Objective·To investigate the expression of protein tyrosine phosphatase receptor type N(PTPRN)in lung adenocarcinoma and its potential molecular mechanisms in promoting lung adenocarcinoma metastasis.Methods·A highly bone-metastatic A549-BM cell line was established through multiple rounds of intracardiac injection.RNA sequencing(RNA-seq),combined with Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses,was performed to identify PTPRN as a key metastasis-related gene.Subsequently,The Cancer Genome Atlas(TCGA)database was utilized to evaluate PTPRN expression in patients with lung adenocarcinoma and its correlation with clinical prognosis.Co-expression analysis based on TCGA data was conducted to identify and analyze key genes co-expressed with PTPRN.Small interfering RNA(siRNA)targeting PTPRN(siPTPRN)was transfected into A549-BM cells,and Transwell assays were performed to assess its effects on cell migration and invasion.Western blotting was used to detect the expression of epithelial-mesenchymal transition(EMT)-related proteins and the activation of the PI3K-AKT signaling pathway.siPTPRN-transfected A549-BM cells were injected into a mouse model via intracardiac injection,and in vivo metastasis was assessed.Additionally,multiple database analyses were integrated to predict BCL6 as an upstream transcription factor of PTPRN,and siBCL6 transfection experiments were performed to validate the regulatory effect of BCL6 on PTPRN expression.Results·RNA-seq and GO/KEGG enrichment analyses demonstrated that PTPRN was significantly upregulated in highly metastatic A549-BM cells and enriched in metastasis-associated pathways,including the PI3K-AKT signaling pathway and extracellular matrix(ECM)-receptor interactions.Analysis of the TCGA database further confirmed that PTPRN was highly expressed in lung adenocarcinoma patients and significantly associated with poor prognosis.Co-expression analysis based on TCGA data,combined with GO/KEGG enrichment analyses,revealed that PTPRN-associated genes were mainly enriched in biological processes such as neural signaling,endocrine regulation,cell communication,and ECM-receptor interactions.In vitro experiments demonstrated that siPTPRN transfection significantly inhibited the migration and invasion of A549-BM cells,accompanied by downregulation of EMT-related proteins and reduced activation of the PI3K-AKT signaling pathway.In vivo experiments further showed that PTPRN knockdown markedly suppressed the metastatic potential of A549-BM cells,confirming its pro-metastatic role.Additionally,siBCL6 transfection experiments demonstrated that BCL6 knockdown upregulated PTPRN expression.Conclusion·PTPRN is highly expressed in lung adenocarcinoma tissues and promotes tumor cell migration and metastasis by enhancing EMT and activating the PI3K-AKT signaling pathway.High PTPRN expression is significantly correlated with poor prognosis in lung adenocarcinoma patients,while PTPRN enhances lung adenocarcinoma cell invasiveness and metastatic potential.BCL6 may act as an upstream transcriptional regulator of PTPRN,influencing its expression levels.

Objective·To investigate the expression level of O-GlcNAc transferase(OGT)in non-small cell lung cancer(NSCLC)and its impact on lung cancer proliferation,as well as to explore the underlying mechanisms.Methods·The expression of OGT in NSCLC tumors and adjacent normal tissues was detected by immunohistochemistry(IHC).The dataset(GSE31210)from the GEO database was analyzed to assess the correlation between OGT expression and NSCLC patient prognosis.siRNA transfection was performed to knock down OGT expression in H460 and H1299 cells,followed by total RNA extraction and transcriptome sequencing.Pathway enrichment analysis was conducted on differentially downregulated genes in the knockdown group compared with the control group,and Western blotting was used to validate the enrichment results.The effects of OGT knockdown on cell proliferation and colony formation in H460 and H1299 cells were evaluated using the cell counting kit-8(CCK-8)assay and colony formation assay,respectively.The impact of overexpressing downstream genes was also examined.Stable OGT-knockdown cell lines were generated using shRNA and subcutaneously inoculated into nude mice to monitor tumor growth.Results·IHC revealed that OGT expression was significantly upregulated in NSCLC tumor tissues compared to adjacent normal tissues.Patients with high OGT expression exhibited shorter survival times and poorer prognoses than those with low expression.Transcriptome sequencing demonstrated that genes downregulated after OGT knockdown were primarily enriched in the mitogen-activated protein kinase(MAPK)signaling pathway.Western blotting showed that total extracellular regulated protein kinase 1/2(ERK1/2)levels remained unchanged in H460 and H1299 cells after OGT knockdown,while phosphorylated ERK1/2(p-ERK1/2)and its downstream proto-oncogene JUNB protein were markedly reduced.Suppression of OGT expression attenuated the proliferation rate and colony formation capacity of H460 and H1299 cells,whereas JUNB overexpression rescued the proliferation defects induced by OGT knockdown.Notably,H460 cells with stable OGT knockdown formed significantly smaller tumors in nude mice.Conclusion·OGT is highly expressed in NSCLC and correlates with poor prognosis.Knockdown of OGT inhibits NSCLC cell proliferation and clonogenicity in vitro,and tumor growth in vivo.Mechanistically,OGT appears to promote NSCLC progression by activating the ERK/JUNB signaling axis.

