Breast cancer has become the malignant tumor with the highest incidence rate among women， seriously threatening the life and health of women all over the world. The pathogenic factors and development mechanisms of breast cancer are complex and diverse. The development of breast cells from ordinary hyperplasia to atypical hyperplasia， and from pre-cancerous lesions to cancerous lesions， is a long-term progressive process. Therefore， early screening and prevention of breast cancer is particularly important. Western medicine has a relatively mature treatment program for breast cancer， which is mainly based on surgery and systemic treatment， whereas the ensuing complications and adverse reactions often bring a heavy burden to patients. For the precancerous lesions of breast cancer， surgery is also the mainstay of treatment. In recent years， traditional Chinese medicine （TCM） has increasingly highlighted its advantages in the prevention and treatment of breast cancer. Increasing studies have shown that in the prevention and treatment of breast cancer and pre-cancerous lesions， TCM compound prescriptions， single herbs or herb pairs， and active components are able to regulate a variety of intracellular signaling pathways through multi-targets to inhibit the proliferation and invasion， promote the apoptosis and autophagy of tumor cells， and regulate the cell cycle and the immune microenvironment， thus exerting anti-tumor effects. At the same time， they can significantly attenuate the toxic side effects of radiotherapy and drug resistance of patients. However， the specific mechanisms of TCM in the prevention and treatment of breast cancer and precancerous lesions have not been fully clarified. The available studies are tanglesome regarding the TCM inhibition of tumor development through the regulation of classical signaling pathways such as phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR）， Wnt/β-catenin， and Notch， which still need to be verified by a large number of clinical and experimental studies. Therefore， this paper reviews the research progress in the prevention and treatment of breast cancer and precancerous lesions by TCM through interfering with the relevant signaling pathways in recent years， aiming to summarize the possible mechanisms of TCM in the prevention and treatment of breast cancer and provide references for subsequent studies.

Employing bibliometric methods and adhering to principles of textual research， this study systematically investigated prescription source， formula name， composition evolution， dose evolution， origin， processing， ancient and modern applications of Xiaofengsan. Xiaofengsan， also known as Renshen Xiaofengsan and Chantui Xiaofengsan， was first recorded in the Taiping Huimin Hejijufang（hereafter referred to as Jufang） of the Southern Song dynasty. The formula composition included Schizonepetae Spica， Glycyrrhizae Radix et Rhizoma， Chuanxiong Rhizoma， Notoptery Rhizoma et Radix， Bombyx Batryticatus， Saposhnikoviae Radix， Poria， Cicadae Periostracum， Pogostemonis Herba， Ginseng Radix et Rhizoma， Magnoliae Officinalis Cortex and Citri Reticulatae Pericarpium， a total of 12 medicinal materials. In terms of the evolution of formula composition， formulas across dynasties largely aligned with those recorded in Jufang， with only minor variations in application. The results of the formula dosage research indicated that one dose of medication in Jufang corresponded to the following modern dosages：Schizonepetae Spica of 82.6 g， Glycyrrhizae Radix et Rhizoma of 82.6 g， Chuanxiong Rhizoma of 82.6 g， Notoptery Rhizoma et Radix of 82.6 g， Bombyx Batryticatus of 82.6 g， Saposhnikoviae Radix of 82.6 g， Poria of 82.6 g， Cicadae Periostracum of 82.6 g， Pogostemonis Herba of 82.6 g， Ginseng Radix et Rhizoma of 82.6 g， Magnoliae Officinalis Cortex of 20.65 g and Citri Reticulatae Pericarpium of 20.65 g， the origins of all the constituent drugs were consistent with the 2020 edition of Pharmacopoeia of the People's Republic of China. The results of the investigation into the decoction method indicated that the aforementioned drugs should be finely ground into powder（pass through the No.5 sieve）， and 8.26 g was taken for each dose， which was taken with the clear liquid obtained by steeping tea leaves in boiling water for several minutes. This mixture was administered three times daily， 30 min after meals. The ancient functional indications of this formula mainly involved dispelling wind-heat， eliminating pathogenic factors and regulating the middle Jiao. It primarily treated all wind-heat syndromes manifesting as skin diseases， predominantly affecting the upper body， especially the head and face. The diseases involved in modern applications were mostly dermatological diseases， including urticaria， eczema， atopic dermatitis and others. In this paper， by combing the relevant ancient literature， the key information of Xiaofengsan was textual researched， in order to provide reference for the modern application and development of this formula.

