McCune-Albright syndrome(MAS) is a postzygotic somatic mutation disorder caused by activating mutations in the GNAS gene, which encodes the α subunit of the stimulatory G protein. Its clinical features typically include polyostotic fibrous dysplasia, cafe-au-lait skin pigmentation, and endocrine hyperactivity, such as Cushing′s syndrome, hyperthyroidism, and growth hormone excess. Here, we report two rare cases of MAS complicated with adrenocorticotropic hormone(ACTH)-independent Cushing syndrome, and provide a review and analysis of previously reported MAS cases associated with Cushing′s syndrome.

Objective:To apply artificial intelligence（AI）in classifying ovarian tumors on ultrasound images，and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures，i.e.，Alexnet，Densenet121，and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors，while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently，the benign and malignant results of the model's predictions were disclosed to each sonographer，and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941，sensitivity of 0.936，and specificity of 0.944 on the internal test dataset，and maintained robust performance on the external test dataset with accuracy of 0.891，sensitivity of 0.880，and specificity of 0.907. Compared to junior sonographers，the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors（0.880 vs. 0.723，0.602；all P<0.05）. No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1（ P=0.05）. With assistance from the optimal model，junior sonographers achieved significant improvements in both sensitivity and specificity（sensitivity：0.723 vs. 0.843，0.602 vs. 0.819；specificity：0.778 vs. 0.833，0.685 vs. 0.741；all P<0.05）. Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance，the diagnostic performance of junior sonographers is significantly improved.

McCune-Albright syndrome(MAS) is a postzygotic somatic mutation disorder caused by activating mutations in the GNAS gene, which encodes the α subunit of the stimulatory G protein. Its clinical features typically include polyostotic fibrous dysplasia, cafe-au-lait skin pigmentation, and endocrine hyperactivity, such as Cushing′s syndrome, hyperthyroidism, and growth hormone excess. Here, we report two rare cases of MAS complicated with adrenocorticotropic hormone(ACTH)-independent Cushing syndrome, and provide a review and analysis of previously reported MAS cases associated with Cushing′s syndrome.

Objective:To apply artificial intelligence（AI）in classifying ovarian tumors on ultrasound images，and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures，i.e.，Alexnet，Densenet121，and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors，while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently，the benign and malignant results of the model's predictions were disclosed to each sonographer，and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941，sensitivity of 0.936，and specificity of 0.944 on the internal test dataset，and maintained robust performance on the external test dataset with accuracy of 0.891，sensitivity of 0.880，and specificity of 0.907. Compared to junior sonographers，the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors（0.880 vs. 0.723，0.602；all P<0.05）. No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1（ P=0.05）. With assistance from the optimal model，junior sonographers achieved significant improvements in both sensitivity and specificity（sensitivity：0.723 vs. 0.843，0.602 vs. 0.819；specificity：0.778 vs. 0.833，0.685 vs. 0.741；all P<0.05）. Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance，the diagnostic performance of junior sonographers is significantly improved.

Objective:To study the molecular mechanism of functional defect of protein C (PC) caused by point mutations of human protein C gene (PROC) N355S,G392E and T314A. Methods:The wild-type and mutant plasmids (PCWT,PCN355S,PCG392E,PCT314A) of PROC gene were constructed and transiently transfected into HEK293 cells. The expression of mutant proteins in vitro were tested. The mRNA level changes of wild-type and mutant PC after 24 h of transfection were detected by real-time PCR. Western blot and ELISA were used to detect the changes of intracellular and extracellular protein levels of wild-type and mutant PC. The supernatant of cells transfected for 24-48 h was concentrated by ultrafiltration. The protein in the concentrated solution was quantified,and PC activation and enzyme kinetics tests were performed. Clustal Omega multiple sequence alignment was used to analyze the conservation of amino acid mutation sites. The effect of mutation on PC protein structure was analyzed by PyMOL software. Results:The relative expression abundances of PROC mRNA in PCN355S,PCG392E and PCT314A groups were 1.14±0.46,0.96±0.08 and 1.08±0.17,respectively,and there were no significant differences compared with 1.02±0.24 in PCWT group (P>0.05). Western blot analysis of the lysates of transfected cells showed that the content of PCT314A recombinant protein slightly decreased and the band became relatively lighter. The ELISA results of the concentrated cell culture supernatants showed that the PC:Ag levels of PCN355S and PCG392E were 98.8％±2.4％ and 101.4％±3.1％,respectively,with no significant differences compared with PCWT,while PCT314A decreased compared with PCWT (PC:Ag:88.6％±3.2％) (P<0.05). The results of enzyme kinetics test showed that APCN355S (Km=338.3±43.2,Vmax=2.015±0.12),APCG392E (Km=292.2±28.4,Vmax=1.893±0.07) and APCT314A (Km=299.5±24.6,Vmax=1.775±0.06) showed an increase in Km and a decrease in Vmax compared with APCWT (Km=238.2±4.58,Vmax=3.205±0.06). Multiple sequence alignment suggested that the three mutations be highly conservative in different species. The structural model suggested that the amino acid substitutions of N355S,G392E and T314A mutations collide with the surrounding amino acid groups,causing distortion of the surrounding structure,which may have adverse effects on the folding and biological function of PC. Conclusion:The N355S,G392E and T314A mutations in the PROC gene cause functional defects in PC by weakening the binding between PC and substrate. These three mutations have caused serious spatial collisions in the protein structure,affecting the folding of PC and the reactivity of active sites.

