BACKGROUND:Steroid-induced femoral head necrosis is mostly caused by long-term and extensive use of hormones,but its specific pathogenesis is not yet clear and needs further study. OBJECTIVE:To screen out the differential miRNAs in osteoclast exosomes after the intervention of Panax notoginseng saponins,and on this basis,to further construct an osteogenic-related ferroptosis regulatory network to explore the potential mechanism and research direction of steroid-induced osteonecrosis of the femoral head. METHODS:MTT assay was used to detect the toxic effects of different concentrations of dexamethasone and different mass concentrations of Panax notoginseng saponins on Raw264.7 cell line.Tartrate resistant acid phosphatase staining and TUNEL assay were used to detect the effects of Panax notoginseng saponins on osteoclast inhibition and apoptosis.Exosomes were extracted from cultured osteoclasts with Panax notoginseng saponins intervention.Exosomes from different groups were sequenced to identify differentially expressed miRNAs.CytoScape 3.9.1 was used to construct and visualize the regulatory network between differentially expressed miRNAs and mRNAs.Candidate mRNAs were screened by GO analysis and KEGG analysis.Finally,the differential genes related to ferroptosis were screened out,and the regulatory network of ferroptosis-related genes was constructed. RESULTS AND CONCLUSION:(1)The concentration of dexamethasone(0.1 μmol/L)and Panax notoginseng saponins(1 736.85 μg/mL)suitable for intervention of Raw264.7 cells was determined by MTT assay.(2)Panax notoginseng saponins had an inhibitory effect on osteoclasts and could promote their apoptosis.(3)Totally 20 differentially expressed miRNAs were identified from osteoclast-derived exosome samples,and 11 differentially expressed miRNAs related to osteogenesis were predicted by target mRNAs.The regulatory networks of 4 up-regulated differentially expressed miRNAs corresponding to 155 down-regulated candidate mRNAs and 7 down-regulated differentially expressed miRNAs corresponding to 238 up-regulated candidate mRNAs were constructed.(4)Twenty-four genes related to ferroptosis were screened out from the differential genes.Finally,12 networks were constructed(miR-98-5p/PTGS2,miR-23b-3p/PTGS2,miR-425-5p/TFRC,miR-133a-3p/TFRC,miR-185-5p/TFRC,miR-23b-3p/NFE2L2,miR-23b-3p/LAMP2,miR-98-5p/LAMP2,miR-182-5p/LAMP2,miR-182-5p/TLR4,miR-23b-3p/ZFP36,and miR-182-5p/ZFP36).These results indicate that Panax notoginseng saponins may regulate osteoblast ferroptosis by regulating the expression of miRNAs derived from osteoclast exosomes,thus providing a new idea for the study of the mechanism of steroid-induced femoral head necrosis.

To investigate the awareness of cognitive impairment disorders among residents of the Xizang Autonomous Region and its influencing factors, thereby providing a basis for targeted prevention and treatment efforts.

OBJECTIVE To investigate the ameliorative effect and potential mechanism of imperatorin （IMP） on doxorubicin （DOX） resistance in breast cancer. METHODS The effects of maximum non-toxic concentration （100 μg/mL） of IMP combined with different concentrations of DOX （12.5， 25， 50， 75， 100 μg/mL） on the proliferation of MCF-7/DOX cells were determined by MTT method. MCF-7/DOX cells were divided into blank control group （1‰ dimethyl sulfoxide）， DOX group （50 μg/mL）， IMP+DOX group （100 μg/mL IMP+50 μg/mL DOX） and IMP group （100 μg/mL）. mRNA and protein expressions of multidrug resistance protein 1 （MDR1） and multidrug resistance-associated protein 1 in each group were measured. The relevant pathways and targets involved in the improvement of DOX resistance in breast cancer cells by IMP were screened and validated by using transcriptome sequencing technology， along with gene ontology （GO） enrichment analyses and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analyses. RESULTS Compared with DOX alone， the combination of IMP and DOX reduced the half inhibitory concentration of DOX on MCF-7/DOX cells from 81.965 μg/mL to 43.170 μg/mL， the reverse fold was 1.90， and the mRNA expression of MDR1 was significantly down-regulated （P＜0.05）. The results of GO enrichment analyses and KEGG pathway enrichment analyses indicated that the reversal of DOX resistance in breast cancer by IMP was mainly associated with the regulation of biological processes such as detoxification， multiple biological processes， and cell killing. The main pathway involved was the p53 signaling pathway， and the key targets mainly included constitutively photomorphogenic protein 1 （COP1）， cyclin E1 （CCNE1）， growth arrest and DNA damage-inducible protein 45A E-mail：tangxilan1983@163.com （GADD45A） and GADD45B. The results of the verification experiments showed that compared with DOX group， there was a trend of up-regulation of COP1 mRNA， and significant down- regulation of CCNE1， GADD45A， and GADD45B mRNA expression in IMP+DOX group （P＜0.05）. CONCLUSIONS The effect of IMP in ameliorating DOX resistance in breast cancer is related to its regulation of COP1， CCNE1， GADD45A and GADD45B targets in the p53 signaling pathway.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

