Objective:To explore influencing factors of the self-reported brief life quality satisfaction score(Brief-QoL) in patients with acromegaly and understand the persistent low Brief-QoL scores in cases achieving biochemical remission.Methods:This study included 836 acromegaly patients who were hospitalized at Peking Union Medical College Hospital between January 2012 and December 2020. We retrospectively examined how clinical characteristics, biochemical parameters, comorbidities, and symptoms influenced Brief-QoL. Among patients who achieved biochemical remission, differences in clinical symptoms and comorbidities were analyzed between the high and low quality of life groups.Results:Patients with well-controlled biochemical indicators at the last follow-up had generally high Brief-QoL. However, patients with symptoms such as headaches (47.8% in the low-score group vs 14.9% in the high-score group, P<0.001) and joint pain (69.6% in the low-score group vs 19.0% in the high-score group, P<0.001) had low Brief-QoL despite biochemical remission. Receiving combined treatment(52.4% in the low-score group vs 27.5% in the high-score group, P=0.030) and having comorbid diabetes or hyperlipidemia were significant factors leading to decreased quality of life. Conclusion:Brief-QoL is suitable for follow-up of outpatient patients. Early identification of factors affecting quality of life and timely intervention can facilitate the realization of standardized management.

BACKGROUND:Increasing evidence suggests that N6-methyladenosine(m6A)regulators are closely associated with osteoarthritis and are considered to be a new direction in the prevention and treatment of osteoarthritis,but their specific mechanism of action is unknown. OBJECTIVE:To conduct a bioinformatics analysis of the osteoarthritis gene microarray dataset in order to explore the role of m6A in osteoarthritis and analyze the pathogenesis of osteoarthritis. METHODS:The m6A regulators associated with osteoarthritis and their expression were first extracted from the GSE1919 dataset in the GEO database using R software,and then the results were analyzed by gene difference analysis and GO and KEGG enrichment analyses.Subsequently,the results of protein-protein interaction network topology analysis and machine learning results were intersected to obtain the m6A Hub regulators,which were validated by in vitro cellular experiments. RESULTS AND CONCLUSION:A total of 16 osteoarthritis-related m6A regulators were extracted and 11 m6A differential regulators,including ZC3H13,YTHDC1,YTHDF3 and HNRNPC,were obtained by differential analysis.GO enrichment analysis showed that osteoarthritis-related m6A differential regulators played a role in the biological processes such as mRNA transport,RNA catabolism,and regulation of insulin-like growth factor receptor signaling pathway.(3)KEGG enrichment analysis showed that the differential regulators were mainly involved in the p53,interleukin-17 and AMPK signaling pathways.The combined protein-protein interaction network topology analysis and machine learning results obtained the m6A Hub regulator-YTHDC1.(5)The results of in vitro cellular experiments showed that there was a significant difference in the expression of m6A key regulator between the control and experimental groups(P<0.05).To conclude,YTHDC1 is closely related to the development of osteoarthritis,which is expected to be a molecular target of m6A for the treatment of osteoarthritis.

BACKGROUND:Cellular senescence is closely related to the development and progression of osteoarthritis,but the specific targets and regulatory mechanisms are not yet clear. OBJECTIVE:To mine key genes in cellular senescence-mediated osteoarthritis by integrating bioinformatics and machine learning approaches and validate them via experiments to explore the role of cellular senescence in osteoarthritis. METHODS:The osteoarthritis gene expression profiles obtained from the GEO database were intersected with cellular senescence-related genes obtained from the CellAge database and the expression of the intersected genes was extracted for differential analysis,followed by GO and KEGG analysis of the differential genes.The key osteoarthritis cellular senescence genes were then screened by protein-protein interaction network analysis and machine learning,and in vitro cellular experiments were performed.Finally,the expression of the key genes was detected by qPCR. RESULTS AND CONCLUSION:A total of 31 osteoarthritis cell senescence differential genes were identified.GO analysis showed that these genes were mainly involved in the biological processes,such as regulation of leukocyte differentiation,monocyte differentiation,regulation of T cell differentiation and exerted roles in DNA transcription factor binding,histone deacetylase binding,chromatin DNA binding,and chemokine binding.KEGG analysis showed that osteoarthritis cell senescence differential genes were mainly activated in the JAK/STAT signaling pathway,PI3K/Akt signaling pathway and FoxO signaling pathway.MYC,a key gene for osteoarthritis cellular senescence,was identified by protein-protein interaction network topology analysis and machine learning methods.The results of the in vitro cellular assay showed that the mRNA expression of MYC was significantly lower in the experimental group(osteoarthritis group)than the control group(normal group)(P＜0.05).To conclude,MYC can be a key gene in the senescence of osteoarthritic cells and may be a new target in the prevention and treatment of osteoarthritis by mediating immune response,inflammatory response and transcriptional regulation.

