ObjectiveTo explore quality difference factors of Perillae Caulis based on the contents of multiple chemical components and comprehensively evaluate the quality. MethodsA total of 32 batches of Perillae Caulis samples were collected from 12 producing areas such as Hebei， Anhui and Guangdong， and their diameter range， epidermis color and producing areas were recorded. Total flavonoids， total phenols， volatile oils， 5 active components and 84 volatile components in 32 batches of samples were quantitatively or semi-quantitatively determined by colorimetry， ultra performance liquid chromatography-photodiode array detector（UPLC-PDA） and gas chromatography-mass spectrometry（GC-MS）. Then the differences between the contents of these components were analyzed by principal component analysis（PCA） and non-parametric test. According to the weights of the index components determined by PCA model， entropy weight-technique for order preference by similarity to ideal solution（TOPSIS） model was constructed to evaluate the quality of Perillae Caulis with different characters and origins. ResultsThere were significant differences in the composition of Perillae Caulis with different diameters， epidermis colors and producing areas， and 9 differential components were screened out， including 6 index constituents（total flavonoids， total phenols， caffeic acid， scutellarin， rosmarinic acid and luteolin） and 3 volatile components（caryophyllene oxide， （-）-humulene epoxide Ⅱ， 14-hydroxycaryophyllene）， of which 6 index constituents were higher in samples with small diameter， purple-brown epidermis and southern origin， while the contents of 3 volatile components were higher in samples with large diameter， dark-brown epidermis and northern origin. A significant difference was shown in the model scores of different diameters， epidermis colors and origins（P<0.05）， and the scores of Perillae Caulis with small diameter and purple-brown epidermis from southern area， especially Guangdong， had a high score. ConclusionThere are significant differences in the composition and content of chemical constituents between different diameters， epidermal colors and production areas of Perillae Caulis， samples showing small diameter， owing purple-brown epidermis， and originating from Guangdong were of higher-quality due to their higher content of 8 key indices.

ObjectiveTo explore quality difference factors of Perillae Caulis based on the contents of multiple chemical components and comprehensively evaluate the quality. MethodsA total of 32 batches of Perillae Caulis samples were collected from 12 producing areas such as Hebei， Anhui and Guangdong， and their diameter range， epidermis color and producing areas were recorded. Total flavonoids， total phenols， volatile oils， 5 active components and 84 volatile components in 32 batches of samples were quantitatively or semi-quantitatively determined by colorimetry， ultra performance liquid chromatography-photodiode array detector（UPLC-PDA） and gas chromatography-mass spectrometry（GC-MS）. Then the differences between the contents of these components were analyzed by principal component analysis（PCA） and non-parametric test. According to the weights of the index components determined by PCA model， entropy weight-technique for order preference by similarity to ideal solution（TOPSIS） model was constructed to evaluate the quality of Perillae Caulis with different characters and origins. ResultsThere were significant differences in the composition of Perillae Caulis with different diameters， epidermis colors and producing areas， and 9 differential components were screened out， including 6 index constituents（total flavonoids， total phenols， caffeic acid， scutellarin， rosmarinic acid and luteolin） and 3 volatile components（caryophyllene oxide， （-）-humulene epoxide Ⅱ， 14-hydroxycaryophyllene）， of which 6 index constituents were higher in samples with small diameter， purple-brown epidermis and southern origin， while the contents of 3 volatile components were higher in samples with large diameter， dark-brown epidermis and northern origin. A significant difference was shown in the model scores of different diameters， epidermis colors and origins（P<0.05）， and the scores of Perillae Caulis with small diameter and purple-brown epidermis from southern area， especially Guangdong， had a high score. ConclusionThere are significant differences in the composition and content of chemical constituents between different diameters， epidermal colors and production areas of Perillae Caulis， samples showing small diameter， owing purple-brown epidermis， and originating from Guangdong were of higher-quality due to their higher content of 8 key indices.

