Chronic eczema has a high prevalence in China， significantly impacting patients’ quality of life. Leveraging the unique advantages of pattern identification/syndrome differentiation and treatment， along with a holistic approach， traditional Chinese medicine （TCM）， which integrates internal and external therapies， has been widely applied in the management of chronic eczema. It has demonstrated significant efficacy and distinctive strengths in alleviating symptoms， reducing recurrence rates， maintaining disease stability， and enhancing patients’ quality of life. Oral administration of TCM（e.g. modified Longdan xiegan decoction） can improve patients’ clinical symptoms through systemic regulation. External use of TCM can directly act on the skin lesion with the help of steaming and washing， hydropathic compress， ointment and other forms. At the same time， it can effectively relieve the clinical symptoms of chronic eczema by combining with non-drug therapies such as acupuncture， moxibustion， acupoint catgut embedding， blood-letting puncture and cupping. In addition， characteristic therapies such as oral administration of TCM combined with external treatment， a combination of various external treatments and a combination of Chinese and Western medicine have also demonstrated certain advantages in regulating immune function， alleviating skin lesions， and relieving itching symptoms. These therapies cooperate with each other， creating a synergistic effect that treats both the symptoms and the root cause simultaneously. It is suggested that more high-quality， large-scale clinical research should be conducted in the future to systematically confirm the therapeutic advantages of TCM and further explore the specific molecular mechanism of action.

A 51-year-old male presented with nasal obstruction, followed by progressive hearing loss and blurred vision. Imaging identified space-occupying lesions in the paranasal sinuses, orbits, and paraspinal regions, while laboratory tests confirmed positive anti-proteinase 3 anti-neutrophil cytoplasmic antibody(PR3- ANCA) immunoglobulin G (IgG)and markedly elevated serum IgG4. Despite treatment with corticosteroids, immunosuppressants, and radiotherapy, the patient exhibited steroid dependency with relentless disease progression. Following multidisciplinary consultation, a diagnosis of inflammatory myofibroblastic tumor (IMT) coexisting with ANCA- associated vasculitis (AAV) was favored, though IgG4-related disease remained a critical differential. Ultimately, profound immunosuppression precipitated a severe herpesvirus infection, leading to disseminated intravascular coagulation and multiple organ dysfunction syndrome. This case underscores the rarity and diagnostic complexity of concurrent IMT and AAV, highlights the therapeutic dilemma of balancing primary disease control against fatal opportunistic infections, and emphasizes the critical role of multidisciplinary collaboration in the diagnosis and treatment of complex diseases.

ObjectiveTo explore the typical syndromes and their characteristic of symptoms and signs with high diagnostic value in patients with metabolic syndrome （MS）. MethodsTraditional Chinese medicine （TCM） diagnostic information was collected from 135 MS patients. Syndrome element differentiation and latent class analysis （LCA） were applied to identify the major TCM syndromes in MS patients. Symptoms were analyzed based on the differentiated syndromes， and a binary logistic regression model was constructed to determine symptoms and signs with high diagnostic value. ResultsA total of 135 MS patients were included， involving 163 symptoms and signs with a total frequency of 1749； twenty-three syndrome elements were extracted， 367 times frequency in total， among which 8 syndrome elements occurred ≥10 times with 323 frequencies （88.01% of the total）. These included location-related elements such as kidney （48 times）， spleen （14 times）， and stomach （14 times）， and nature-related elements such as phlegm （71 times）， yin deficiency （64 times）， dampness （57 times）， heat （42 times）， and qi deficiency （13 times）. Based on LCA， the 135 patients were categorized into two groups distinguished by the syndrome elements of dampness and phlegm， forming the "phlegm-dampness syndrome" as the major syndrome type. Nine high-frequency symptoms and signs associated with the phlegm-dampness syndrome were identified，i.e. obesity （39 times）， greasy coating （38 times）， slippery pulse （33 times）， white coating （31 times）， preference for fatty and heavy foods （30 times）， excessive urination （30 times）， fatigue and lack of strength （29 times）， wiry pulse （25 times）， and dark red tongue （25 times）. A binary logistic regression model was constructed combining these nine symptoms and signs with the LCA classification results， ultimately identifying obesity， greasy coating， fatigue and lack of strength， and white coating as independent factors associated with the phlegm-dampness syndrome in MS patients （P＜0.05）. ConclusionThe major TCM syndrome in MS patients is phlegm-dampness syndrome， and obesity， greasy coating， fatigue and lack of strength， and white coating are the typical symptoms and signs for diagnosing phlegm-dampness syndrome in MS patients.