ObjectiveTo address the challenges of unstructured classical Chinese expressions， nested entity relationships， and limited annotated data in famous traditional Chinese medicine（TCM） case records， this study proposes a joint relation extraction framework that integrates data augmentation and entity mapping， aiming to support the construction of TCM diagnostic knowledge graphs and clinical pattern mining. MethodsWe developed an annotation structure for entities and their relationships in TCM case texts and applied a data augmentation strategy by incorporating multiple ancient texts to expand the relation extraction dataset. A cascade binary tagging framework for relation triple extraction（CasRel） model for TCM semantics was designed， integrating a pre-trained bidirectional encoder representations from transformers（BERT） layer for classical TCM texts to enhance semantic representation， and using a head entity-relation-tail entity mapping mechanism to address entity nesting and relation overlapping issues. ResultsExperimental results showed that the CasRel model， combining data augmentation and entity mapping， outperformed the pipeline-based Bert-Radical-Lexicon（BRL）-bidirectional long short-term memory（BiLSTM）-Attention model. The overall precision， recall， and F₁-score across 12 relation types reached 65.73%， 64.03%， and 64.87%， which represent improvements of 14.26%， 7.98%， and 11.21% compared to the BRL-BiLSTM-Attention model， respectively. Notably， the F₁-score for tongue syndrome relations increased by 22.68%（69.32%）， and the prescription-syndrome relations performed the best with the F₁-score of 70.10%. ConclusionThe proposed framework significantly improves the semantic representation and complex dependencies in TCM texts， offering a reusable technical framework for structured mining of TCM case records. The constructed knowledge graph can support clinical syndrome differentiation， prescription optimization， and drug compatibility， providing a methodological reference for TCM artificial intelligence research.

Cholangiocarcinoma (CCA) is a malignancy characterized by tumor cells originating in the liver or bile ducts, exhibiting features of cholangiocyte differentiation. It poses a significant clinical challenge due to the limited diagnostic and therapeutic options available. Robust animal models are essential for advancing our understanding of CCA pathogenesis and developing effective treatments. This review provides a comprehensive overview of CCA mouse models, highlighting various approaches, including chemical induction, genetically engineered models, and tumor xenografts. Each model is discussed in terms of its establishment techniques, pathological characteristics, and research significance, with a focus on intrahepatic CCA. Chemical induction models, such as diethylnitrosamine- and azoxymethane-induced models, offer insights into tumorigenesis processes, whereas genetically modified models involving alterations in key genes such as Kirsten rat sarcoma viral oncogene homolog, tumor protein 53, and isocitrate dehydrogenase serve as important tools for studying the molecular mechanisms underlying CCA. Xenograft models, including patient-derived xenografts, bridge the gap between experimental research and clinical applications, allowing for precise therapeutic evaluations. By comparing these models, this review underscores their respective advantages and limitations, paving the way for future studies aiming to optimize and innovate CCA modeling strategies.

