Puji Xiaoduyin， a specialized formula for the swollen-head epidemic， was recorded in the Catalogue of Ancient Classical Formula （the Second Batch）-Han Medicine， published in September 2023. It had been inherited and developed by medical experts of successive generations and passed down to this day. This paper sorted out the historical evolution of this formula using bibliometric methods. It also comprehensively analyzed key information on the formula name， historical origin， drug dosage， herb origin， processing methods， decocting methods， function， and clinical applications. Additionally， this paper analyzed the application of this formula in both modern and ancient times. Results showed that the formula was first recorded as "Puji Xiaodu Yinzi" in LI Dongyuan's Proven Formulas written by LI Gao from the Jin dynasty. The medicinal composition and dosage were： Scutellariae Radix and Coptidis Rhizoma （20.65 g each）， Ginseng Radix et Rhizoma 12.39 g， Scrophulariae Radix， Citri Reticulatae Pericarpium， and Glycyrrhizae Radix et Rhizoma （8.26 g each）， Forsythiae Fructus， Arctii Fructus， Isatidis Radix， and Lasiosphaera Calvatia （4.13 g each）， Bombyx Batryticatus and Cimicifugae Rhizoma （2.891 g each）， Bupleuri Radix and Platycodonis Radix （8.26 g each）. These medicines were grounded to fine powder. One dose， including 20.65 g of the powder， was mixed with 600 mL of water and decocted to 300 mL. After abandoning slag， the medicine should be taken warm frequently. In the formula， Bombyx Batryticatus is stir-fired. With the effect of dispersing wind and clearing heat， removing stagnation and dissipating mass， the formula is specialized in swollen-head epidemic， pestilence， red and swelling head， face， and neck， dry mouth and tongue， as well as other diseases resulting from toxic heat stagnated in the upper jiao. The formula is widely used in treating diseases involving the respiratory， dermal， ophthalmologic， otolaryngologic， and nervous systems. The formula is most frequently used for respiratory diseases， with a wide range of symptoms including parotitis/mumps （66 times）， followed by tonsillitis （28 times）. In conclusion， the broadly applied formula has accurate efficacy and great development value.

Puji Xiaoduyin， a specialized formula for the swollen-head epidemic， was recorded in the Catalogue of Ancient Classical Formula （the Second Batch）-Han Medicine， published in September 2023. It had been inherited and developed by medical experts of successive generations and passed down to this day. This paper sorted out the historical evolution of this formula using bibliometric methods. It also comprehensively analyzed key information on the formula name， historical origin， drug dosage， herb origin， processing methods， decocting methods， function， and clinical applications. Additionally， this paper analyzed the application of this formula in both modern and ancient times. Results showed that the formula was first recorded as "Puji Xiaodu Yinzi" in LI Dongyuan's Proven Formulas written by LI Gao from the Jin dynasty. The medicinal composition and dosage were： Scutellariae Radix and Coptidis Rhizoma （20.65 g each）， Ginseng Radix et Rhizoma 12.39 g， Scrophulariae Radix， Citri Reticulatae Pericarpium， and Glycyrrhizae Radix et Rhizoma （8.26 g each）， Forsythiae Fructus， Arctii Fructus， Isatidis Radix， and Lasiosphaera Calvatia （4.13 g each）， Bombyx Batryticatus and Cimicifugae Rhizoma （2.891 g each）， Bupleuri Radix and Platycodonis Radix （8.26 g each）. These medicines were grounded to fine powder. One dose， including 20.65 g of the powder， was mixed with 600 mL of water and decocted to 300 mL. After abandoning slag， the medicine should be taken warm frequently. In the formula， Bombyx Batryticatus is stir-fired. With the effect of dispersing wind and clearing heat， removing stagnation and dissipating mass， the formula is specialized in swollen-head epidemic， pestilence， red and swelling head， face， and neck， dry mouth and tongue， as well as other diseases resulting from toxic heat stagnated in the upper jiao. The formula is widely used in treating diseases involving the respiratory， dermal， ophthalmologic， otolaryngologic， and nervous systems. The formula is most frequently used for respiratory diseases， with a wide range of symptoms including parotitis/mumps （66 times）， followed by tonsillitis （28 times）. In conclusion， the broadly applied formula has accurate efficacy and great development value.