Objective To investigate the impact of Toxoplasma gondii type I, II and III rhoptry protein 16 (ROP16) on programmed cell death ligand 1 (PD-L1) expression in lung adenocarcinoma cells, and to examine the effects of T. gondii type I ROP16 protein on the relative PD-L1 expression, the relative PD-L1 distribution on the cell membrane surface, and the binding of programmed cell death 1 (PD-1) to PD-L1 in lung adenocarcinoma cells. Methods Lentiviral vectors overexpressing T. gondii type I, II and III ROP16 proteins were generated, and transfected into the human lung adenocarcinoma A549 cell line. A549 cells were used as a blank control group, and A549 cells transfected with an empty lentiviral expression vector were used as a negative control group, while A549 cells transfected with lentiviral vectors overexpressing T. gondii type I, II and III ROP16 proteins served as experimental groups. Stably transfected cells were selected with puromycin and verified using Western blotting, quantitative real-time PCR (RT-qPCR), and immunofluorescence assays. The PD-L1 expression was quantified at translational and transcriptional levels using Western blotting and RT-qPCR assays in A549 cells in the five groups, and the relative PD-L1 distribution was detected on the A549 cell membrane surface using flow cytometry. In addition, the effect of T. gondii type I ROP16 protein on the PD-1/PD-L1 binding was measured in A549 cells using enzyme-linked immunosorbent assay (ELISA). Results The relative ROP16 protein expression was 0, 0, 1.546 ± 0.091, 1.822 ± 0.047 and 2.334 ± 0.089 in the blank control group, negative control group, and the T. gondii type I, II and III ROP16 protein overexpression groups (F = 1 339.00,P < 0.001), and the relative ROP16 mRNA expression was 2.153 ± 0.949, 2.436 ± 1.614, 14.343 ± 0.020, 12.577 ± 0.285 and 15.090 ± 0.420 in the blank control group, negative control group and the T. gondii type I, II and III ROP16 protein overexpression groups, respectively (F = 483.50,P < 0.001). The ROP16 expression was higher in the T. gondii type I, II and III ROP16 protein overexpression groups than in the blank control group at both translational and transcriptional levels (allP values < 0.001). Immunofluorescence assay revealed that T. gondii type I, II and III ROP16 proteins were predominantly localized in A549 cell nuclei. Western blotting showed that the relative PD-L1 protein expression was 0.685 ± 0.109, 0.589 ± 0.114, 1.007 ± 0.117, 0.572 ± 0.151, and 0.426 ± 0.116 in the blank control group, negative control group, and the T. gondii type I, II and III ROP16 protein overexpression groups (F = 9.46,P < 0.05), and RT-qPCR assay quantified that the relative PD-L1 mRNA expression was 1.012 ± 0.190, 1.281 ± 0.465, 1.950 ± 0.175, 0.889 ± 0.251, and 0.230 ± 0.192 in the blank control group, negative control group, and the T. gondii type I, II and III ROP16 protein overexpression groups (F = 14.18,P < 0.05). The PD-L1 expression was higher in the T. gondii type IROP16 protein overexpression group than in the blank control group at both translational and transcriptional levels (both P values < 0.05). Flow cytometry detected that the relative distributions of PD-L1 protein were (10.83 ± 0.60)%, (11.23 ± 0.20)%, and (14.61 ± 0.50)% on the A549 cell membrane surface (F = 28.31, P < 0.05), and the relative distribution of PD-L1 protein was higher in the T. gondii type IROP16 protein overexpression group than in the blank control group and negative control group (both P values < 0.001). ELISA measured significant differences in the absorbance (A) value among the T. gondii type IROP16 protein overexpression group, the blank control group and the negative control group if the concentrations of the recombinant PD-1 protein were 0.04 (F = 10.45, P < 0.05), 0.08 μg/mL (F = 11.68, P < 0.05) and 0.12 μg/mL (F = 52.68, P < 0.05), and the A value was higher in the T. gondii type IROP16 protein overexpression group than in the blank control group and the negative control group (both P values < 0.05), indicating that T. gondii type IROP16 protein promoted the PD-L1/PD-1 binding in A549 cells in a concentration-dose manner. Conclusions T. gondii type IROP16 protein overexpression may up-regulate PD-L1 expression in A549 cells at both transcriptional and translational levels and the relative PD-L1 distribution on the A549 cell membrane surface, and affect the PD-1/PD-L1 binding in a concentration-dependent manner.

