BACKGROUND:The pathogenesis of rheumatoid arthritis has not yet been fully clarified,and recent studies have shown that mitophagy is associated with rheumatoid arthritis,but the key mechanisms need to be explored in depth.OBJECTIVE:To identify and validate the core interaction genes of mitophagy in rheumatoid arthritis using multiple machine learning algorithms and to analyze its immunoregulatory process.METHODS:The rheumatoid arthritis transcriptome expression dataset GSE15573 was retrieved from the GEO database as an independent training set,with the GSE97779 and GSE55235 collections used as independent validation sets.The differentially expressed genes of rheumatoid arthritis were screened using the training set,and"WGCNA"analysis was also performed.Then we downloaded the mitophagy-related genes from the"MitoCarta3.0"database,and intersected them with the differentially expressed genes of rheumatoid arthritis and the genes in the"WGCNA"analysis module to obtain the rheumatoid arthritis-mitophagy-related genes,and then analyzed the related genes for functional enrichment to clarify the cellular pathways.Feature genes were initially identified using the"Random Forest"and"Lasso"algorithms.The overlapping genes from these two methods were further refined using the"GMM"algorithm to identify the core interaction genes between rheumatoid arthritis and mitophagy.A predictive model was then developed and validated using an external dataset.Finally,"CIBERSORT"was employed to analyze the proportions and interactions of immune cell subsets during immune infiltration,while"ssGSEA"was used to examine the associations between the rheumatoid arthritis-mitophagy core interaction genes and immune cell subsets."ssGSEA"was also utilized to analyze the"GO"and"KEGG"biological pathways of the core interaction genes.RESULTS AND CONCLUSION:(1)Totally 807 differentially expressed genes in rheumatoid arthritis were obtained by differential analysis,1 208 genes were selected from two feature modules by"WGCNA"analysis,1136 genes were sorted out from the MitoCarta 3.0 database,and 53 HUB genes were obtained from the intersection of the three genes as rheumatoid arthritis-mitophagy related genes.(2)The results of functional enrichment analysis of related genes showed that the cellular processes were mainly related to mitophagy,peroxisome metabolism,cellular senescence,and necroptosis.(3)The three machine learning algorithms identified four rheumatoid arthritis-mitophagy core interaction genes(DNAJA3,C12orf65,AKR7A2,and PDHB).The area under the curve of nomoscore was 0.989,and the area under the curve values of rheumatoid arthritis-mitophagy core interaction genes verified by the receiver operating characteristic curve of external patient samples were all greater than 0.7.(5)Immunoregulatory analysis showed that the mitophagy process in rheumatoid arthritis was closely associated with memory B cells,M0 macrophages,activated memory CD4 T cells,and resting memory CD4 T cells.(6)The biological pathway analysis revealed that the core interaction genes were strongly associated with 821"GO"pathways(|cor|＞0.8,P＜0.001)and 48"KEGG"pathways(|cor|＞0.8,P＜0.001).The key biological processes identified were related to mitochondrial DNA metabolic process,mitochondrial DNA repair,mitochondrial DNA replication,mitochondrial genome maintenance,positive regulation of mitochondrial depolarization,and positive regulation of mitochondrial outer membrane permeabilization involved in apoptotic signaling pathway.To conclude,DNAJA3,C12orf65,AKR7A2,and PDHB are the core interaction genes of the mitophagy process in rheumatoid arthritis,which play key roles in disease progression by participating in specific immune processes and have precise and predictive effects on the diagnosis of rheumatoid arthritis.

