BACKGROUND:Mitophagy is closely associated with the development of idiopathic pulmonary fibrosis,but its mechanism remains unclear.OBJECTIVE:To investigate the biological mechanism of mitophagy in idiopathic pulmonary fibrosis and provide ideas for the risk prediction of idiopathic pulmonary fibrosis and subtype differentiation.METHODS:The mitophagy-related genes in idiopathic pulmonary fibrosis were obtained through GEO and Reactome Pathway databases.The mitophagy-related characteristic genes in idiopathic pulmonary fibrosis were screened based on intergroup differences and random forest model.GO functional enrichment analysis and KEGG,Reactome with WIKI pathway enrichment analyses were performed by g:Profiler database.Mitophagy subtypes in idiopathic pulmonary fibrosis were distinguished by consensus clustering method and immune infiltration analysis was performed.The mitophagy-related key gene was screened.Finally,the predictive value of mitophagy-related key gene for the risk of idiopathic pulmonary fibrosis was quantified by alignment diagram and the correlation between mitophagy-related key gene and clinical characteristics of idiopathic pulmonary fibrosis was explored.RESULTS AND CONCLUSION:(1)A total of 13 genes related to mitophagy in idiopathic pulmonary fibrosis were identified and 5 characteristic genes were screened,containing PINK1,RPS27A,SRC,HIF1A,and CDH6.(2)GO analysis was mainly involved in ubiquitin protein ligase binding,and cellular response to hypoxia.Pathway enrichment analysis was mainly involved in PINK1-PRKN mediated mitophagy,NOTCH signaling pathway,signaling by EGFR and angiogenesis.(3)HIF1A had significant expression differences between subtypes,which might serve as a key gene for the differentiation of mitophagy subtypes of idiopathic pulmonary fibrosis.(4)Immune infiltration analysis suggested that myeloid-derived suppressor cell,neutrophil and type 1 T helper cell might have infiltration differences between subtypes,while HIF1A was positively correlated with multiple immune cells.(5)Alignment diagram suggested that the risk of idiopathic pulmonary fibrosis might be predicted by the expression level of HIF1A.(6)Clinical characteristics analysis indicated patients with high expression of HIF1A might have poorer lung function and more severe fibrosis.It is concluded that PINK1,RPS27A,SRC,HIF1A,and CDH6 may influence the development of idiopathic pulmonary fibrosis through mitophagy,in which HIF1A may serve as a key gene for risk prediction with clinical subtype differentiation and HIF1A is strongly associated with the lung function of patients.

Objective To investigate the establishment and evaluation of an idiopathic pulmonary fibrosis(IPF)mouse model induced by the intratracheal infusion of bleomycin(BLM)of different concentrations.Methods Male C57BL/6J mice were randomly divided into a control group,Model-L group(1.5 mg/kg,BLM),Model-M group(2.5 mg/kg,BLM),and Model-H group(3.5 mg/kg,BLM).An IPF mouse model was constructed by one-time intratracheal infusion of BLM.The general status,body mass,survival rate,and lung coefficient of mice in different groups were compared.Pathological changes in lung tissue,the hydroxyproline content,fibrosis markers and inflammatory factor levels were observed.Results Compared with the control group,the survival rate decreased and body weight showed a downward trend in the low-,medium-,and high-dose model groups,with significant increases in lung coefficients.Inflammatory infiltration(P＜0.01)and collagen deposition(P＜0.0001)were observed in the lung tissues of all model groups.Hydroxyproline levels in lung tissue and serum were significantly elevated(P＜0.05).The mRNA levels of fibrosis markers α-Sma,Fn1,and Col1a1 were upregulated(P＜0.001),with significant increases in corresponding protein expression(P＜0.05).The mRNA expression of the inflammatory factor Tgfb1 also increased(P＜0.0001).Conclusion 1.5,2.5 and 3.5 mg/kg BLM can induce an IPF model in C57BL/6J mice.Based on the results observed for survival rate,body mass,lung coefficient changes,lung tissue gross and pathological changes,and fibrosis-related biomarkers,2.5 mg/kg BLM is the optimal concentration for inducing an IPF mouse model.