BACKGROUND:Hypoxia is strongly associated with the development and progression of osteoarthritic chondrocyte injury,but the specific targets and regulatory mechanisms are unclear. OBJECTIVE:A machine learning approach was used to identify KDEL(Lys-Asp-Glu-Leu)receptor 3(KDELR3)as a characteristic gene for osteoarthritis hypoxia and immune infiltration analysis,to provide new ideas and methods for the treatment of osteoarthritis. METHODS:The osteoarthritis-related datasets were downloaded from the GEO database and the GSEA website to obtain hypoxia-related genes.The osteoarthritis datasets were batch-corrected and immune infiltration analyzed using R language,and osteoarthritis hypoxia genes were extracted for differential analysis.Differentially expressed genes were analyzed for GO function and KEGG signaling pathway.Weighted correlation network analysis(WGCNA)and machine learning were also used to screen osteoarthritis hypoxia signature genes,and in vitro cellular experiments were performed to validate expression and correlate immune infiltration analysis using the datasets and qPCR. RESULTS AND CONCLUSION:(1)8492 osteoarthritis genes were obtained by batch correction and principal component analysis,mainly strongly associated with immune cells such as Macrophages M2 and Mast cells resting;200 hypoxia genes were also obtained,resulting in 41 osteoarthritis hypoxia differentially expressed genes.(2)GO analysis involved mainly biological processes such as response to nutrient levels and glucocorticoids;cellular components such as lysosomal lumen and Golgi lumen;and molecular functions such as 14-3-3 protein binding and DNA-binding transcriptional activator activity.(3)KEGG analysis of osteoarthritis hypoxia differentially expressed genes was associated with signaling pathways such as PI3K-Akt,FoxO,and microRNAs in cancer.(4)The characteristic gene KDELR3 was obtained after using WGCNA analysis and machine learning screening.(5)The gene expression of KDELR3 was found to be higher in the test group than in the control group in the synovium(P=0.014)but lower in the meniscus(P=0.024)after validation by gene microarray.(6)In vitro chondrocyte assay showed that the expression of KDELR3 was higher in cartilage than in the control group(P=0.005),while KDELR3 was closely associated with Macrophages M0(P=0.014)and T cells follicular helper(P=0.014).Using a machine learning approach,we confirmed that KDELR3 can be used as a hypoxic signature gene for osteoarthritis and may intervene in osteoarthritis pathogenesis by improving hypoxia,expecting to provide a new direction for better treatment of osteoarthritis.

BACKGROUND:Ferroptosis is strongly associated with the occurrence and progression of osteoarthritis,but the specific characteristic genes and regulatory mechanisms are not known. OBJECTIVE:To identify osteoarthritis ferroptosis signature genes and immune infiltration analysis using the WGCNA and various machine learning methods. METHODS:The osteoarthritis dataset was downloaded from the GEO database and ferroptosis-related genes were obtained from the FerrDb website.R language was used to batch correct the osteoarthritis dataset,extract osteoarthritis ferroptosis genes and perform differential analysis,analyze differentially expressed genes for GO function and KEGG signaling pathway.WGCNA analysis and machine learning(random forest,LASSO regression,and SVM-RFE analysis)were also used to screen osteoarthritis ferroptosis signature genes.The in vitro cell experiments were performed to divide chondrocytes into normal and osteoarthritis model groups.The dataset and qPCR were used to verify expression and correlate immune infiltration analysis. RESULTS AND CONCLUSION:(1)12 548 osteoarthritis genes were obtained by batch correction and PCA analysis,while 484 ferroptosis genes were obtained,resulting in 24 differentially expressed genes of osteoarthritis ferroptosis.(2)GO analysis mainly involved biological processes such as response to oxidative stress and response to organophosphorus,cellular components such as apical and apical plasma membranes,and molecular functions such as heme binding and tetrapyrrole binding.(3)KEGG analysis exhibited that differentially expressed genes of osteoarthritis ferroptosis were related to signaling pathways such as the interleukin 17 signaling pathway and tumor necrosis factor signaling pathway.(4)After using WGCNA analysis and machine learning screening,we obtained the characteristic gene KLF2.After validation by gene microarray,we found that the gene expression of KLF2 was higher in the test group than in the control group in the meniscus(P=0.000 14).(5)In vitro chondrocyte assay showed that type Ⅱ collagen and KLF2 expression was lower in the osteoarthritis group than in the control group in chondrocytes(P<0.05),while in osteoarthritis ferroptosis,mast cells activated was closely correlated with dendritic cells(r=0.99);KLF2 was closely correlated with natural killer cells(r=-1,P=0.017)and T cells follicular helper(r=-1,P=0.017).(6)The findings indicate that using WGCNA analysis and machine learning methods confirmed that KLF2 can be a characteristic gene for osteoarthritis ferroptosis and may improve osteoarthritis ferroptosis by interfering with KLF2.