BACKGROUND:The pathogenesis of rheumatoid arthritis has not yet been fully clarified,and recent studies have shown that mitophagy is associated with rheumatoid arthritis,but the key mechanisms need to be explored in depth.OBJECTIVE:To identify and validate the core interaction genes of mitophagy in rheumatoid arthritis using multiple machine learning algorithms and to analyze its immunoregulatory process.METHODS:The rheumatoid arthritis transcriptome expression dataset GSE15573 was retrieved from the GEO database as an independent training set,with the GSE97779 and GSE55235 collections used as independent validation sets.The differentially expressed genes of rheumatoid arthritis were screened using the training set,and"WGCNA"analysis was also performed.Then we downloaded the mitophagy-related genes from the"MitoCarta3.0"database,and intersected them with the differentially expressed genes of rheumatoid arthritis and the genes in the"WGCNA"analysis module to obtain the rheumatoid arthritis-mitophagy-related genes,and then analyzed the related genes for functional enrichment to clarify the cellular pathways.Feature genes were initially identified using the"Random Forest"and"Lasso"algorithms.The overlapping genes from these two methods were further refined using the"GMM"algorithm to identify the core interaction genes between rheumatoid arthritis and mitophagy.A predictive model was then developed and validated using an external dataset.Finally,"CIBERSORT"was employed to analyze the proportions and interactions of immune cell subsets during immune infiltration,while"ssGSEA"was used to examine the associations between the rheumatoid arthritis-mitophagy core interaction genes and immune cell subsets."ssGSEA"was also utilized to analyze the"GO"and"KEGG"biological pathways of the core interaction genes.RESULTS AND CONCLUSION:(1)Totally 807 differentially expressed genes in rheumatoid arthritis were obtained by differential analysis,1 208 genes were selected from two feature modules by"WGCNA"analysis,1136 genes were sorted out from the MitoCarta 3.0 database,and 53 HUB genes were obtained from the intersection of the three genes as rheumatoid arthritis-mitophagy related genes.(2)The results of functional enrichment analysis of related genes showed that the cellular processes were mainly related to mitophagy,peroxisome metabolism,cellular senescence,and necroptosis.(3)The three machine learning algorithms identified four rheumatoid arthritis-mitophagy core interaction genes(DNAJA3,C12orf65,AKR7A2,and PDHB).The area under the curve of nomoscore was 0.989,and the area under the curve values of rheumatoid arthritis-mitophagy core interaction genes verified by the receiver operating characteristic curve of external patient samples were all greater than 0.7.(5)Immunoregulatory analysis showed that the mitophagy process in rheumatoid arthritis was closely associated with memory B cells,M0 macrophages,activated memory CD4 T cells,and resting memory CD4 T cells.(6)The biological pathway analysis revealed that the core interaction genes were strongly associated with 821"GO"pathways(|cor|＞0.8,P＜0.001)and 48"KEGG"pathways(|cor|＞0.8,P＜0.001).The key biological processes identified were related to mitochondrial DNA metabolic process,mitochondrial DNA repair,mitochondrial DNA replication,mitochondrial genome maintenance,positive regulation of mitochondrial depolarization,and positive regulation of mitochondrial outer membrane permeabilization involved in apoptotic signaling pathway.To conclude,DNAJA3,C12orf65,AKR7A2,and PDHB are the core interaction genes of the mitophagy process in rheumatoid arthritis,which play key roles in disease progression by participating in specific immune processes and have precise and predictive effects on the diagnosis of rheumatoid arthritis.

AIM: To explore retinal microvascular changes in migraine patients using meta-analysis.METHODS: The National Library of Medicine PubMed, Embase, and Cochrane Library were searched to find relevant studies, and the search period was from the creation of database to June 2023. Two investigators independently screened the literatures, extracted data, and evaluated the quality of included studies using the NOS scale. STATA15.0 was used for Meta-analysis and publication bias evaluation, sensitivity analysis was performed for results with large heterogeneity, and the funnel plot and Egger were used to assess the publication bias of the literature.RESULTS:A total of 12 studies, including 217 patients(252 eyes)with migraine with aura(MA), 283 patients(388 eyes)with migraine without aura(MO), and 374 healthy individuals(479 eyes), were included in this Meta-analysis. Several optical coherence tomography angiography(OCTA)indicators, including foveal avascular zone(FAZ)macular or optic disc perfusion density were compared and analyzed. The Meta-analysis results showed that compared with healthy controls, patients with MA had a significant increase in FAZ area and perimeter, a significant decrease in perfusion density of the macular deep capillary plexus(mDCP)except for the fovea, and a significant decrease in perfusion density of the radial peripapillary capillaries(RPC)around the optic disc; the FAZ parameters were significantly increased in MO, while the differences in perfusion density of the macular superficial capillary plexus(mSCP), mDCP and RPC were not statistically significant, except for the perfusion density in the parafovea mDCP.CONCLUSIONS: Both MA and MO patients had an enlarged FAZ area, patients with MA had a significant decrease in mDCP perfusion density, and migraine patients had some degree of retinal ischemia.

AIM:To systematically evaluate the changes in retinal and choroidal thickness in patients with internal carotid artery stenosis by using optical coherence tomography(OCT)through Meta-analysis.METHODS: Literatures on the measurement of retinal and choroidal structure in patients with internal carotid artery stenosis by using OCT from CNKI, VIP, WF, PubMed, the Cochrane Library, SinoMed, and Embase databases were searched for relevant studies. The retrieval time was from the establishment of the databases to January 2024. In addition, quality of the included literatures was assessed by the Newtle-Ottawa scale(NOS), and RevMan 5.4.1 and Stata 16.0 were used for statistical analysis.RESULTS: A total of 17 articles(including 18 studies)were included, and the Meta-analysis results showed that, patients with internal carotid artery stenosis had significantly thinner peripapillary retinal nerve fiber layer(pRNFL), ganglion cell complex(GCC), center macular thickness(CMT), and subfoveal choroidal thickness(SFCT)than the healthy control group(age matched normal population). The pRNFL and SFCT of the ipsilateral eye in patients with internal carotid artery stenosis become thinner compared with the contralateral eye.CONCLUSION:To a certain extent, the morphological structure of the retina and choroid can be altered by stenosis of the internal carotid artery. OCT can non-invasively detect the microstructural changes of the retina and choroid in patients with internal carotid artery stenosis, and can be used for the evaluation of internal carotid artery stenosis.