Through data collection and collation combined with bibliometrics， this study conducted a series of textual research on Yanghetang， such as the name and origin， the evolution of prescription composition and modern clinical application. Yanghetang was first recorded in Bencao Yidu of WANG Ang in the Qing dynasty. In addition to Yanghetang， there were 3 bynames of Jiawei Yanghetang， Quanshengji Yanghetang and Zhenjun Yanghetang. Regarding the composition of the formula， a total of 4 versions of Yanghetang were collected. The first version is the 5 medicines version of Cervi Cornus Colla， Rehmanniae Radix Praeparata， Cinnamomi Cortex， Zingiberis Rhizoma and Ephedrae Herba in Bencao Yidu. The second version is the 7 medicines version of Waike Zhengzhi Quanshengji， changing Zingiberis Rhizoma to Zingiberis Rhizoma Praeparatum Carbonisata（ZRPC） and adding Sinapis Semen and Glycyrrhizae Radix et Rhizoma（GRR） on the basis of Bencao Yidu， and most of the Yanghetang is of this version. The third version is the 6 medicines version of Wushi Yifang Huibian， that is， on the basis of Bencao Yidu， Zingiberis Rhizoma is changed into ZRPC， and Sinapis Semen is added. The fourth version is the 6 medicines version in Yifang Jiedu， that is， on the basis of Bencao Yidu， Zingiberis Rhizoma is changed into Zingiberis Rhizoma Praeparatum， and GRR Praeparata cum Melle is added. Regarding the dose of Yanghetang， the doses of the medicines in Waike Zhengzhi Quanshengji was converted into the modern doses as follows：37.3 g of Rehmanniae Radix Praeparata， 1.87 g of Ephedrae Herba， 11.19 g of Cervi Cornus Colla， 7.46 g of Sinapis Semen， 3.73 g of Cinnamomi Cortex， 3.73 g of GRR， and 1.87 g of ZRPC. The origins of the above medicines are consistent with the 2020 edition of Chinese Pharmacopoeia. The processing specification of Rehmanniae Radix Praeparata is steaming method， ZRPC is ginger charcoal， Sinapis Semen is the fried products， and the rest of the medicines are raw products. The decoction method was verified by the decoction method in Chonglou Yuyao， which is similar in the time， and it is recommended that the above medicines should be added with 600 mL of water， decocted to 100 mL， and taken warmly 30 min after meal. For each dose， it is recommended to use 1-3 doses per day according to the doctor's advice in combination with clinical practice. The diseases involved in the ancient applications involved 42 diseases in 11 departments， including orthopedics， dermatology and gynecology， which were dominated by Yin-cold syndrome. However， the diseases involved in modern research also include 148 related diseases in 10 departments， such as orthopedics， obstetrics and gynecology， which is consistent with the ancient books. In recent years， the research hotspots of Yanghetang have focused on more than 10 fields， including osteoblasts， malignant tumors， wound healing， traditional Chinese medicine fumigation and so on， which are widely used. It is suitable for comprehensive research and development because of its rational formula composition， clear origin， processing and decoction method， and wide clinical application.

Most cancers are currently incurable, partly due to abnormal post-translational modifications (PTMs). In this study, we initially used multiple myeloma (MM) as a working model and found that SUMOylation activating enzyme subunit 1 (SAE1) promotes the malignancy of MM. Through proteome microarray analysis, SAE1 was identified as a potential target for bioactive colcemid or its derivative colchicine. Elevated levels of SAE1 were associated with poor clinical survival and increased MM proliferation in vitro and in vivo. Additionally, SAE1 directly SUMOylated and upregulated the total protein expression of p27, leading to LLPS-mediated nuclear export of p27. Our study also demonstrated the involvement of SAE1 in other types of cancer cells, and provided the first monomer crystal structure of SAE1 and its key binding model with colchicine. Colchicine also showed promising results in the Patient-Derived Tumor Xenograft (PDX) model. Furthermore, a controlled clinical trial with 56 MM patients demonstrated the clinical efficacy of colchicine. Our findings reveal a novel mechanism by which tumor cells evade p27-induced cellular growth arrest through p27 SUMOylation-mediated nuclear export. SAE1 may serve as a promising therapeutic target, and colchicine may be a potential treatment option for multiple types of cancer in clinical settings.