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.

The pre-metabolic disease state is the body state of substance metabolism disorder that has not yet reached the physical and chemical indicators of the disease, and abnormal glucose metabolism is often the key link of metabolic disorder. In TCM, the healthy function of the spleen is the cornerstone of the production and distribution of fine substances. This article discussed the pre-metabolic disease state based on the theory of "overflow of Five Qi" in the Nei Jing, taking the loss of spleen preparedness as the starting point, in order to provide new ideas and directions for the prevention and treatment of clinical metabolic diseases.

Objective:To explore and validate the targets of Salvia miltiorrhiza in myopia using network pharmacology and molecular docking technology. Methods:The TCMSP database was used to extract the targets of Salvia miltiorrhiza.GeneCards, DisGeNET, Malacard and OMIM databases were used to extract the myopia-related targets.The target intersection was taken, and the intersecting targets were selected to extract the corresponding active ingredients of traditional Chinese medicine (TCM) and construct the pharmacological regulatory network of TCM using Cytoscape.The protein interaction network map for the key target genes was constructed using the String database, and the relevant proteins were selected to download the three-dimensional structures of the active ingredients from the PubChem database, and molecular docking was performed using AutoDockvina software.Twelve 3-week-old guinea pigs were induced with lens-induced myopia (LIM) in the right eye and randomly divided into normal saline group and sodium danshensu group, with 6 animals in each group.During the maintenance of LIM, periocular injection of 1 ml normal saline or sodium danshensu was performed daily.The contralateral eye was used as a negative control.On days 0, 14, and 28 of the experiment, the axial length of both eyes was measured by A-scan ultrasonography, and the refractive status was assessed with a streak retinoscope.To avoid individual differences, relative spherical equivalent (treated eye-contralateral eye) and relative axial length (treated eye-contralateral eye) were compared.On day 28, the relative expression levels of hypoxia-inducible factor-1α (HIF-1α) and transforming growth factor-β1 (TGF-β1) proteins were determined by Western blot.The feeding and use of laboratory animals followed the 3R principle, and the research program was approved by the Ethics Committee of Experimental Animal Center of Zhengzhou University (No.ZZU-LAC 202320405[02]). Results:Sixteen intersecting key targets were screened for myopia and TCM components derived from Salvia divinorum.A TCM network pharmacology map and protein interaction map were constructed with Salvia divinorum as a drug candidate, and the corresponding proteins of target genes, such as MMP2, TGFB1, and MMP9 were screened to perform molecular docking with the active ingredients, such as lignocellulosic acid, danshensu, tanshinone ⅡA, and so on.After 14 days of induction, the relative spherical equivalent and relative axial length were (-4.67±1.03)D and (0.67±0.26)mm in sodium danshensu group, and (-6.30±1.22)D and (1.08±0.34)mm normal saline group, indicating slower myopia progression and axial elongation in sodium danshensu group, and the differences were statistically significant ( t=2.412, P=0.039; t=2.750, P=0.049). The relative expression levels of HIF-1α protein were 0.20±0.01, 1.29±0.05 and 0.63±0.02, and the relative expression levels of TGF-β1 protein were 0.93±0.05, 0.25±0.01 and 0.74±0.05 in the negative control, normal saline and sodium danshensu groups, respectively.The expression of HIF-1α protein was higher in sodium danshensu group than in negative control group but lower than in the normal saline group, and the expression of TGF-β1 protein was lower in sodium danshensu group than in negative control group but higher than in the normal saline group, showing statistically significant differences (all at P<0.05). Conclusions:Natural compounds extracted from Salvia divinorum extracts may serve as potential drug candidates to combat scleral hypoxia and improve scleral extracellular matrix remodeling.