Objective:To summarize the clinical characteristics of 4 cases of mixed pituitary adenomas involving growth hormone(GH), prolactin(PRL), and thyroid stimulating hormone(TSH), and explore the standardized management approaches.Methods:The clinical data of four GH/PRL/TSH mixed pituitary adenoma patients diagnosed by Peking Union Medical College Hospital were retrospectively analyzed, including clinical manifestations, biochemical parameters, radiographic characteristics, as well as treatment and prognosis. Then literature review was conducted.Results:Among the 4 patients, 3 were male, with onset ages ranging from 15 to 38 years. All patients presented with coarse facial features as initial symptom. Three patients had visual impairment or visual field defects. All 4 patients had significantly elevated levels of GH and insulin-like growth factor-Ⅰ(IGF-Ⅰ). GH was not inhibited by oral glucose tolerance test. PRL concentration was over 100 ng/mL. Triiodothyronine(T 3)and thyroxine(T 4)were also elevated, while TSH was not inhibited. All pituitary adenomas in four cases were macroadenomas or giant adenomas, all of which were invasive growth, and one case developed pituitary stroke. Except for one patient who did not receive treatment in our hospital due to medical expenses, the remaining three patients underwent a combined treatment of medication and transnasal transsphenoidal pituitary adenoma resection. Among them, one patient had relief of central hyperthyroidism and hyperprolactinemia, but GH/IGF-Ⅰ did not meet the remission criteria. The other two patients had persistent non-resolution of at least 2 hormone axes. Conclusions:Patients with GH/PRL/TSH mixed pituitary adenoma were mainly characterized by coarse facial features, GH/PRL/TSH hyperfunction, large adenoma volume, low biochemical remission after surgery combined with drug treatment, and poor clinical prognosis.

Objective:Cushing′s disease(CD) is caused by the pituitary adrenocorticotroph hormone(ACTH) secreting adenomas, leading to increased serum cortisol levels and various abnormal metabolic processes. Untreated CD is linked to high mortality, thus it is critical to elucidate its pathogenesis. This study aims to explore the pathogenesis of pituitary ACTH adenomas using whole-genome sequencing analysis.Methods:Fresh tumor tissues and peripheral blood samples were collected in 9 confirmed cases of pituitary ACTH adenomas who underwent surgery. Whole genome sequencing was then performed, followed by analysis and verification of single nucleotide mutations, copy number variation(CNV) and chromosome structure variations.Results:Somatic USP8 mutations(p.Ser718del, p. Ser718Pro, p. Pro720Arg, p. Pro720Gln) were found in 5 patients, with a rate of 55.6%; CNV of USP8 was detected in 1 patient; TP53(p.Cys135Tyr), NF1(p.Val1049Glufs*11) and KMT2C(c.3323+ 1G>A) mutations were identified in 1 patient harboring wild-type USP8. CNV analysis showed a loss of heterozygosity in multiple chromosomes in a wild-type USP8 patient. Structural variations were found in 2 with unknown significance. No germline gene mutations were detected in this study.Conclusion:Somatic USP8 mutations, increased copy number of USP8, variations of tumor-related genes such as TP53 and extensive somatic CNV all contribute to pathogenesis of CD. Chromosomal structure variations may suggest high-risk pituitary ACTH adenomas, and call for frequent follow-up and aggressive treatment.