Objective: To explore the laboratory testing methods and clinical management strategies for immune hemolytic anemia induced by Ceftizoxime sodium drug-dependent antibodies. Methods: Patient blood samples were subjected to blood typing, direct antiglobulin test, and unexpected antibody identification. Ceftizoxime sodium drug-dependent antibodies were detected using the immune complex method and drug-sensitized red cell method. The properties and titers of the drug antibodies were further assessed. Flow cytometry was used to assess the complement activation capacity of the drug antibodies in vitro. Results: Direct antiglobulin tests (IgG and C3d) were positive. Ceftizoxime sodium drug-dependent antibodies were identified using both the immune complex method and the sensitized red cell method, their titers significantly increased following the addition of the drug. Flow cytometry confirmed the complement activation capability of these antibodies and identified 30 minutes as the optimal time for activation in vitro. The patient's condition improved rapidly after drug withdrawal and supportive transfusion, resulting in a favorable outcome. Conclusion: Ceftizoxime sodium can cause drug-induced immune hemolytic anemia via complement activation mediated by drug-dependent antibodies. Serological testing is essential for diagnosing drug-induced hemolytic anemia. Clinicians should be vigilant for this adverse reaction. The offending drug must be promptly discontinued, and supportive care should be initiated upon the onset of symptoms.

Phase Ⅰ clinical trials play a crucial role in the research and development of new drugs, serving as the initial studies to assess their safety, tolerability, effectiveness, and pharmacokinetic properties in humans. These trials involve uncertainties regarding safety and efficacy. Comprehensive management of all aspects of phase Ⅰ clinical trials for anti-tumor drugs is crucial to protect the rights and safety of participants. This article provides an in-depth analysis of the key points and precautions necessary for effective quality control throughout the process. The analysis is informed by guidelines such as the “Good Clinical Practice for Drugs” “Key Points and Judgment Principles for Drug Registration Verification” “Key Points and Judgment Principles for Supervision and Inspection of Drug Clinical Trial Institutions” and the standard operating procedures for quality control of the center. Topics discussed include informed consent, inclusion criteria, experimental drugs, biological samples, adverse events, and serious adverse events. The goal is to standardize quality control in phase Ⅰ clinical trials of anti-tumor drugs, ensure the authenticity and reliability of clinical trial data, and protect the rights and safety of participants.

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.

Objective To investigate the potential categories of nutrition literacy in young and middle-aged patients with type 2 diabetes mellitus combined with overweight or obesity,and analyze the relationship between various latent categories and dietary motivation,so as to provide references for clinical working staff to develop relevant dietary intervention strategies.Methods A convenient sampling method was used to enroll 270 young and middle-aged patients with type 2 diabetes mellitus combined with overweight or obesity from the endocrine department of a tertiary general hospital in Zhenjiang City,Jiangsu province,using basic information questionnaire,Nutrition Literacy Measurement Scale for Chinese adults,and the Regulation of Eating Behaviors Scale to collect data,using latent profile analysis to extract nutrition literacy potential categories,with general data and potential categories as independent variables,dietary motivation as the dependent variable for univariate analysis and multiple linear regression analysis.Results A total of 262 young and middle-aged patients with type 2 diabetes mellitus combined with overweight or obesity completed the survey,and their nutrition literacy could be divided into 3 potential categories:low nutrition literacy group(16.41％),transformation dilemma group(54.96％),and middle and high nutrition literacy group(28.63％).The results of multiple linear regression analysis showed that residency style,potential categories of nutrition literacy and presence of diabetic complications were the influencing factors of dietary motivation in young and middle-aged patients with type 2 diabetes mellitus combined with overweight or obesity(P＜0.05).Conclusion There was a group heterogeneity in nutrition literacy in young and middle-aged patients with type 2 diabetes mellitus combined with overweight or obesity.Clinical working staff should provide targeted interventions based on the patient's potential categories of nutrition literacy to stimulate ongoing motivation to maintain a healthy diet.