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Yttrium-90 microsphere selective internal radiation therapy (SIRT), also known as transarterial radioembolization, has become one of the pivotal treatments for liver cancer, particularly for selected advantageous patient groups. This review summarizes the characteristics of different patients with liver cancer that could obtain maximum benefit from SIRT and discusses key factors affecting efficacy and safety, including tumor characteristics, liver function, patient performance status, and treatment intent. In evaluating appropriate candidates, mapping serves as a crucial simulation procedure to assess tumor vascular anatomy, predict lung shunting, and guide catheter positioning and dose planning. This procedure substantially enhances therapeutic precision while minimizing the risk of nontarget radiation-related adverse events, such as radiation-induced pneumonitis and gastrointestinal toxicity. Several studies have suggested that SIRT is not only suitable for patients with early or limited hepatocellular carcinoma but can also be used as a bridging therapy for liver transplantation and conversion therapy for unresectable liver cancers. In combination with systemic treatments, SIRT has demonstrated survival benefits in patients with unresectable liver cancer. This review also highlights the importance of further optimizing patient screening through personalized dosimetry and mapping to ensure the precision and safety of treatment. A thorough review of relevant literature and clinical practice offers clinicians comprehensive suggestions on patient screening and clarifies the promise of SIRT in the liver cancer population.

OBJECTIVES: We propose a Contrastive Regional Attention and Prior Knowledge-Infused U-Transformer model (CRAKUT) to address the challenges of imbalanced text distribution, lack of contextual clinical knowledge, and cross-modal information transformation to enhance the quality of generated radiology reports. METHODS: The CRAKUT model comprises 3 key components, including an image encoder that utilizes common normal images from the dataset for extracting enhanced visual features, an external knowledge infuser that incorporates clinical prior knowledge, and a U-Transformer that facilitates cross-modal information conversion from vision to language. The contrastive regional attention in the image encoder was introduced to enhance the features of abnormal regions by emphasizing the difference between normal and abnormal semantic features. Additionally, the clinical prior knowledge infuser within the text encoder integrates clinical history and knowledge graphs generated by ChatGPT. Finally, the U-Transformer was utilized to connect the multi-modal encoder and the report decoder in a U-connection schema, and multiple types of information were used to fuse and obtain the final report. RESULTS: We evaluated the proposed CRAKUT model on two publicly available CXR datasets (IU-Xray and MIMIC-CXR). The experimental results showed that the CRAKUT model achieved a state-of-the-art performance on report generation with a BLEU-4 score of 0.159, a ROUGE-L score of 0.353, and a CIDEr score of 0.500 in MIMIC-CXR dataset; the model also had a METEOR score of 0.258 in IU-Xray dataset, outperforming all the comparison models. CONCLUSIONS The proposed method has great potential for application in clinical disease diagnoses and report generation.
Humans ; Radiology Information Systems ; Radiology

This article systematically reviews the characteristics and trends of the writing, editing, publication and promotion of physiology textbooks in China from the late 19th century to the present, focusing on the introduction, development and innovation of Chinese physiology textbooks. The development of physiology textbooks in China is divided into four main stages: the introduction and initial development of physiology textbooks from the late 19th century to 1925; the localization and diversification of textbooks from 1926 to 1949, after the establishment of the Chinese Physiological Society; the exploratory phase of textbook construction after the founding of the People's Republic of China from 1949 to 1976; the formation and innovation of the textbook development process from 1977 to the present, following the restoration of the college entrance examination. For each phase, the article not only records the historical development of physiology textbooks, but also analyzes the evolution of their content, writing styles and the interaction with the social and political contexts. The article summarizes the characteristics and experiences of all these four phases. Special attention is given to the comprehensive statistical analysis of physiology textbooks published since the restoration of the college entrance examination and Economic Reform and Opening-up in 1977, revealing the changes in the number, publication trends and academic features of textbooks during this period. Finally, the article presets the future development of physiology textbooks in China, proposing that textbook writing should integrate aspects such as ideological and political education, medical humanities, basic and clinical medicine, health education, scientific research and international exchange and collaboration. The article also advocates for the application of new technologies and methods, such as artificial intelligence, virtual teaching models and knowledge graphs, to support "personalized learning". This research provides a systematic reference for the study of the history of medical education and offers theoretical support for the future innovation of physiology textbook in China.