BACKGROUND:As a common disease in middle-aged and elderly,osteoarthritis is difficult to cure,and the pathogenesis is not clear.Long non-coding RNA participates in the pathogenesis of osteoarthritis through many ways,such as regulating translation,promoting or inhibiting mRNA,and adsorbing miRNAs. OBJECTIVE:To review the types of common long non-coding RNA in osteoarthritis,and the influence of multiple long non-coding RNAs on the pathological factors related to osteoarthritis,to analyze the future application of long non-coding RNAs in osteoarthritis. METHODS:Literature retrieval was conducted in CNKI,WanFang Data,VIP database,PubMed,Web of Science and Sciencedirect databases,using the search terms of"osteoarthritis,degenerative joint disease,degenerative arthritis,OA,LncRNA,long non-coding RNA,long noncoding RNA,long intergenic non-coding RNA"in Chinese and English.All relevant literature published from 1976 and May 2024 was retrieved.After literature screening,induction,analysis and summary,93 articles were finally included for review. RESULTS AND CONCLUSION:This review collected 25 long non-coding RNAs that are well studied with osteoarthritis.Long non-coding RNAs,as a molecular sponge for miRNA,are competing endogenous RNAs to competitively adsorb miRNAs and then affect downstream targets.Long non-coding RNAs can regulate physiopathological processes such as chondrocyte apoptosis and proliferation,cartilage extracellular matrix degradation,and inflammatory responses.Long non-coding RNAs are expected to become a biomarker and potential therapeutic target for the clinical diagnosis and therapeutic prognosis of osteoarthritis,and it may become a new strategy for the clinical treatment of osteoarthritis in the future.

ObjectiveTo explore the effectiveness of health information dissemination and its influencing factors using the "Shanghai CDC" WeChat public account as a case study, providing references for public health institutions to optimize the use of official new media platforms for effective publicity. MethodsA total of 1 030 headline articles published on the "Shanghai CDC" WeChat public account between 2016 and 2019 were analyzed using content analysis and non-parametric tests to examine the impact of factors such as titles and content categories. ResultsFrom 2016 to 2019, the number of WeChat public account followers increased by 280 000, with the articles accumulating over 8.8 million views. The median (P₂₅, P₇₅) open rate of articles was 5.90% (3.69%, 10.31%), and the median (P₂₅, P₇₅) sharing and forwarding rate was 6.60% (4.25%, 9.17%). Factors such as the use of first- and second-person pronouns, degree adverbs, negative adverbs, explicit viewpoints, and title length all significantly affected the open rate of articles, with OR (95%CI) values of 0.175 (0.041‒0.756), 32.606 (2.350‒452.432), 4.079 (1.093‒15.230), 0.106 (0.028‒0.409), and 1.184 (1.063‒1.319),respectively (all P<0.05). In terms of content, statistical significant differences in dissemination effectiveness were observed across article categories and themes (P<0.05). In terms of article categories, articles related to news hotspots and service information had higher open rates of 9.58% and 14.00%, respectively. These two types of articles also obtained higher sharing and forwarding rates of 7.65% and 9.16%, respectively. In terms of article topics, compared with healthy life and health products, among the top four topics in terms of publication volume, the open rates of articles about infectious diseases and disease-causing biology and immunization programs were higher, accounting for 7.88% and 6.88%, respectively, with no significant difference in sharing and forwarding rates. ConclusionThe "Shanghai CDC" WeChat public account demonstrated good dissemination effectiveness. Enhancing article titles by increasing informational content and degree adverbs (e.g., "highly," "most," and "extremely") and negative adverbs (e.g., "no") can improve dissemination reach. Public health WeChat accounts should incorporate news hotspots or service information in their articles. While maintaining their strengths in disseminating knowledge on infectious diseases and immunization programs, they should also enhance public education in other professional fields within their scope of responsibility to improve the overall dissemination impact of health information.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.