Chinese medicine (CM) diagnosis intellectualization is one of the hotspots in the research of CM modernization. The traditional CM intelligent diagnosis models transform the CM diagnosis issues into classification issues, however, it is difficult to solve the problems such as excessive or similar categories. With the development of natural language processing techniques, text generation technique has become increasingly mature. In this study, we aimed to establish the CM diagnosis generation model by transforming the CM diagnosis issues into text generation issues. The semantic context characteristic learning capacity was enhanced referring to Bidirectional Long Short-Term Memory (BILSTM) with Transformer as the backbone network. Meanwhile, the CM diagnosis generation model Knowledge Graph Enhanced Transformer (KGET) was established by introducing the knowledge in medical field to enhance the inferential capability. The KGET model was established based on 566 CM case texts, and was compared with the classic text generation models including Long Short-Term Memory sequence-to-sequence (LSTM-seq2seq), Bidirectional and Auto-Regression Transformer (BART), and Chinese Pre-trained Unbalanced Transformer (CPT), so as to analyze the model manifestations. Finally, the ablation experiments were performed to explore the influence of the optimized part on the KGET model. The results of Bilingual Evaluation Understudy (BLEU), Recall-Oriented Understudy for Gisting Evaluation 1 (ROUGE1), ROUGE2 and Edit distance of KGET model were 45.85, 73.93, 54.59 and 7.12, respectively in this study. Compared with LSTM-seq2seq, BART and CPT models, the KGET model was higher in BLEU, ROUGE1 and ROUGE2 by 6.00-17.09, 1.65-9.39 and 0.51-17.62, respectively, and lower in Edit distance by 0.47-3.21. The ablation experiment results revealed that introduction of BILSTM model and prior knowledge could significantly increase the model performance. Additionally, the manual assessment indicated that the CM diagnosis results of the KGET model used in this study were highly consistent with the practical diagnosis results. In conclusion, text generation technology can be effectively applied to CM diagnostic modeling. It can effectively avoid the problem of poor diagnostic performance caused by excessive and similar categories in traditional CM diagnostic classification models. CM diagnostic text generation technology has broad application prospects in the future.
Humans ; Medicine, Chinese Traditional ; Pattern Recognition, Automated ; Asian People ; Language ; Learning

To explore the research hotspots and frontier directions of pyroptosis in the field of traditional Chinese medicine(TCM), the authors searched CNKI and Web of Science for literature related to pyroptosis in TCM, screened literature according to the search strategy and inclusion criteria, and analyzed the publication trend of the included literature. VOSviewer was used to draw author cooperation and keyword co-occurrence network diagrams, and CiteSpace was employed for keyword clustering, emergence, and timeline view. Finally, 507 Chinese literature and 464 English literature were included, and it was found that the number of Chinese and English literature was increasing rapidly year by year. The co-occurrence of the authors showed that in terms of Chinese literature, there was a representative research team composed of DU Guan-hua, WANG Shou-bao and FANG Lian-hua, and for English literature, the representative research team was composed of XIAO Xiao-he, BAI Zhao-fang and XU Guang. The network visualization of Chinese and English keywords revealed that inflammation, apoptosis, oxidative stress, autophagy, organ damage, fibrosis, atherosclerosis, and ischemia-reperfusion injury were the primary research diseases and pathological processes in TCM; berberine, resveratrol, puerarin, na-ringenin, astragaloside Ⅳ, and baicalin were the representative active ingredients; NLRP3/caspase-1/GSDMD, TLR4/NF-κB/NLRP3, and p38/MAPK signaling pathways were the main research pathways. Keyword clustering, emergence, and timeline analysis indicated that the pyroptosis research in TCM focused on the mechanism of TCM monomers and compounds intervening in diseases and pathological processes. Pyroptosis is a research hotspot in the area of TCM, and the current discussion mainly focuses on the mechanism of the therapeutic effect of TCM.
Pyroptosis ; Medicine, Chinese Traditional ; NLR Family, Pyrin Domain-Containing 3 Protein ; Pattern Recognition, Automated ; Apoptosis

With the booming development of medical information technology and computer science, the medical services industry is gradually transiting from information technology to intelligence. The medical knowledge graph plays an important role in intelligent medical applications such as knowledge questions and answers and intelligent diagnosis, and is a key technology for promoting wise medical care and the basis for intelligent management of medical information. In order to fully exploit the great potential of knowledge graphs in the medical field, this paper focuses on five aspects: inter-drug relationship discovery, assisted diagnosis, personalized recommendation, decision support and intelligent prediction. The latest research progress on medical knowledge graphs is introduced, and relevant suggestions are made in light of the current challenges and problems faced by medical knowledge graphs to provide reference for promoting the wide application of medical knowledge graphs.
Pattern Recognition, Automated ; Medical Informatics