Objective:To investigate long-term auditory changes and characteristics of Alport syndrome（AS） patients with different degrees of renal injury. Methods:Retrospectively analyzing clinical data of patients diagnosed AS from January 2007 to September 2022, including renal pathology, genetic detection and hearing examination. A long-term follow-up focusing on hearing and renal function was conducted. Results:This study included 70 AS patients, of which 33（25 males, 8 females, aged 3.4-27.8 years） were followed up, resulting in a loss rate of 52.9%.The follow-up period ranged from 1.1to 15.8 years, with 16 patients followed-up for over 10 years. During the follow-up, 10 patients presenting with hearing abnormalities at the time of diagnosis of AS had progressive hearing loss, and 3 patients with new hearing abnormalities were followed up, which appeared at 5-6 years of disease course. All of which were sensorineural deafness. While only 3 patients with hearing abnormalities among 13 patients received hearing aid intervention. Of these patients,7 developed end-stage renal disease（ESRD）, predominantly males （6/7）. The rate of long-term hearing loss was significantly different between ESRD group and non-ESRD group（P=0.013）. There was no correlation between the progression of renal disease and long-term hearing level（P>0.05）. kidney biopsies from 28 patients revealed varying degrees of podocyte lesion and uneven thickness of basement membrane. The severity of podocyte lesion was correlated with the rate of long-term hearing loss（P=0.048）, and there was no correlation with the severity of hearing loss（P>0.05）. Among 11 cases, theCOL4A5mutationwas most common （8 out of 11）, but there was no significant correlation between the mutation type and hearing phenotype（P>0.05）. Conclusion:AS patients exhibit progressive hearing loss with significant heterogeneity over the long-term.. THearing loss is more likely to occur 5-6 years into the disease course. Hearing abnormalities are closely related to renal disease status, kidney tissue pathology, and gene mutations, emphasizing the need for vigilant long-term hearing follow-up and early intervention.
Male ; Child ; Female ; Humans ; Nephritis, Hereditary/pathology* ; Retrospective Studies ; Kidney ; Deafness ; Hearing Loss/genetics* ; Kidney Failure, Chronic/pathology* ; Mutation

Adequate inflammation can effectively eliminate harmful substances and prevent disease as a self-protective measure to prevent further damage to the body,while abnormally activated inflammation is detrimental to the body.Nucleotide binding and oligomerization domain-like receptor protein 3(NLRP3)inflammasome that participates in inflammatory responses are closely related to many physiological and pathological processes and play an important role in the occurrence and development of pulmonary diseases.This article mainly reviewed the activation mechanism and hypothesis of NLRP3 inflammasome,as well as the research on treating respiratory diseases by interfering with NLRP3 inflammasome.

