%), liver (from 2982 to 4610; increase of 54.6%), spleen (from 5047 to 7351; increase of 45.7%), lungs (from 4984 to 6903; increase of 38.5%), and kidneys (from 3550 to 5739; increase of 61.7%), and we identified a total of 10 104 protein groups. The overall data indicated that 3-week-old mice showed more differences compared with the other three age groups. The proteins of amino acid-related metabolism were increased in aged mice compared with those in the 3-week-old mice. Protein-related infections were increased in the spleen of the aged mice. Interestingly, the spliceosome-related pathway significantly changed from youth to elders in the liver, spleen, and lungs, indicating the vital role of the spliceosome during the aging process. Our established aging mouse organ proteome atlas provides comprehensive insights into understanding the aging process, and it may help in prevention and treatment of age-related diseases.
Diagnosis of benign and malignant small nodules of the lung remains an unmet clinical problem which is leading to serious false positive diagnosis and overtreatment. Here, we developed a serum protein fishing-based spectral library (ProteoFish) for data independent acquisition analysis and a machine learning-boosted protein panel for diagnosis of early Non-Small Cell Lung Cancer (NSCLC) and classification of benign and malignant small nodules. We established an extensive NSCLC protein bank consisting of 297 clinical subjects. After testing 5 feature extraction algorithms and six machine learning models, the Lasso algorithm for a 15-key protein panel selection and Random Forest was chosen for diagnostic classification. Our random forest classifier achieved 91.38% accuracy in benign and malignant small nodule diagnosis, which is superior to the existing clinical assays. By integrating with machine learning, the 15-key protein panel may provide insights to multiplexed protein biomarker fishing from serum for facile cancer screening and tackling the current clinical challenge in prospective diagnostic classification of small nodules of the lung.
Abstract Background As China's aging population continues to grow, the prevalence of mental illness among the seniors has been steadily increasing. The aim of this study is to reveal the changing trends and characteristics of economic burden among seniors patients with long-term hospitalization for mental illness, and to analyze the influencing factors. Methods The data for this study were gathered from seniors’ patients with mental illness who were hospitalized and aged 60 years or older. The patients were admitted to four specialized and general hospitals located in Dalian city between January 2018 and December 2020. The types of diseases include affective mental disorders (mood disorders), Schizophrenia, schizotypal, and delusional disorders, Organic (including symptomatic) mental disorders, Neurotic, stress-related and somatoform disorders, Mental retardation, Mental and behavioral disorders due to substance use. (Identify the main diagnosis at discharge using ICD-10 coding). This study analyzed the basic characteristics and disease-related information of seniors patients with long-term psychiatric disorders who were hospitalized, and explored the factors influencing hospitalization costs among patients with different illnesses. Results Among the 3871 study subjects, the average length of hospital stay was 127.51 days. The average hospitalization expenses per case were 33,656.07 yuan. Seniors’ patients with mental illness who receives treatment in specialized hospitals have higher hospitalization costs. Long-term hospitalization increases the total hospitalization costs. Age has an impact on hospitalization costs for patients with organic mental disorders. Patients with affective disorders (mood disorders) and neurotic, stress-related, and somatoform disorders who are covered by urban employee medical insurance have higher hospitalization costs.Patients with severe psychiatric disorders who have a 31-day readmission plan, as well as senior patients with somatoform disorders comorbid with other illnesses, incur higher hospitalization costs. Conclusions We should take corresponding measures to reduce the number of readmissions for patients with severe mental illnesses. The impact of treatment methods and differences in healthcare institutions on total hospitalization costs deserves further research. It is necessary to strengthen the prevention and diagnosis of comorbid physical illnesses in patients with mental disorders. The burden of mental illnesses in the seniors is significant, and medical insurance policies should be inclined towards providing support.
Based on the theory of "opening and closing pivot" in Inner Path, this paper discusses the physiological basis of the two pivot points from the perspective of yin-yang and Yin-yang, puts forward that the key of chronic heart failure is the imbalance of yin-yang, the disharmony of cold and heat, the disturbance of qi movement, the disuse of gasification, and the failure of water and liquid regulation are the pathologic formation of heart failure.And according to the cardinal theory as the guidance, with the armature legislation, the selection of prescription and medicine, the treatment of heart failure, in order to provide a theoretical basis for clinical differentiation and treatment of heart failure.
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