BACKGROUND:Previous studies on cervical instability failed to explain the dynamic and static interaction relationship and pathological characteristics changes in the development of cervical lesions under the traditional imaging examination.In recent years,the emerging nuclear magnetic resonance imaging(MRI)radiomics can provide a new way for in-depth research on cervical instability. OBJECTIVE:To investigate the application value of MRI radiomics in the study of cervical instability. METHODS:Through recruitment advertisements and the Second Department of Spine of Wangjing Hospital,China Academy of Chinese Medical Sciences,young cervical vertebra unstable subjects and non-unstable subjects aged 18-45 years were included in the cervical vertebra nuclear magnetic image collection.Five specific regions of interest,including the intervertebral disc region,the facet region,the prevertebral muscle region,the deep region of the posterior cervical muscle group,and the superficial region of the posterior cervical muscle group,were manually segmented to extract and screen the image features.Finally,the cervical instability diagnosis classification model was constructed,and the effectiveness of the model was evaluated using the area under the curve. RESULTS AND CONCLUSION:(1)A total of 56 subjects with cervical instability and 55 subjects with non-instability were included,and 1 688 imaging features were extracted for each region of interest.After screening,300 sets of specific image feature combinations were obtained,with 60 sets of regions of interest for each group.(2)Five regions of interest diagnostic classification models for cervical instability were initially established.Among them,the support vector machine model for the articular process region and the support vector machine model for the deep cervical muscle group had certain accuracy for the classification of instability and non-instability,and the average area under the curve of ten-fold cross-validation was 0.719 7 and 0.703 3,respectively.(3)The Logistic model in the intervertebral disc region,the LightGBM model in the prevertebral muscle region,and the Logistic model in the superficial posterior cervical muscle region were generally accurate in the classification of instability and non-instability,and the average area under the curve of ten-fold cross-validation was 0.650 4,0.620 7,and 0.644 2,respectively.(4)This study proved the feasibility of MRI radiomics in the study of cervical instability,further deepened the understanding of the pathogenesis of cervical instability,and also provided an objective basis for the accurate diagnosis of cervical instability.

This study was performed to screen the sequence of specific nanobody targeting SARS-CoV-2 S protein,and to express and purify recombinant anti-SARS-CoV-2 nanobodies,and evaluate their characteristics and application potential.Based on the previously constructed natural bacteriophage nanobody display library,the anti-SARS-CoV-2 S protein nanobody sequences were screened,with biotinylated SARS-CoV-2 S protein receptor-binding domain antigen as target,by biotin-streptavidin liquid phase screening method,phage-ELISA and sequencing.Recombinant anti-SARS-CoV-2 S protein nanobody expression vectors were constructed,the protein was induced by IPTG and then purified,and their characteristics and application potential were analyzed by SDS-PAGE,Westem blot and ELISA methods.Two anti-SARS-CoV-2 S protein nanobody sequences were successfully obtained,and the corresponding prokaryotic expression bacteria were constructed.The recombinant anti-SARS-CoV-2 S protein nanobody was expressed and purified successfully,which can specifically bind to SARS-CoV-2 S protein.In conclusion,the recombinant anti-SARS-CoV-2 S protein nanobodies have screened and expressed successfully,which provides a basis for its application in SARS-CoV-2 detection and treatment,and facilitates related researches.