Nonalcoholic fatty liver disease (NAFLD) and hyperhomocysteinemia (HHcy) both are major health problems worldwide, whose incidence are closely related with each other. We previously reported the mechanism of HHcy-caused hepatic steatosis, but the role of n-3 polyunsaturated fatty acid (n-3 PUFA) in HHcy-induced hepatic steatosis remains unclear. In this study, 6-week-old C57BL/6 male mice were given a high methionine diet (HMD, 2% methionine diet), and plasma homocysteine levels were measured by ELISA to confirm the establishment of an HHcy model. Meantime, mice were fed HMD with or without n-3 PUFA supplement for 8 weeks to determine the role and mechanism of n-3 PUFA in hepatic steatosis induced by HHcy. Results showed that n-3 PUFA significantly improved hepatic lipid deposition induced by HHcy. qRT-PCR analysis demonstrated that n-3 PUFA inhibited the upregulation of Cd36, a key enzyme of fatty acid uptake, caused by HHcy. Further, the inhibition of hepatic Cd36 expression was associated with the inactivation of aryl hydrocarbon receptor (Ahr) induced by n-3 PUFA. Of note, mass spectrometry revealed that hepatic content of lipoxin A
Animals ; Fatty Acids, Omega-3 ; Fatty Liver/drug therapy* ; Hyperhomocysteinemia/drug therapy* ; Liver ; Male ; Mice ; Mice, Inbred C57BL

Objective:To investigate the clinical features and pathological classification of patients with nonfunctional pituitary adenomas(NFPAs)in single medical center according to 2017 World Health Organization.Methods:The clinical and pathological characteristics of 166 patients with NFPAs diagnosed by neurosurgery in Peking Union Medical College Hospital from April 2019 to January 2020 were analyzed retrospectively.Results:In 166 patients, the ratio of male to female was almost equal(1.05∶1). Their average operation age was(49.9±12.3) years, which was significantly higher than that of functional pituitary tumor patients in the same period. Headache, visual acuity decline, and visual field defect were the most common causes for the first visit. All the maximum diameter of tumors was more than 10 mm, and 15 cases(9.0%)were giant tumors. 18 patients(10.8%)were recurrent cases. According to the results of immunohistochemistry for anterior pituitary hormones and transcriptional factors, the most common pathological type was gonadotroph adenomas(50.6%), followed by corticotroph adenomas(24.7%), plurihormonal pituitary adenomas(11.4%), PIT-1-positive adenomas(6.6%), and null cell adenomas(6.6%). Gonadotroph adenomas were more common in men(male∶female ratio=4.1∶1), while corticotroph adenomas occurred mainly in women(male∶female ratio=1∶12.7). The average age of patients with gonadotroph adenomas was the highest, while those of patients with PIT1-positive adenomas and rare combining IHC plurihormonal pituitary adenoma were significantly lower than that of the former. There were no significant differences in the mean diameters of tumors, the proportion of giant adenomas, and recurrent cases among different pathological types of tumors. However, the mean Ki-67 index of PIT-1-positive adenomas was significantly higher than those of other groups( P=0.001). Conclusion:Although the clinical manifestations of NFPAs were similar, their pathological classifications were different. Gonadotroph adenomas occurs mainly in male patients while corticotroph adenomas is more common in women. The prognosis may be different among various pathological types of NFPAs.

Objective:To analyze and determine heavy metal content in Paridis Rhizoma from different genus and localities,in order to provide a reference for selecting cultivation areas and establishing the quality standard of Paridis Rhizoma of heavy metals content. Method:Microwave digestion method combined with inductively coupled plasma atomic emission spectrometry method (ICP-AES) method were applied to determine the contents of 6 heavy metals,i.e. As,Cu,Hg,Cd,Pb and Cr in 39 samples of Paridis Rhizoma of different genus and localities in Yunnan Province. Cluster analysis,statistical analysis and principal component analysis (PCA) were used to compare the differences of heavy metals contents in different localities and species. Result:The contents of six heavy metals in Paridis Rhizoma met the ISO international standard of Heavy Metal Limit of Traditional Chinese Medicine-traditional Chinese Medicinal Materials. Under the limited value standard of Green Trade Standards of Importing Medicinal Plants and Preparations,the over-standard rate of heavy metal As was 15.4%,the excess rate of Cd was 5.1%,and the excess rate of Pb was 2.6%. The contents of Cu and Hg conformed to relevant requirements. Cluster analysis,statistical analysis and principal component analysis showed that for the same variety,differences in producing places had significant effects on heavy metal content,while differences in species had little effects. Conclusion:The results of this study indicated that the heavy metal content of Paris planted in and around Dali basically conformed to relevant standards. The differences of heavy metal content in Paris were mainly regional differences,which provided a theoretical basis for standardizing the cultivation of medicinal materials and formulating the limit standards of heavy metals for Paridis Rhizoma.