OBJECTIVE: To develop monoclonal antibodies that can specifically recognize human von Willebrand factor (VWF) propeptide (VWFpp) in plasma, and establish a rapid and reliable method for the detection of VWFpp antigen in plasma by using the double-antibody sandwich ELISA with the obtained anti-VWFpp monoclonal antibody. METHODS: The recombinant human VWFpp (D1 and D2 regions) protein expressed in eukaryotic cells was used as immunogen to immunize BALB/c mice with routine method, so as to obtain clones of fusion cells. After screening and identification, hybridoma cell lines secreting monoclonal antibodies against VWFpp were selected, and then double-antibody sandwich ELISA assay was used to construct VWFpp antigen detection kit for the determination of VWFpp in human plasma. The levels of VWFpp antigen in plasma of 12 leukemia patients who underwent bone marrow transplantation were dynamically detected. RESULTS: Two hybridoma cell lines that can be subcultured continuously and secrete monoclonal antibodies against VWFpp were obtained and named SZ175 and SZ176 respectively. Identified by ELISA and Western blot, the antibodies could both specifically recognize VWFpp but couldn't recognize mature VWF (without propeptide). Based on the principle of double-antibody sandwich ELISA, monoclonal antibodies SZ175 and SZ176 were successfully made into a kit for detecting VWFpp antigen. The plasma VWFpp levels of leukemia patients before and after bone marrow transplantation were dynamically detected. The results showed that the plasma VWFpp levels of the patients after transplantation were significantly higher than those before transplantation. CONCLUSION Two monoclonal antibodies against VWFpp were successfully prepared, and a double-antibody sandwich ELISA detection kit for VWFpp antigen was constructed, which provides a powerful tool for further study on the biological function of VWFpp, the clinical diagnosis and classification of von Willebrand disease (VWD), and the prognostic monitoring of endothelial injury-related diseases.
Animals ; Mice ; Humans ; von Willebrand Factor ; Antibodies, Monoclonal ; Protein Precursors/metabolism* ; von Willebrand Diseases/diagnosis* ; Prognosis

Humans ; Lymphoma, Follicular/pathology* ; Lymphoma, T-Cell, Peripheral

ObjectiveTo predict the potential targets and mechanism of Jingfang mixture in the treatment of H1N1 influenza and provide references for clinical application of Jingfang mixture. MethodThe active components and targets of Jingfang mixture against H1N1 influenza were screened out by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform（TCMSP），SwissTargetPrediction， and TargetNet. The targets of H1N1 influenza were obtained from GeneCards，Online Mendelian Inheritance in Man （OMIM）， and DisGeNET and standardized by UniProt KB. The intersection targets were obtained by Venny 2.1.0. The "drug-component-target" network was constructed with Cytoscape 3.2.1 and analyzed for the topological attributes. The intersection targets were uploaded to STRING 11.5 to obtain the protein-protein interaction （PPI） network. Gene Ontology （GO） enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） analysis were carried out by Metascape. Finally，the top active components ranked by degree were docked to the core targets by Autodock vina and visually analyzed by PyMOL. Balb/c female rats were used for experimental verification. Hematoxylin-eosin（HE） staining was used to observe the pathological changes in lung tissues. Enzyme-linked immunosorbent assay（ELISA）was used to detect the levels of tumor necrosis factor-α（TNF-α），interleukin-10（IL-10）， and interleukin-17（IL-17）. Real-time fluorescence-based quantitative polymerase chain reaction（Real-time PCR） and Western blot were used to detect the mRNA and protein expression levels in lung tissues. ResultThere were 144 active components in Jingfang mixture. A total of 421 target genes of Jingfang mixture and 2 956 targets of H1N1 influenza were identified，including 199 common targets. Topological analysis showed that the core components of Jingfang mixture against H1N1 influenza included quercetin，luteolin， and kaempferol，and the core targets included prostaglandin-endoperoxide synthase 2（PTGS2），estrogen receptor alpha（ESR1），inducible nitric oxide synthase 2（iNOS2），peroxisome proliferator-activated receptorγ（PPARγ），and cyclooxygenase-1（PTGS1）. GO enrichment yielded 697 items in biological process （BP） （P<0.01）， 59 items in molecular function （MF）（P<0.01）， and 21 items in cellular component （CC） （P<0.01）. A total of 132 signaling pathways （P<0.01） were obtained by KEGG enrichment analysis， including phosphatidylinositol 3-kinases（PI3K）/protein kinase B（Akt） signaling pathway and mitogen-activated protein kinase（MAPK） signaling pathway，most of which were related to the regulation of immune inflammation. Molecular docking showed that the binding energy of the active components of Jingfang mixture to the core targets was less than -5.0 kcal·mol^-1，indicating good binding activity. HE staining showed that the lung tissues were significantly improved after drug intervention，and Real-time PCR and Western blot showed that Jingfang mixture could reduce the mRNA and protein expression of PI3K and Akt in lung tissues. ConclusionJingfang mixture can play an anti-viral effect against the influenza A virus through multiple components，multiple targets， and multiple pathways. The active components quercetin，luteolin， and kaempferol may control the inflammation and regulate immunity on the PI3K/Akt，MAPK， and other signaling pathways by acting on targets such as PTGS2，ESR1，iNOS2，PPARγ， and PTGS1.