Objective:To quantitatively evaluate the changes of choroidal biomarkers in patients with central serous chorioretinopathy (CSC) and preliminarily explore its pathogenesis.Methods:Clinical cross-sectional study. From July 2021 to December 2022, 74 eyes of 65 patients with CSC (CSC group) confirmed by ophthalmic examination at the First Affiliated Hospital of Zhengzhou University were included in the study. Among them, 46 patients (51 eyes) were male, 19 patients (23 eyes) were female. The duration from the onset of symptoms to the time of treatment was less than or equal to 3 months. A control group consisted of 40 healthy volunteers (74 eyes) matched in age and gender. Among them, 26 patients (50 eyes) were male, and 14 patients (24 eyes) were female. Using VG200D from Microimaging (Henan) Technology Co., Ltd., macular scanning source light coherence tomography angiography was performed, with scanning range 6 mm × 6 mm. According to the division of the diabetes retinopathy treatment research group, the choroid within 6 mm of the macular fovea was divided into three concentric circles centered on the macular fovea, namely, the central area with a diameter of 1 mm, the macular area with a diameter of 1-3 mm, and the surrounding area of the fovea with a diameter of 3-6 mm. The device comes with software to record the three-dimensional choroidal vascular index (CVI), choroidal vascular volume (CVV), perfusion area of the choroidal capillary layer (CFA), choroidal thickness (CT), and three-dimensional CVI, CVV, and CT in the upper, temporal, lower, and subnasal quadrants within 6 mm of the fovea. Quantitative data between the two groups were compared using an independent sample t-test. Qualitative data comparison line χ2 inspection. The value of receiver operating curve (ROC) analysis in predicting the occurrence of CSC, including CVI, CVV, CFA, and CT. Results:Compared with the control group, the CVI ( t=3.133, 4.814), CVV ( t=7.504, 9.248), and CT ( t=10.557, 10.760) in the central and macular regions of the affected eyes in the CSC group significantly increased, while the CFA ( t=-8.206, -5.065) significantly decreased, with statistically significant differences ( P<0.05); CVI ( t=7.129), CVV ( t=10.020), and CT ( t=10.488) significantly increased within 6 mm of the central fovea, while CFA ( t=-2.548) significantly decreased, with statistically significant differences ( P<0.05). The CVI ( t=4.980, 4.201, 4.716, 8.491), CVV ( t=9.014, 7.156, 7.719, 10.730), and CT ( t=10.077, 8.700, 8.960, 11.704) in the upper, temporal, lower, and lower nasal quadrants within 6 mm of the central fovea were significantly increased, with statistically significant differences ( P<0.05). In the CSC group, the maximum CVI and CVV were (0.39±0.10)% and (1.09±0.42) mm 3, respectively, on the nasal side of the affected eye. Upper CT was (476.02±100.89) μm. The nasal side CVI, CVV, and CT have the largest changes. The ROC curve analysis results showed that the area under the curve of CT, CVV, and CVI within 6 mm of the central region, macular region, and fovea was over than 0.5. Subcentral CT was the most specific for the diagnosis of CSC. Conclusion:Choroidal biomarkers CVI, CVV, and CT in CSC patients increase, while CFA decreases. Central CT is the most specific for the diagnosis of CSC.

ABSTARCT Purpose To investigate the clinicopathologic characteristics and genetic mutations of metastatic follicular thy-roid carcinoma(FTC).Methods A total of 22 cases of meta-static FTC were collected,including previous medical history,imaging,treatments and outcomes,and next-generation sequen-cing study and Sanger sequencing were performed in 12 cases.Results There were 16 women and 6 men.Sixteen cases were older than 50 years.Seven cases presented with metastases as the first symptom.Fourteen cases developed metastases 3 to 12 years after thyroid surgery.Sixteen cases developed bone metas-tasis,10 cases had lung metastasis,and 3 cases had brain me-tastasis.Those patients with multiple bone metastases progressed during the follow-up period.The common gene mutations in me-tastases were NRAS p.Q61R(6 cases),HRAS p.Q61R(2 ca-ses)and KRAS p.Q61R(1 case),followed by TERT promoter mutation(8 cases).Other mutated genes included KEL,BRCA1/2,ALK,ROS1,ErbB4,etc.Conclusion FTC has a high misdiagnosis rate.Those diagnosed with FTC should under-go regular systemic examinations to detect potential metastasis,especially in bone,lung,and brain.Further research on the sig-nificance of NRAS and other molecular indicators in FTC metas-tasis will help to better predict its biological behaviors.