Objective To evaluate the results of anorectal dynamics in patients with severe rec-tocele.Methods A retrospective analysis was conducted on the clinical data of 38 patients defini-tively diagnosed with severe rectocele at the pelvic floor center of the anorectal department of Nanjing Hospital of Traditional Chinese Medicine from January 2020 to January 2023.All patients underwent anorectal manometry,and the results of anorectal dynamics were analyzed.Results A total of 15 pa-tients(39.47％)had elevated anal resting pressure(ARP),20(52.63％)had normal ARP,and 3(7.89％)had decreased ARP.Five patients(13.16％)had elevated maximum anal sphincter pressure(MASP),9(23.68％)had normal MASP,and 24(63.16％)had decreased MASP.Nor-mal defecation relaxation reflex was observed in 15 patients(39.47％),and abnormal defecation re-laxation reflex was observed in 23 patients(60.53％).Ten patients(26.32％)had normal rectal defecation pressure,and 28(73.68％)had decreased rectal defecation pressure.Eleven patients(28.95％)had elevated rectal initial sensory threshold(RIST),27(71.05％)had normal RIST.Fifteen patients(39.47％)had elevated rectal defecation sensory threshold,21(55.26％)had normal rectal defecation sensory threshold,and 2(5.26％)had decreased rectal defecation sensory threshold.Three patients(7.89％)had elevated rectal maximum tolerable volume,26(68.42％)had normal rectal maximum tolerable volume,and 9(23.68％)had decreased rectal maximum tolerable vol-ume.ARP was moderately positively correlated with the chronic constipation severity(CSS)score(P=0.007,r=0.429),and abnormal defecation relaxation reflex was moderately negatively correla-ted with the CSS score(P=0.019,r=-0.329).In 3 patients(7.89％),both ARP and MASP were decreased,and both ARP and MASP were elevated in 5 patients(13.16％).Conclusion Pre-operative anorectal dynamics analysis is necessary for patients with severe rectocele to formulate a reasonable individualized surgical plan and postoperative rehabilitation program.

OBJECTIVE: To screen the population for acupuncture treatment of neck pain, using functional magnetic resonance imaging (fMRI) technology and based on machine learning algorithms. METHODS: Eighty patients with neck pain were recruited. Using FPX25 handheld pressure algometer, the tender points were detected in the areas with high-frequent onset of neck pain and high degree of acupoint sensitization. Acupuncture was delivered at 4 tender points with the lowest pain threshold, once every two days; and the treatment was given 3 times a week and for 2 consecutive weeks. The amplitude of low-frequency fluctuation (ALFF) of the brain before treatment was taken as a predictive feature to construct support vector machine (SVM), logistic regression (LR), and K-nearest neighbors (KNN) models to predict the responses of neck pain patients to acupuncture treatment. A longitudinal analysis of the ALFF features was performed before and after treatment to reveal the potential biological markers of the reactivity to the acupuncture therapy. RESULTS: The SVM model could successfully distinguish high responders (48 cases) and low responders (32 cases) to acupuncture treatment, and its accuracy rate reached 82.5%. Based on the SVM model, the ALFF values of 4 brain regions were identified as the consistent predictive features, including the right middle temporal gyrus, the right superior occipital gyrus, and the bilateral posterior cingulate gyrus. In the patients with high acupuncture response, the ALFF value in the left posterior cingulate gyrus decreased after treatment (P<0.05), whereas in the patients with low acupuncture response, the ALFF value in the right superior occipital gyrus increased after treatment (P<0.01). The longitudinal functional connectivity (FC) analysis found that compared with those before treatment, the high responders showed the enhanced FC after treatment between the left posterior cingulate gyrus and various regions, including the bilateral Crus1 of the cerebellum, the right insula, the bilateral angular gyrus, the left medial superior frontal gyrus, and the left middle cingulate gyrus (GRF: corrected, voxel level: P<0.05, mass level: P<0.05). In contrast, the low responders exhibited the enhanced FC between the left posterior cingulate gyrus and the left Crus2 of the cerebellum, the left middle temporal gyrus, the right posterior cingulate gyrus, and the left angular gyrus; besides, FC was reduced in low responders between the left posterior cingulate gyrus and the right supramarginal gyrus (GRF: corrected, voxel level: P<0.05, mass level: P<0.05). CONCLUSION This study validates the practicality of pre-treatment ALFF feature prediction for acupuncture efficacy on neck pain. The therapeutic effect of acupuncture on neck pain is potentially associated with its impact on the default mode network, and then, alter the pain perception and emotional regulation.
Humans ; Neck Pain/physiopathology* ; Acupuncture Therapy ; Female ; Male ; Adult ; Middle Aged ; Machine Learning ; Magnetic Resonance Imaging ; Young Adult ; Brain/physiopathology* ; Acupuncture Points ; Aged

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*