Recent Advances in Systems and Network Medicine: Meeting Report from the First International Conference in Systems and Network Medicine

A Coordinated and Optimized Mechanism of Artificial Intelligence for Student Management by College Counselors Based on Big Data

The purpose of this article is to perform in-depth research and analysis on the artificial intelligence coordination and optimization mechanism of college counseling student management using big data technology. This study places the collaborative ideological and political work of colleges and universities in the context of big data, and by analyzing its basic connotation and changes in the real situation, it explores the development progression of colleges and universities making full use of big data resources to cultivate a collaborative education model, which is conducive to promoting colleges and universities to cultivate a whole staff, whole process, and all-round accurate ideological education and value-led services and to shape excellent young college students with comprehensive growth. The first is to scientifically build a multilevel linked big data management platform for counselor professionalization construction, plan the technical architecture of the organizational platform, build a cloud database of counselor career files, and extract valuable information and data from the organizational activities at the macrolevel and personal activities at the microlevel with counselor professionalization construction activities; the second is to realize the integrated application of information resources for counselor team construction. The second is to realize the integrated application of counselor team construction information resources, visualise and accurately analyze and evaluate the counselor group's focus on career development and individual counselors' feedback on career capacity construction, and improve the overall construction, personalized education management level, and self-improvement development ability. Fourth, in the professionalization of counselors, attention should be paid to the scientific selection and prevention of risks of big data application, ensuring the authenticity and reliability of data and leakage prevention and control, etc.

Cancer and pulmonary hypertension: Learning lessons and real-life interplay

This article reviews the scientific reasons that support the intriguing vision of pulmonary hypertension (PH) as a disease with a cancer-like nature and to understand whether this point of view may have fruitful consequences for the overall management of PH. This review compares cancer and PH in view of Hanahan and Weinberg’s principles (i.e., hallmarks of cancer) with an emphasis on hyperproliferative, metabolic, and immune/inflammatory aspects of the disease. In addition, this review provides a perspective on the role of transcription factors and chromatin and epigenetic aberrations, besides genetics, as “common driving mechanisms” of PH hallmarks and the foreseeable use of transcription factor/epigenome targeting as multitarget approach against the hallmarks of PH. Thus, recognition of the widespread applicability and analogy of these concepts will increasingly affect the development of new means of PH treatment.