In the early stage of diabetes retinopathy(DR),the change in the molecular level is often earlier than chan-ges in retinal microvessels.Under the chronic high-glucose environment,oxidative stress,epigenetic changes and other mechanisms cause retinal mitochondrial DNA(mtDNA)damage,affect the transcription process of mtDNA coding genes,and damage the electronic transport chain,leading to a vicious cycle of free radicals,which accelerates the apoptosis of retinal capillary pericytes and endothelial cells,leads to retinal microcirculation dysfunction,and cause DR.This paper will review the epigenetic changes,oxidative stress,damage to replication and repair system,gene mutation and other aspects,in order to elaborate on the research progress of retinal mtDNA damage in the pathogenesis of DR.

Objective : To explore the independent risk factors affecting the prognosis，and to construct a nomogram model predicting overall of patients with rectal cancer at T1 and T2 stage． Methods : Retrospective analysis was made on the data of 353 patients diagnosed as rectal cancer，who received the radical rectal resection．The collect- ed data were as follows : age，body mass index (BMI) ，carcinoembryonic antigen ( CEA) ，tumor size，histological type，T stage，N stage，tumor location and number of lymph nodes detected，which were used to perform Kaplan- Meier curve and Log-rank test for univariate analysis and Cox regression for multivariate analysis．The nomogram model was established to predict the overall survival of patients. Results : Age≥60 years，Mucinous adenocarcino- ma，poorly differentiation ，T2 stage ，lymph node metastasis ，BMI ≥25 kg / m2 ，CEA ≥5 μg / L and number of lymph nodes detected ＜12 were associated with overall survival of patients with rectal cancer at T1 and T2 stage (all P＜0. 05) ．Cox regression showed that age≥60 years，T2 stage，mucinous adenocarcinoma，lymph node me- tastasis，CEA≥5 μg / L，BMI ≥25 kg / m2 and lymph node detection number ＜12 were independent risk factors. Based on the above independent risk factors，the nomogram model was constructed，and the predicted curve was in good agreement with the actual survival curve ( C-index = 0. 779) ． Conclusion Age≥60 years，T2 stage，mucin- ous adenocarcinoma，lymph node metastasis，CEA≥5 μg / L，BMI≥25 kg / m2 and the number of lymph nodes de- tected ＜12 are independent risk factors ，and the nomogram established in this study can effectively predict the prognosis of patients with rectal cancer at T1 and T2 stage.

Objective : To investigate the effect of ginsenoside Rg1 (GRg1) on human retinal microvascular endothelial cells (HRMECs) glycolysis by regulating pyruvate kinase M2 ( PKM2) expression. Methods : HRMECs were cultured in vitro and divided into normal control (NC) group, high glucose (HG) group, high glucose + ginsenoside Rg1 (HG + GRg1) group, high glucose + ginsenoside Rg1 + low expression PKM2 ( HG + GRg1 + si-PKM2) group, and high glucose + ginsenoside Rg1 + overexpression PKM2 (HG + GRg1 + OE⁃PKM2) group. si-PKM2 and OE⁃PKM2 were transfected into HRMECs cells by cell transfection. The expression of PKM2 mRNA in HRMECs was detected by qRT⁃PCR. The expression levels of related proteins in HRMECs were detected by Western blot. The number of lumen formation in vitro was observed under an inverted microscope to quantify the angiogenesis ability. Cell culture medium of each group was collected, and glucose intake, lactate production and adenosine triphosphate(ATP)content were detected by glucose detection kit, lactate detection kit and ATP detection kit,re spectively. Results : HG induced HRMECs significantly increased the number of blood vessel formation, glycolysis and PKM2 expression, while GRg1 treatment significantly reduced the number of blood vessel formation, glycolysis and PKM2 expression; transfection of si⁃PKM2 assisted the inhibitory effect of GRg1 on glycolysis and angiogenesis while transfection of OE⁃PKM2 interfered with the function of GRg1 . Conclusion GRg1 inhibits angiogenesis by inhibiting PKM2 to reduce glycolysis of HRMECs.