Objective:To analyze the clinical characteristics of patients with pregnancy-related chronic pain visiting the pain clinic.Methods:The number of pregnant patients who completed a pregnancy registration at the Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University from 2022 to 2024 was collected. The medical records were reviewed to identify the patients who visited the department of pain of our hospital due to chronic pain related to pregnancy. The clinical characteristics such as the visiting situation, gestational weeks, age and types of pain were analyzed.Results:From 2022 to 2024, the total number of registered pregnant patients was 64, 818, of which, 2, 224 cases visited the pain clinic, and the annual proportions of pregnancy-related chronic pain visits were 2.540%, 3.836% and 3.889% respectively. Among the patients who attended the clinic, 77.97% were pregnant (5.82% in early pregnancy, 41.93% in mid-pregnancy, and 52.25% in late pregnancy), and 21.03% were postpartum patients. A total of 83.72% were aged 20-34 yr. The types of pain were pelvic girdle pain (40.96%), limb joint pain (28.82%), low back pain (14.16%), cervical spondylosis (3.64%), peripheral nerve entrapment syndrome (3.42%), headache (2.97%), chest and back pain (2.79%), pelvic and perineal pain (1.66%), neuralgia (0.94%) and other pains (0.63%).Conclusions:From 2022 to 2024, the proportion of registered pregnant women at our hospital who visited to the pain clinic due to pregnancy-related chronic pain increases year by year. The common types of pain are pelvic girdle pain, limb joint pain and low back pain.

OBJECTIVES: Osteoarthritis (OA) and sarcopenia are significant health concerns in the elderly, substantially impacting their daily activities and quality of life. However, the relationship between them remains poorly understood. This study aims to uncover common biomarkers and pathways associated with both OA and sarcopenia. METHODS: Gene expression profiles related to OA and sarcopenia were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between disease and control groups were identified using R software. Common DEGs were extracted via Venn diagram analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to identify biological processes and pathways associated with shared DEGs. Protein-protein interaction (PPI) networks were constructed, and candidate hub genes were ranked using the maximal clique centrality (MCC) algorithm. Further validation of hub gene expression was performed using 2 independent datasets. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive value of key genes for OA and sarcopenia. Mouse models of OA and sarcopenia were established. Hematoxylin-eosin and Safranin O/Fast Green staining were used to validate the OA model. The sarcopenia model was validated via rotarod testing and quadriceps muscle mass measurement. Real-time reverse transcription PCR (real-time RT-PCR) was employed to assess the mRNA expression levels of candidate key genes in both models. Gene set enrichment analysis (GSEA) was conducted to identify pathways associated with the selected shared key genes in both diseases. RESULTS: A total of 89 common DEGs were identified in the gene expression profiles of OA and sarcopenia, including 76 upregulated and 13 downregulated genes. These 89 DEGs were significantly enriched in protein digestion and absorption, the PI3K-Akt signaling pathway, and extracellular matrix-receptor interaction. PPI network analysis and MCC algorithm analysis of the 89 common DEGs identified the top 17 candidate hub genes. Based on the differential expression analysis of these 17 candidate hub genes in the validation datasets, AEBP1 and COL8A2 were ultimately selected as the common key genes for both diseases, both of which showed a significant upregulation trend in the disease groups (all P<0.05). The value of area under the curve (AUC) for AEBP1 and COL8A2 in the OA and sarcopenia datasets were all greater than 0.7, indicating that both genes have potential value in predicting OA and sarcopenia. Real-time RT-PCR results showed that the mRNA expression levels of AEBP1 and COL8A2 were significantly upregulated in the disease groups (all P<0.05), consistent with the results observed in the bioinformatics analysis. GSEA revealed that AEBP1 and COL8A2 were closely related to extracellular matrix-receptor interaction, ribosome, and oxidative phosphorylation in OA and sarcopenia. CONCLUSIONS AEBP1 and COL8A2 have the potential to serve as common biomarkers for OA and sarcopenia. The extracellular matrix-receptor interaction pathway may represent a potential target for the prevention and treatment of both OA and sarcopenia.
Sarcopenia/genetics* ; Osteoarthritis/genetics* ; Computational Biology/methods* ; Humans ; Protein Interaction Maps/genetics* ; Animals ; Mice ; Gene Expression Profiling ; Gene Ontology ; Transcriptome ; Male ; Signal Transduction/genetics* ; Gene Regulatory Networks