DNA sensor, a kind of pattern recognition receptor (PRR), is widely expressed in innate immune cells. It activates the inflammatory signaling pathways and triggers an innate immune response by recognizing the pathogens or DNA in abnormal host cells. DNA-dependent activator of IFN-regulatory factors (DAI) is the first cytoplasmic DNA receptor discovered, which plays an important role in regulating the innate immune responses characterized by induction of interferon and programmed cell death. The article summarizes the molecular characteristics of DAI, its downstream signaling pathways, and its role and mechanism in anti-infective immunity, tumor immunity and inflammatory diseases. It also makes a preliminary exploration of the correlation between DAI and transplantation immunology, and provides a new target for the therapy of various immune diseases.
DNA/metabolism* ; Receptors, Pattern Recognition ; Immunity, Innate ; Signal Transduction/genetics* ; DNA-Binding Proteins/genetics*

Bibliometric and scientific knowledge graph methods were used to analyze the research status and hot spots of acupuncture-moxibustion in treatment of myofascial pain syndrome (MPS) and explore its development trend. The articles of both Chinese and English versions relevant to MPS treated by acupuncture-moxibustion were searched in CNKI, VIP, Wanfang, SinoMed and WOS from the database inception to March 20, 2023. Using Excel2016, CiteSpace6.2.R2 and VOSviewer1.6.18, the visual analysis was conducted by means of the cooperative network, keyword co-occurrence, keyword timeline, keyword emergence, etc. From Chinese databases and WOS database, 910 Chinese articles and 300 English articles were included, respectively. The annual publication volume showed an overall rising trend. Literature output of English articles was concentrated in Spain, China, and the United States, of which, there was less cross-regional cooperation. In the keyword analysis, regarding acupuncture-moxibustion therapy, Chinese articles focused on "acupuncture", "electroacupuncture" and "acupotomy"; while, "dry needling" and "injection" were dominated for English one. Clinical study was the current hot spot in Chinese databases, in comparison, the randomized controlled double-blind clinical trial was predominant in WOS. Both Chinese and English articles were limited in the report of mechanism research. The cooperation among research teams should be strengthened to conduct comparative research, dose-effect research and effect mechanism research with different methods of acupuncture-moxibustion involved so that the evidences can be provided for deeper exploration.
Humans ; Moxibustion ; Pattern Recognition, Automated ; Acupuncture Therapy ; Myofascial Pain Syndromes/therapy* ; Electroacupuncture

To explore the methods of the explicitation of implicit knowledge and the construction of knowledge graph on moxibustion in medical case records of ZHOU Mei-sheng's Jiusheng. The medical case records data of Jiusheng was collected, the frequency statistic was analyzed based on Python3.8.6, complex network analysis was performed using Gephi9.2 software, community analysis was performed by the ancient and modern medical case cloud platform V2.3.5, and analysis and verification of correlation graph and weight graph were proceed by Neo4j3.5.25 image database. The disease systems with frequency≥10 % were surgery, ophthalmology and otorhinolaryngology, locomotor, digestive and respiratory systems. The diseases under the disease system were mainly carbuncle, arthritis, lumbar disc herniation and headache. The commonly used moxibustion methods were fumigating moxibustion, blowing moxibustion, direct moxibustion and warming acupuncture. The core prescription of points obtained by complex network analysis included Yatong point, Zhiyang(GV 9), Sanyinjiao(SP 6), Dazhui(GV 14), Zusanli(ST 36), Lingtai(GV 10), Xinshu(BL 15), Zhijian point and Hegu(LI 4), which were basically consistent with high-frequency points. A total of 6 communities were obtained by community analysis, corresponding to different diseases. Through the analysis of correlation graph, 13 pairs of strong association rule points were obtained. The correlation between Zhiyang(GV 9)-Dazhui(GV 14) and Yatong point-Lingtai(GV 10) was the strongest. The acupoints with high correlation with Yatong point were Zhiyang(GV 9), Lingtai(GV 10), Dazhui(GV 14), Zusanli(ST 36) and Sanyinjiao(SP 6). In the weight graph of the high-frequency disease system, the relationship of the first weight of the surgery system disease was fumigating moxibustion-carbuncle-Yatong point, and the relationship of the first weight of the ophthalmology and otorhinolaryngology system disease was blowing moxibustion-laryngitis-Hegu (LI 4). The results of correlation graph and weight graph are consistent with the results of data mining, which can be used as an effective way to study the knowledge base of moxibustion diagnosis and treatment in the future.
Humans ; Moxibustion ; Carbuncle ; Pattern Recognition, Automated ; Acupuncture Therapy ; Acupuncture Points