Objective:To construct a systematic, standardized, scientific and effective evaluation index system for standardized training of newly recruited nurses.Methods:By the literature review, applying the Delphi method and purpose sampling to conduct two rounds of expert consultations to 17 nursing experts from 5 medical units and 1 nursing school from October 2019 to April 2020 to construct the evaluation index system for standardized training of newly recruited nurses.Results:The recovery rates of the two rounds of expert consultation questionnaires were all 100%, and the expert authority coefficient was 0.92. The final evaluation index system for standardized training of newly recruited nurses included 4 first-level indicators (professional literacy, theoretical knowledge, nursing operation skills, and core competency of the post) , 17 second-level indicators, and 52 third-level indicators.Conclusions:The evaluation index system for standardized training of newly recruited nurses established in this study is systematic, scientific and effective, which can provide a reference for standardized training and evaluation of newly recruited nurses, and provide a theoretical basis and practical guidance for improving the training effect and quality.

Objective:To explore the application value of contrast-enhanced ultrasound with SonoLiver software including quantitative analysis and dynamic vascular pattern (DVP) in the intraoperative diagnosis of glioma.Methods:SonoLiver software was used to analyze the contrast-enhanced ultrasound (CEUS) process of 252 cases with different grades of gliomas in General Hospital of Southern Theatre Command of PLA from 2006 to 2016. Among them, 144 were in the low-grade gliomas (LGG) group and 108 were in the high-grade gliomas (HGG) group. The quantitative parameters included maximum intensity (IMAX), time to peak (TTP) and mean transit time (mTT). The images of each CEUS were obtained, and the microvessel density (MVD) of corresponding pathology was compared, so as to analyze their correlations and characteristics.Results:There were significant differences in IMAX, TTP and mTT between the CEUS parameters of gliomas with different grades. IMAX in HGG group was significantly higher than that in LGG group( P<0.001), while TTP was shorter ( P=0.017) and mTT was longer( P=0.030). By correlation analysis between MVD and the CEUS parameters, MVD was positively correlated with IMAX ( r s=0.736, P<0.001) and mTT( r s=0.184, P=0.003), but negatively correlated with TTP( r s=-0.186, P=0.003). Compared with DVP images, the tumor areas of LGG group were mainly warm and black colors with small spots of cool-colored areas, and most of the surrounding areas were more obvious black areas. In HGG group, the tumor areas were mainly warm colors. Most of which were scattered in patchy cold colors areas, and the surrounding black areas were less ( P<0.05). There were significant differences in differentiating gliomas boundary before and after using DVP technique ( P<0.05). After using DVP, the boundary of glioma was clearer and more discernible. The discernibility of HGG group was up to 99%, and that of LGG group reached 97%. Conclusions:SonoLiver software can effectively and quantitatively analyze the CEUS parameters of gliomas with different grades, and its DVP images can directly reflect the contrast perfusion characteristics of gliomas, providing a new way to distinguish the boundary of gliomas and a new imaging method for the differential diagnosis of high and low grades of gliomas.

Objective To investigate the protective effect of dexamethasone on hearing loss induced by canalwall-down mastoidectomy.Methods A total of 76 patients (76 ears) were randomized to dexamethasone group and non dexamethasone group with 38 patients in each group.For dexamethasone group,gelfoam soaked with dexamethasone (5 mg/ml) was topically applied to the round window niche at the end of the surgery,and dexamethasone was administrated intravenously at the dosage of 5 mg/50 kg immediately after the surgery.While for non-dexamethasone group,dexamctbasone was not used.The pure-tone audiograms were performed before mastoidectomy and 90 days after the surgery.Absolute bearing change was defined as the difference in hearing thresholds in decibels before and after the surgery.Results The changes of bone conduction thresholds in dexamethasone group were 8.3± 3.9 dB at 6 kHz,11.3±5.2 dB at 8 kHz,and 10.1±7.2 dB for HPTA (4-6-8 kHz high tone average).As in non-dexamethasone group,the changes of bone conduction thresholds were 13.7±4.6 dB at 6 kHz,25.1±5.4 dB at 8 kHz,19.3±9.7 dB for HPTA.There were significant differences in the changes of bone conduction thresholds between dexamethasone and non dexamethasone groups at frequencies of 6 kHz (P=0.039),8 kHz (P=0.007) and HPTA (P=0.009).Conclusion The results demonstrated that application of dexamethasone significantly reduced sensorineural high frequencies (6 kHz and 8 kHz) hearing loss after canal-wall down mastoidectomy,thus the use of dexamethasone is recommended.