OBJECTIVE To provide a reference for optimizing the market access process for over-the-counter drugs （OTC） in China. METHODS Based on literature review， questionnaire survey was designed and distributed via the Wenjuanxing platform to respondents from pharmaceutical enterprises， drug regulatory agencies， industry associations， medical institutions and universities. The collected survey data were then subjected to statistical analysis. RESULTS A total of 154 questionnaires were collected， all of which were valid. Among the respondents， 58.5% were from pharmaceutical enterprises， 18.8% were from the field of drug regulation， and the remaining 22.7% were from universities and medical institutions. More than half of the respondents had been working for 10 years or more. A total of 89.6% of the respondents called for the establishment of an independent review system for OTC. Additionally， 88.3% believed it was necessary to establish an OTC monograph system based on China’s national conditions. Meanwhile， 73.4% of respondents believed it was necessary to standardize the monograph inclusion procedures and processes， while 77.3% thought the specific process for switching prescription drugs to OTC status should be improved. Furthermore， 91.0% of the respondents considered that real-world data/evidence could contribute to simplifying the OTC market approval pathway， although challenges related to data quality and data accessibility were acknowledged. CONCLUSIONS The review cycle for China’s OTC market access mechanism is relatively long. A localized adaptation and optimization path of “institutional reconstruction-technological innovation-regulatory innovation” in a trinity is proposed to provide a decision-making basis for establishing a scientific and efficient OTC regulatory system with international experience serving as a reference.

ObjectiveThis paper aims to use the digital muscle function assessment system Myoton PRO to assess the correlation between muscle tension，clinical characteristics， and traditional Chinese medicine（TCM） syndromes in patients with hepatolenticular degeneration ［also known as Wilson disease（WD）］. MethodsA total of 104 patients with WD accompanied by abnormal muscle tension（increased or decreased，hereinafter the same） who were hospitalized in the Brain Disease Centre of the First Affiliated Hospital of Anhui University of Chinese Medicine from April 2021 to November 2023 were selected，all of whom were subjected to TCM syndrome diagnosis and Myoton PRO for the measurement of F value of muscle tension，Goldstein， and UWDRS-N scales. The age of onset of the disease and disease duration were analyzed，and the differences and correlations of the above indexes in different TCM syndromes of WD were analyzed ResultsAmong the 104 patients with WD ，the phlegm and stasis syndrome was the most common（60 patients），followed by the damp-heat syndrome（33 patients），and the least common was the liver-kidney Yin deficiency syndrome（11 patients）. The F value of the phlegm and stasis syndrome group was higher than that of the liver-kidney Yin deficiency syndrome group and the damp-heat syndrome group（P<0.01）. The F value of the damp-heat syndrome group was higher than that of the liver-kidney Yin deficiency syndrome group（P<0.05），and the F value of the lower limbs of each group was higher than that of the upper limbs（P<0.01）. Goldstein and UWDRS-N scores of the patients in the phlegm and stasis syndrome group were higher than those in the damp-heat syndrome group and the liver-kidney Yin deficiency syndrome group（P<0.05）. There was no significant difference between the Goldstein and UWDRS-N scores of patients in the liver-kidney Yin deficiency syndrome group and the damp-heat syndrome group. Correlation analysis revealed that the age of onset and duration of the disease were positively correlated with the F values of the lower limbs（r=0.20，P<0.05，r=0.38，P<0.01）and had no significant correlation with those of the upper limbs. The F value levels of muscle tension of all limbs in the three groups of patients were positively correlated with the Goldstein and UWDRS-N scores（muscle tension of the upper limbs in the phlegm and stasis syndrome group，r=0.36，P<0.01，r=0.42，P<0.01. muscle tension of the lower limbs in the phlegm and stasis syndrome group，r=0.70，P<0.01，r=0.60，P<0.01. muscle tension of the upper limbs in the damp-heat syndrome group，r=0.64，P<0.01，r=0.53，P<0.01. muscle tension of the lower limbs in the damp-heat syndrome group，r=0.59，P<0.01，r=0.70，P<0.01. muscle tension of the upper limbs in the liver-kidney Yin deficiency syndrome group，r=0.70，P<0.01，r=0.74，P<0.01. muscle tension of the lower limbs in the liver-kidney Yin deficiency syndrome group，r=0.85，P<0.01，r=0.62，P<0.01）. Conlusion： The digital muscle function assessment system Myoton PRO can objectively evaluate the muscle tension level of patients with WD accompanied by abnormal muscle tension. This level has significant differences among different TCM syndromes and can evaluate the patient's condition to some extent.

This paper summarizes Professor WANG Xiuxia's clinical experience in treating hyperprolactinemia using the liver soothing therapy. Professor WANG identifies liver qi stagnation and rebellious chong qi （冲气） as the core pathomechanisms of hyperprolactinemia. Furthermore， liver qi stagnation may transform into fire or lead to pathological changes such as spleen deficiency with phlegm obstruction or kidney deficiency with essence depletion. The treatment strategy centers on soothing the liver， with a modified version of Qinggan Jieyu Decoction （清肝解郁汤） as the base formula. Depending on different syndrome patterns such as liver stagnation transforming into fire， liver stagnation with spleen deficiency， or liver stagnation with kidney deficiency， heat clearing， spleen strengthening， or kidney tonifying herbs are added accordingly. In addition， three paired herb combinations are commonly used for symptom specific treatment， Danggui （Angelica sinensis） with Chuanxiong （Ligusticum chuanxiong）， Zelan （Lycopus lucidus） with Yimucao （Leonurus japonicus） ， and Jiegeng （Platycodon grandiflorus） with Zisu （Perilla frutescens）.

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.