BACKGROUND:Mitophagy is closely associated with the development of idiopathic pulmonary fibrosis,but its mechanism remains unclear.OBJECTIVE:To investigate the biological mechanism of mitophagy in idiopathic pulmonary fibrosis and provide ideas for the risk prediction of idiopathic pulmonary fibrosis and subtype differentiation.METHODS:The mitophagy-related genes in idiopathic pulmonary fibrosis were obtained through GEO and Reactome Pathway databases.The mitophagy-related characteristic genes in idiopathic pulmonary fibrosis were screened based on intergroup differences and random forest model.GO functional enrichment analysis and KEGG,Reactome with WIKI pathway enrichment analyses were performed by g:Profiler database.Mitophagy subtypes in idiopathic pulmonary fibrosis were distinguished by consensus clustering method and immune infiltration analysis was performed.The mitophagy-related key gene was screened.Finally,the predictive value of mitophagy-related key gene for the risk of idiopathic pulmonary fibrosis was quantified by alignment diagram and the correlation between mitophagy-related key gene and clinical characteristics of idiopathic pulmonary fibrosis was explored.RESULTS AND CONCLUSION:(1)A total of 13 genes related to mitophagy in idiopathic pulmonary fibrosis were identified and 5 characteristic genes were screened,containing PINK1,RPS27A,SRC,HIF1A,and CDH6.(2)GO analysis was mainly involved in ubiquitin protein ligase binding,and cellular response to hypoxia.Pathway enrichment analysis was mainly involved in PINK1-PRKN mediated mitophagy,NOTCH signaling pathway,signaling by EGFR and angiogenesis.(3)HIF1A had significant expression differences between subtypes,which might serve as a key gene for the differentiation of mitophagy subtypes of idiopathic pulmonary fibrosis.(4)Immune infiltration analysis suggested that myeloid-derived suppressor cell,neutrophil and type 1 T helper cell might have infiltration differences between subtypes,while HIF1A was positively correlated with multiple immune cells.(5)Alignment diagram suggested that the risk of idiopathic pulmonary fibrosis might be predicted by the expression level of HIF1A.(6)Clinical characteristics analysis indicated patients with high expression of HIF1A might have poorer lung function and more severe fibrosis.It is concluded that PINK1,RPS27A,SRC,HIF1A,and CDH6 may influence the development of idiopathic pulmonary fibrosis through mitophagy,in which HIF1A may serve as a key gene for risk prediction with clinical subtype differentiation and HIF1A is strongly associated with the lung function of patients.

Objective To investigate the establishment and evaluation of an idiopathic pulmonary fibrosis(IPF)mouse model induced by the intratracheal infusion of bleomycin(BLM)of different concentrations.Methods Male C57BL/6J mice were randomly divided into a control group,Model-L group(1.5 mg/kg,BLM),Model-M group(2.5 mg/kg,BLM),and Model-H group(3.5 mg/kg,BLM).An IPF mouse model was constructed by one-time intratracheal infusion of BLM.The general status,body mass,survival rate,and lung coefficient of mice in different groups were compared.Pathological changes in lung tissue,the hydroxyproline content,fibrosis markers and inflammatory factor levels were observed.Results Compared with the control group,the survival rate decreased and body weight showed a downward trend in the low-,medium-,and high-dose model groups,with significant increases in lung coefficients.Inflammatory infiltration(P＜0.01)and collagen deposition(P＜0.0001)were observed in the lung tissues of all model groups.Hydroxyproline levels in lung tissue and serum were significantly elevated(P＜0.05).The mRNA levels of fibrosis markers α-Sma,Fn1,and Col1a1 were upregulated(P＜0.001),with significant increases in corresponding protein expression(P＜0.05).The mRNA expression of the inflammatory factor Tgfb1 also increased(P＜0.0001).Conclusion 1.5,2.5 and 3.5 mg/kg BLM can induce an IPF model in C57BL/6J mice.Based on the results observed for survival rate,body mass,lung coefficient changes,lung tissue gross and pathological changes,and fibrosis-related biomarkers,2.5 mg/kg BLM is the optimal concentration for inducing an IPF mouse model.