Humans ; China ; History, 19th Century ; History, 20th Century ; History, 21st Century ; Physiology/education* ; Textbooks as Topic/history*

OBJECTIVE: To preliminarily investigate the effects and mechanism of action of Yishen Yangsui Formula (, YSYSF)on the recovery of neurological function in rats with degenerative cervical myelopathy. METHODS: Fifty adult SD female rats were randomly divided into control group, sham group, model group, YSYSF group and positive drug group by using randomized numerical table method. In the model group, YSYSF group and positive drug group, polyvinyl alcohol acrylamide interpenetrating network hydrogel(water-absorbent swelling material) was used to construct a rat spinal cord chronic compression model. The sham group was implanted with the water-absorbent swelling material and then removed without causing spinal cord compression. The control group, the sham group and the model group were given equal amounts of saline by gavage, the group of YSYSF was given Chinese herbal medicine soup by gavage 9.1 g·kg^-1 once a day, and the positive drug group was given tetrahexylsalicylglucoside sodium monosialate ganglioside by intraperitoneal injection 4.2 mg·kg^-1 once a day. The motor function of the rats was assessed by the BBB method after 1, 3, 7, and 14 d of drug administration. The spinal cord tissues were taken from rats executed 14 d after drug administration, and the morphological changes of the spinal cord compression site were observed by HE staining, and the expression levels of Caspase-1, GSDMD, NLRP3, PYCARD, IL-1β, and IL-18 were detected in the area of spinal cord injury by Western blot method. RESULTS: The BBB scores of the control group and the sham group were normal at all time points after modeling, which were higher than the BBB scores of the model group, the YSYSF, and the positive drug group (P<0.05). From the 3rd day after gavage, at all time points, the BBB scores of rats in the YSYSF group and the positive drug group were higher than those of rats in the model group (P<0.05). The staining pattern of HE spinal cord tissue was normal in the control group and the sham group, and the HE spinal cord in the model group was severely damaged with a large number of neuron deaths, whereas the damage to the spinal cord and neuron cells was reduced in the YSYSF group and the positive drug group. The expression levels of caspase-1, GSDMD, NLRP3, PYCARD, IL-1β and IL-18 in the spinal cord of the model group were significantly higher than those of the sham group (P<0.0001), and the expression levels of caspase-1, GSDMD, NLRP3, PYCARD, IL-1β, and IL-18 in the YSYSF group and the drug group were significantly lower than those in the model group (P<0.05). CONCLUSION YSYSF can improve the motor function of rats with degenerative cervical spinal cord disease, alleviate the pathological changes, and promote the recovery of spinal cord neurological function. The specific mechanism may be related to the inhibition of the activation of inflammatory vesicles NLRP3 and PYCARD, the reduction of the release of inflammatory factors IL-1β and IL-18, the reduction of the expression of caspase-1 and GSDMD, the reduction of cellular death, and the inhibition of inflammatory response.
Animals ; Female ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Rats, Sprague-Dawley ; Pyroptosis/drug effects* ; Spinal Cord/pathology* ; NLR Family, Pyrin Domain-Containing 3 Protein ; Spinal Cord Diseases/drug therapy* ; Interleukin-1beta/metabolism*