The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

The internal organs and meridians were associated with Yin and Yang, five elements, six qi, and time and space, based on the holistic view of heaven, earth and human, according to Huangdi Neijing. The syndrome differentiation system of six meridians and Zang Fu meridians were established by Shanghan Zabing Lun, on the basis of the three Yin, three Yang, six meridians, and five Zang system in Huangdi Neijing. We put forward the concept of the six meridians syndrome differentiation system of circular motion, considering that the six meridians syndrome differentiation system actually implies the theory of circular motion. The syndrome differentiation system was constructed with the circular model of one qi circulating around the road, rising left and falling right, corresponding up and down, and maintaining conservation in the middle as the core, integrating Yin and Yang, five elements, six qi, Zang Fu and meridians, qi, blood and body fluid, and the integration of heaven, earth and human, focusing on "disease location and disease nature", taking classical prescriptions as the main treatments, and cooperating with external treatments such as acupuncture and moxibustion. We organically combined the circular motion with the syndrome differentiation of the six meridians, systematically interpreted the physiological bases, pathological changes, progressive patterns, and the treatments, based on syndrome differentiation, by inheriting the classical thinking mode of Hetu, Luoshu,Zhouyi, Huangdi Neijing, ShennongHerbal Classic, and Shanghan Zabing Lun.

The interaction between ephrin ligands (efn) and their receptors (Eph) is capable of inducing forward signaling, from ligand to receptor, as well as reverse signaling, from receptor to ligand. The ephrins are widely expressed in many tissues, where they mediate cell migration and adherence, properties that make the efn-Eph signaling critically important in establishing and maintaining tissue boundaries. The efn-Eph system has also received considerable attention in skeletal tissues, as ligand and receptor combinations are predicted to mediate interactions between the different types of cells that regulate bone development and homeostasis. This review summarizes our current understanding of efn-Eph signaling with a particular focus on the expression and functions of ephrins and their receptors in bone.
Bone Development ; Cell Movement ; Ephrins ; Homeostasis ; Ligands ; Osteoblasts ; Osteoclasts

Understanding the regulatory mechanism that controls the alteration of global gene expression patterns continues to be a challenging task in computational biology. We previously developed an ant algorithm, a biologically-inspired computational technique for microarray data, and predicted putative transcription-factor binding motifs (TFBMs) through mimicking interactive behaviors of natural ants. Here we extended the algorithm into a set of web-based software, Ant Modeler, and applied it to investigate the transcriptional mechanism underlying bone formation. Mechanical loading and administration of bone morphogenic proteins (BMPs) are two known treatments to strengthen bone. We addressed a question: Is there any TFBM that stimulates both "anabolic responses of mechanical loading" and "BMP-mediated osteogenic signaling"? Although there is no significant overlap among genes in the two responses, a comparative model-based analysis suggests that the two independent osteogenic processes employ common TFBMs, such as a stress responsive element and a motif for peroxisome proliferator-activated receptor (PPAR). The post-modeling in vitro analysis using mouse osteoblast cells supported involvements of the predicted TFBMs such as PPAR, Ikaros 3, and LMO2 in response to mechanical loading. Taken together, the results would be useful to derive a set of testable hypotheses and examine the role of specific regulators in complex transcriptional control of bone formation.
Algorithms ; Animals ; Base Sequence ; Binding Sites ; genetics ; Biomechanical Phenomena ; Bone Morphogenetic Proteins ; pharmacology ; Consensus Sequence ; DNA ; genetics ; metabolism ; Databases, Genetic ; Gene Expression Profiling ; statistics & numerical data ; Genomics ; statistics & numerical data ; Mice ; Oligonucleotide Array Sequence Analysis ; statistics & numerical data ; Osteoblasts ; drug effects ; metabolism ; Osteogenesis ; drug effects ; genetics ; physiology ; Transcription Factors ; metabolism

Understanding the regulatory mechanism that controls the alteration of global gene expression patterns continues to be a challenging task in computational biology. We previously developed an ant algorithm, a biologically-inspired computational technique for microarray data, and predicted putative transcription-factor binding motifs (TFBMs) through mimicking interactive behaviors of natural ants. Here we extended the algorithm into a set of web-based software, Ant Modeler, and applied it to investigate the transcriptional mechanism underlying bone formation. Mechanical loading and administration of bone morphogenic proteins (BMPs) are two known treatments to strengthen bone. We addressed a question: Is there any TFBM that stimulates both "anabolic responses of mechanical loading" and "BMP-mediated osteogenic signaling"? Although there is no significant overlap among genes in the two responses, a comparative model-based analysis suggests that the two independent osteogenic processes employ common TFBMs, such as a stress responsive element and a motif for peroxisome proliferator-activated recep- tor (PPAR). The post-modeling in vitro analysis using mouse osteoblast cells sup- ported involvements of the predicted TFBMs such as PPAR, Ikaros 3, and LMO2 in response to mechanical loading. Taken together, the results would be useful to derive a set of testable hypotheses and examine the role of specific regulators in complex transcriptional control of bone formation.