How the brain perceives objects and classifies perceived objects is one of the important goals of visual cognitive neuroscience. Previous research has shown that when we see objects, the brain's ventral visual pathway recognizes and classifies them, leading to different ways of interacting with them. In this paper, we summarize the latest research progress of the ventral visual pathway related to the visual classification of objects. From the perspective of the neural representation of objects and its underlying mechanisms in the visual cortex, we summarize the current research status of the two important organizational dimensions of object animacy and real-world size, provide new insights, and point out the direction of further research.
Brain Mapping/methods* ; Magnetic Resonance Imaging ; Pattern Recognition, Visual ; Photic Stimulation ; Visual Cortex ; Visual Pathways

Visual object recognition in humans and nonhuman primates is achieved by the ventral visual pathway (ventral occipital-temporal cortex, VOTC), which shows a well-documented object domain structure. An on-going question is what type of information is processed in the higher-order VOTC that underlies such observations, with recent evidence suggesting effects of certain visual features. Combining computational vision models, fMRI experiment using a parametric-modulation approach, and natural image statistics of common objects, we depicted the neural distribution of a comprehensive set of visual features in the VOTC, identifying voxel sensitivities with specific feature sets across geometry/shape, Fourier power, and color. The visual feature combination pattern in the VOTC is significantly explained by their relationships to different types of response-action computation (fight-or-flight, navigation, and manipulation), as derived from behavioral ratings and natural image statistics. These results offer a comprehensive visual feature map in the VOTC and a plausible theoretical explanation as a mapping onto different types of downstream response-action systems.
Animals ; Brain Mapping ; Humans ; Magnetic Resonance Imaging ; Occipital Lobe ; Pattern Recognition, Visual ; Photic Stimulation ; Temporal Lobe ; Visual Pathways/diagnostic imaging* ; Visual Perception

Diabetic nephropathy (DN) is currently the most common complication of diabetes. It is considered to be one of the leading causes of end-stage renal disease (ESRD) and affects many diabetic patients. The pathogenesis of DN is extremely complex and has not yet been clarified; however, in recent years, increasing evidence has shown the important role of innate immunity in DN pathogenesis. Pattern recognition receptors (PRRs) are important components of the innate immune system and have a significant impact on the occurrence and development of DN. In this review, we classify PRRs into secretory, endocytic, and signal transduction PRRs according to the relationship between the PRRs and subcellular compartments. PRRs can recognize related pathogen-associated molecular patterns (PAMPs) and danger-associated molecular patterns (DAMPs), thus triggering a series of inflammatory responses, promoting renal fibrosis, and finally causing renal impairment. In this review, we describe the proposed role of each type of PRRs in the development and progression of DN.
Alarmins/physiology* ; C-Reactive Protein/physiology* ; Diabetic Nephropathies/etiology* ; Endocytosis ; Humans ; Immunity, Innate ; Mannose-Binding Lectin/physiology* ; Pathogen-Associated Molecular Pattern Molecules ; Receptors, Pattern Recognition/physiology* ; Serum Amyloid P-Component/physiology* ; Signal Transduction

The aim of this paper was to study the influence of triptolide in the immune response pathways of acquired immune deficiency syndrome( AIDS). Target proteins of triptolide and related genes of AIDS were searched in PubChem and Gene databases on line. Molecular networks and canonical pathways comparison analyses were performed by bioinformatics software( IPA). There were 15 targets proteins of triptolide and 258 related genes of AIDS. Close biological relationships of molecules of triptolide and AIDS were established by networks analysis. There were 21 common immune response pathways of triptolide and AIDS,including neuroinflammation signaling pathway,Th1 and Th2 activation pathway and role of pattern recognition receptors in recognition of bacteria and viruses. Triptolide stimulated immune response pathways by the main molecules of IFNγ,JAK2,NOD1,PTGS2,RORC. IFNγ is the focus nodes of triptolide and AIDS,and regulates genes of AIDS directly or indirectly. Triptolide may against AIDS by regulating molecules IFNγ in immune response pathways.
Acquired Immunodeficiency Syndrome ; drug therapy ; immunology ; Computational Biology ; Diterpenes ; pharmacology ; Epoxy Compounds ; pharmacology ; Gene Regulatory Networks ; Humans ; Interferon-gamma ; genetics ; Phenanthrenes ; pharmacology ; Receptors, Pattern Recognition ; immunology ; Signal Transduction ; T-Lymphocytes ; immunology