Objective:To monitor intra-fractional set-up errors in tumor radiotherapy using a real-time intelligent capture system for precision displacement.Methods:A simulated radiotherapy environment was created in both the laboratory and the treatment room. A three-axis ( xyz) displacement platform (LD60-LM) and dial gauges were used as displacement measurement tools. Moreover, a real-time intelligent capture system for precision displacement was developed for displacement monitoring. With 23 patients treated with radiotherapy enrolled in this study, the above system was employed to monitor their intra-fractional set-up errors in fractionated radiotherapy. Descriptive analyses were conducted on the deviations between the data captured by cameras and the actual displacement, obtaining the mean values and standard deviation. Results:The monitoring calibration data from the laboratory revealed displacement differences of ≤ 0.5 mm within 20 mm and a maximum displacement difference of 1.47 mm for 50 mm. In contrast, the calibration result from the treatment room exhibited deviations of ± 0.2 mm on the y- z axes, as displayed by both the left and right cameras, and ± 0.31 mm on the x- z axes, as displayed by the middle camera. During 37 radiotherapy sessions in 23 patients, the monitoring result from the middle camera revealed five deviations exceeding the threshold of 5 mm, with the maximum deviation duration and displacement of 57.2 s and 9.24 mm, respectively. Conclusions:The real-time intelligent capture system for precision displacement based on machine vision can achieve real-time monitoring of set-up errors during tumor radiotherapy. Nevertheless, further improvements and service testing are necessary for this system.

Objective:To compare the short-term efficacy and the safety of microwave ablation (MWA) and radiofrequency ablation (RFA) in the treatment of benign thyroid nodules (BTNs).Methods:This prospective randomized controlled trial, performed from December 2019 to September 2021, included 36 patients with solid or predominantly solid BTNs who met the eligibility criteria and provided written informed consent at the Nanjing sub-center (Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine). Patients were assigned to either the MWA group or the RFA group (18 patients in each group) at a ratio of 1∶1 using a block randomization design and allocation concealment using sealed envelope randomization. The independent-sample t-test and χ2 test were used to compare the volume reduction rates (VRRs), effective rates (VRRs≥50%), cosmetic scores, and complication rates at 1, 3, and 6 months after treatment between the two groups. Results:The clinical characteristics of the two groups of patients were comparable. After ablation, the nodule volume was significantly reduced in both groups. At 1, 3, and 6 months, there was no significant difference in the volume between the two groups (all P>0.05). At 3 months, the RFA group had a larger VRRs than that in the MWA group (62.08%±12.46% vs. 46.90%±23.16%, t=-2.45, P=0.021). However, at 1 and 6 months, no statistical significance was observed (both P>0.05). No significant difference was observed in the effective rates at the last follow-up (14/18 vs. 18/18, P=0.104). However, the RFA group had a lower cosmetic score than that in the MWA group (1.78±0.43 vs. 2.17±0.51, t=-2.47, P=0.019). There was no statistically significant difference in the complication rates between the two groups (all P>0.05). Conclusions:Both MWA and RFA were effective and safe treatments for BTNs, with no significant differences in short-term efficacy and safety. In addition, the RFA group showed slightly more favorable outcomes than the MWA group in terms of cosmetic improvement.

Objective The goals of this study were to identify early warning markers of severe dengue based on bioinformatics com-bined with machine learning,and explore the evaluation system of the risk of occurrence of severe dengue.Methods Based on the Gene Expression Omnibus database,the differentially expressed genes between dengue and severe dengue were analyzed,and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted.Early warning genes of severe dengue were screened using a random forest model,and the accuracy of the genes was verified using receiver operating characteristic(ROC)curves.Finally,nomograms were constructed to quantify the warning genes and predict the risk of progression from dengue to severe dengue based on the expression level of these genes.Results A total of 817 differentially expressed genes were identified,along with the associated biolo-gical processes that may be closely related to the occurrence and development of severe dengue,namely,antimicrobial humoral response,humoral immune response,serine hydrolase activity,and arachidonic acid metabolism.Based on this analysis,five early warning genes were isolated:AZU1,PDCD4,COL4A3BP,TRPM4,and ATP4A.Among these,ATP4A,COL4A3BP,and TRPM4 showed low expression levels,whereas AZU1and PDCD4were highly expressed.The ROC curves indicated that these genes were accurate pre-dictors of severe dengue.The nomograms indicated good predictive accuracy,clinical benefit rate,and clinical effectiveness of the model.Conclusion Measuring the expression levels of five warning genes(AZU1,PDCD4,COL4A3BP,TRPM4,and ATP4A)may help to evaluate the risk of severe dengue.

