Retinopathy of prematurity (ROP) is a vision-threatening disorder that leads to pathological growth of the retinal vasculature due to hypoxia. Here, we investigated the potential effects of alamandine, a novel heptapeptide in the renin-angiotensin system (RAS), on hypoxia-induced retinal neovascularization and its underlying mechanisms. In vivo, the C57BL/6J mice with oxygen-induced retinopathy (OIR) were injected intravitreally with alamandine (1.0 μmol/kg per eye). In vitro, human retinal microvascular endothelial cells (HRMECs) were utilized to investigate the effects of alamandine (10 μg/mL) on proliferation, apoptosis, migration, and tubular formation under vascular endothelial growth factor (VEGF) stimulation. Single-cell RNA sequencing (scRNA-seq) matrix data from the Gene Expression Omnibus (GEO) database and RAS-related genes from the Molecular Signatures Database (MSigDB) were sourced for subsequent analyses. By integrating scRNA-seq data across multiple species, we identified that RAS-associated endothelial cell populations were highly related to retinal neovascularization. The liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis revealed a significant decrease in alamandine levels in both the serum and retina of OIR mice compared to those in the control group. Next, alamandine ameliorated hypoxia-induced retinal pathological neovascularization and physiologic revascularization in OIR mice. In vitro, alamandine effectively mitigated VEGF-induced proliferation, scratch wound healing, and tube formation of HRMECs primarily by inhibiting the hypoxia-inducible factor-1α (HIF-1α)/VEGF pathway. Further, coincubation with D-Pro⁷ (Mas-related G protein-coupled receptor D (MrgD) antagonist) hindered the beneficial impacts of alamandine on hypoxia-induced pathological angiogenesis both in vivo and in vitro. Our findings suggested that alamandine could mitigate retinal neovascularization by targeting the MrgD-mediated HIF-1α/VEGF pathway, providing a potential therapeutic agent for OIR prevention and treatment.
Animals ; Retinal Neovascularization/prevention & control* ; Mice, Inbred C57BL ; Vascular Endothelial Growth Factor A/metabolism* ; Humans ; Mice ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Oligopeptides/therapeutic use* ; Signal Transduction/drug effects* ; Cell Proliferation/drug effects* ; Endothelial Cells/drug effects* ; Retinopathy of Prematurity/drug therapy* ; Apoptosis/drug effects* ; Cell Movement/drug effects* ; Renin-Angiotensin System/drug effects* ; Cells, Cultured

The Menghe Medical School is a highly influential academic school of Chinese medicine in China.Its academic features are mainly learning from others'strengths,openness and tolerance;integrity as the foundation,communication as the strength;harmo-ny as the way,and agility as the technique.The Menghe Medical School originated in Menghe,developed in Shanghai,spread all over the country,and spread around the world.The reasons for the prosperity and development of the Menghe Medical School are analyzed.Among them,imperial doctors being rewarded and supported,the stars having their roots in Menghe,inheritance from teach-ers by blood,help from in-laws,and the establishment of education and leadership in development are the main factors.On the basis of inheriting the scholarship of Menghe Medical School,Professor Tong Xiaolin innovatively proposed academic ideas such as the train-ing path of Xiang thinking,state-target differentiation and treatment,and dosage and effectiveness of prescriptions and medicines,pushing the academic thought of Menghe Medical School to a new theoretical peak in the new era.Based on the majestic development path of the Menghe Medical School,the implications for the inheritance,innovation and development of modern Chinese medicine are analyzed.

Objective To compare the dosimetric characteristics of non-coplanar and coplanar field technology in static intensity-modulated radiotherapy of gastric cancer patients, so as to provide a reference for clinical radiotherapy plan selection. Methods Thirty-six patients with gastric cancer were selected to receive intensity-modulated radiotherapy in Huanggang Central Hospital, which was designed plan A and B. Group A used 7-field coplanar technology, while Group B used 7-field non-coplanar technology. We compared the differences of the optimized monitor unit, the dosimetry of organs at risk and target areas between group A and group B. Results Both group A and B could meet the requirements of doctors. The homogeneity index (0.14 ± 0.02), the conformity index (0.98 ± 0.01), D_min (4315.21 ± 16.74) cGy、D_mean (4679.28 ± 28.39) cGy and D_max(4952.30 ± 33.26) cGy of target areas in group B were better than those of group A. Moreover, the monitor unit of group B was much lower than that of group A, and the difference was statistically significant (P < 0.05). The D_max, D_mean, V₁₅, V₂₀ and V₃₀ of the left and right kidneys in group B were lower than those of group A. The D_max (3408.57 ± 46.03) cGy, D_mean (1250.32 ± 14.27) cGy and V₂₀ (44.91% ± 6.67%) of spinal cord and the D_max (3408.57 ± 46.03) cGy, D_mean (1720.55 ± 17.42) cGy, V₂₀ (25.31% ± 7.78%) and V₃₀ (18.52% ± 1.56%) of small intestine were also lower than those of group A. The differences were statistically significant (P < 0.05). Conclusion The non-coplanar field radiation plan has more advantages in terms of target dose distribution and protection of organs so that it can be more considerably used in the process of planning and design.

With the development of mass spectrometry technologies and bioinformatics analysis algorithms, disease research-driven human proteome project (HPP) is advancing rapidly. Protein biomarkers play critical roles in clinical applications and the biomarker discovery strategies and methods have become one of research hotspots. Feature selection and machine learning methods have good effects on solving the "dimensionality" and "sparsity" problems of proteomics data, which have been widely used in the discovery of protein biomarkers. Here, we systematically review the strategy of protein biomarker discovery and the frequently-used machine learning methods. Also, the review illustrates the prospects and limitations of deep learning in this field. It is aimed at providing a valuable reference for corresponding researchers.
Algorithms ; Biomarkers ; Humans ; Machine Learning ; Mass Spectrometry ; Proteomics

Tumor-specific gene mutations might generate suitable neoepitopes for cancer immunotherapy that are highly immunogenic and absent in normal tissues. The high heterogeneity of the tumor genome poses a big challenge for precision cancer immunotherapy. Mutations characteristic of each tumor can help to distinguish it from other tumors. Based on these mutations' characteristic, it is possible to develop immunotherapeutic strategies for specific tumors. In this study, a tumor neoantigen prediction scheme was proposed, in which both the intracellular antigen presentation process and the ability to bind with extracellular MHC molecule were taken into consideration. The overall design is meritorious and may help reduce the cost for validation experiments compared with conventional methods. This strategy was tested with several cancer genome datasets in the TCGA database, and a number of potential tumor neoantigens were predicted for each dataset. These predicted neoantigens showed tumor type specificity and were found in 20% to 70% of cancer patients. This scheme might prove useful clinically in future.
Antigens, Neoplasm ; Computational Biology ; Genome, Human ; Humans ; Immunotherapy ; Mutation ; Neoplasms