Pancytopenia is one of the serious complications of Graves disease, and its clinical treatment is quite challenging. Based on traditional Chinese medicine theory and combining with literature reports and clinical practice in China, we discuss the etiology, pathogenesis, and syndromes-based treatment of pancytopenia, hoping to open up new treatment approaches, guide clinical practice, and improve treatment effectiveness.

Objective:To develop an automated landmark location system applicable to the case of landmark missing.Methods:Four and eighty-one lateral cephalograms, which contained 240 males and 241 females, with an average age of (24.5±5.6) years, taken from January 2015 to January 2021 in the Department of Orthodontics, Capital Medical University School of Stomatology, and met the inclusion criteria were collected. Five postgraduate orthodontic students were the annotators to manually locate 61 possible landmarks in 481 lateral cephalograms. Two assistant professors in the department as reviewers performed calibration. Two professors as arbitrators, made final decision. Data sets were established (341 were used as training set, 40 as validation set, and 100 as test set). In this paper, an automatic landmarks identification and location model based on convolutional neural networks (CNN), CephaNET, was developed. The model was trained by feeding the original image into the feature extraction module and convolutional pose machine (CPM) module to locate landmarks with high accuracy using deep supervision. Training set was enhanced to 1 684 images by histogram equalization, cropping, and adjustment of brightness. The model was trained to compare the Gaussian heat maps output from the network with the set threshold to identify landmark missing cases. Test set of 100 lateral cephalograms was used to test the accuracy of the model. The evaluation criteria used were success detection rate of missing landmark, mean radial error (MRE) and success detection rate (SDR) in the range of 2.0, 2.5, 3.0, 3.5 and 4.0 mm.Results:The model identified and located 61 commonly used landmarks in 0.13 seconds on average. It had an average accuracy of 93.5% in identifying missing landmarks. The MRE of our testing set was (1.19±0.91) mm. SDR of 2.0, 2.5, 3.0, 3.5 and 4.0 mm were 85.4%, 90.2%, 93.5%, 95.4%, 97.0% respectively.Conclusions:The model proposed in this paper could adapt to the absence of landmark in lateral cephalograms and locate 61 commonly used landmarks with high accuracy to meet the requirements of different cephalometric analysis methods.

Objective:To evaluate the effect of short-term very low-calorie restriction(VLCR) on glycemic control in overweight/obese patients with type 2 diabetes, and to explore mechanisms through identifying markers of gut microbiota.Methods:This trial was conducted in 14 adult overweight/obese patients with type 2 diabetes. They received VLCR for 9 days in the hospital(calorie intake 300-600 kcal/d). Before and after VLCR, body weight(BW), waist circumference(WC), blood pressure(BP), and heart rate(HR) were measured, and body mass index(BMI) was calculated according to their height and weight. Fasting blood glucose(FBG), 2 h postprandial blood glucose(2hPBG), fasting insulin(FINS), triglycerides(TG), total cholesterol(TC), high-density lipoprotein-cholesterol(HDL-C), and low-density lipoprotein-cholesterol(LDL-C) were determined, and yielded the homeostasis model assessment for insulin resistance(HOMA-IR). Additional lab tests such as liver and kidney function and electrolytes were performed. The estimated glomerular filtration rate(eGFR) was calculated to evaluate renal function. All data were analyzed using the SPSS Sample Power software. Feces samples were collected before and after VLCR. Fecal samples were tested for microbial diversity using 16S rDNA technology. Professional software was used to analyze the differences of gut microbiota in feces before and after VLCR.Results:After 9 days of VLCR, BW, BMI, WC, BP, HR, FBG, 2hPBG, FINS, HOMA-IR, alkaline phosphatase, TG, and blood urea nitrogen of 14 overweight/obese patients with type 2 diabetes were significantly reduced( P<0.05). No effect was seen on serum alanine aminotransferase, aspartate amino transferase, gamma glutamyl transferase, TC, HDL-C, LDL-C, creatinine, eGFR, uric acid, albumin, calcium, and phosphorus( P>0.05). The gut microbiota diversity did not differ before and after VLCR. The abundance of Bacteroidetes increased significantly, and the Firmicutes/Bacteroidetes ratio decreased from 11.79 to 4.20. Between groups analysis showed the abundance of Parabacteroides distasonis increased significantly after VLCR. Conclusion:VLCR can improve body weight and glucose and lipid metabolism in overweight/obese patients with type 2 diabetes, with no serious adverse events. Parabacteroides distasonis may be a marker of VLCR.