Objective·To investigate the expression of protein tyrosine phosphatase receptor type N(PTPRN)in lung adenocarcinoma and its potential molecular mechanisms in promoting lung adenocarcinoma metastasis.Methods·A highly bone-metastatic A549-BM cell line was established through multiple rounds of intracardiac injection.RNA sequencing(RNA-seq),combined with Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses,was performed to identify PTPRN as a key metastasis-related gene.Subsequently,The Cancer Genome Atlas(TCGA)database was utilized to evaluate PTPRN expression in patients with lung adenocarcinoma and its correlation with clinical prognosis.Co-expression analysis based on TCGA data was conducted to identify and analyze key genes co-expressed with PTPRN.Small interfering RNA(siRNA)targeting PTPRN(siPTPRN)was transfected into A549-BM cells,and Transwell assays were performed to assess its effects on cell migration and invasion.Western blotting was used to detect the expression of epithelial-mesenchymal transition(EMT)-related proteins and the activation of the PI3K-AKT signaling pathway.siPTPRN-transfected A549-BM cells were injected into a mouse model via intracardiac injection,and in vivo metastasis was assessed.Additionally,multiple database analyses were integrated to predict BCL6 as an upstream transcription factor of PTPRN,and siBCL6 transfection experiments were performed to validate the regulatory effect of BCL6 on PTPRN expression.Results·RNA-seq and GO/KEGG enrichment analyses demonstrated that PTPRN was significantly upregulated in highly metastatic A549-BM cells and enriched in metastasis-associated pathways,including the PI3K-AKT signaling pathway and extracellular matrix(ECM)-receptor interactions.Analysis of the TCGA database further confirmed that PTPRN was highly expressed in lung adenocarcinoma patients and significantly associated with poor prognosis.Co-expression analysis based on TCGA data,combined with GO/KEGG enrichment analyses,revealed that PTPRN-associated genes were mainly enriched in biological processes such as neural signaling,endocrine regulation,cell communication,and ECM-receptor interactions.In vitro experiments demonstrated that siPTPRN transfection significantly inhibited the migration and invasion of A549-BM cells,accompanied by downregulation of EMT-related proteins and reduced activation of the PI3K-AKT signaling pathway.In vivo experiments further showed that PTPRN knockdown markedly suppressed the metastatic potential of A549-BM cells,confirming its pro-metastatic role.Additionally,siBCL6 transfection experiments demonstrated that BCL6 knockdown upregulated PTPRN expression.Conclusion·PTPRN is highly expressed in lung adenocarcinoma tissues and promotes tumor cell migration and metastasis by enhancing EMT and activating the PI3K-AKT signaling pathway.High PTPRN expression is significantly correlated with poor prognosis in lung adenocarcinoma patients,while PTPRN enhances lung adenocarcinoma cell invasiveness and metastatic potential.BCL6 may act as an upstream transcriptional regulator of PTPRN,influencing its expression levels.

Objective·To investigate the expression level of O-GlcNAc transferase(OGT)in non-small cell lung cancer(NSCLC)and its impact on lung cancer proliferation,as well as to explore the underlying mechanisms.Methods·The expression of OGT in NSCLC tumors and adjacent normal tissues was detected by immunohistochemistry(IHC).The dataset(GSE31210)from the GEO database was analyzed to assess the correlation between OGT expression and NSCLC patient prognosis.siRNA transfection was performed to knock down OGT expression in H460 and H1299 cells,followed by total RNA extraction and transcriptome sequencing.Pathway enrichment analysis was conducted on differentially downregulated genes in the knockdown group compared with the control group,and Western blotting was used to validate the enrichment results.The effects of OGT knockdown on cell proliferation and colony formation in H460 and H1299 cells were evaluated using the cell counting kit-8(CCK-8)assay and colony formation assay,respectively.The impact of overexpressing downstream genes was also examined.Stable OGT-knockdown cell lines were generated using shRNA and subcutaneously inoculated into nude mice to monitor tumor growth.Results·IHC revealed that OGT expression was significantly upregulated in NSCLC tumor tissues compared to adjacent normal tissues.Patients with high OGT expression exhibited shorter survival times and poorer prognoses than those with low expression.Transcriptome sequencing demonstrated that genes downregulated after OGT knockdown were primarily enriched in the mitogen-activated protein kinase(MAPK)signaling pathway.Western blotting showed that total extracellular regulated protein kinase 1/2(ERK1/2)levels remained unchanged in H460 and H1299 cells after OGT knockdown,while phosphorylated ERK1/2(p-ERK1/2)and its downstream proto-oncogene JUNB protein were markedly reduced.Suppression of OGT expression attenuated the proliferation rate and colony formation capacity of H460 and H1299 cells,whereas JUNB overexpression rescued the proliferation defects induced by OGT knockdown.Notably,H460 cells with stable OGT knockdown formed significantly smaller tumors in nude mice.Conclusion·OGT is highly expressed in NSCLC and correlates with poor prognosis.Knockdown of OGT inhibits NSCLC cell proliferation and clonogenicity in vitro,and tumor growth in vivo.Mechanistically,OGT appears to promote NSCLC progression by activating the ERK/JUNB signaling axis.

Objective To explore the value of improved ResNet18 lightweight deep learning(DL)models for automatically detecting gouty arthritis(GA)based on ultrasonogram of the first metatarsophalangeal joint(MTP1).Methods A total of 2 401 ultrasonograms obtained from 260 patients with suspected gout who underwent MTP1 ultrasound examination were included and divided into training set(1 910 ultrasonograms from 209 cases)and test set(491 ultrasonograms from 51 cases)at the ratio of 4∶1.GA lesions on ultrasonograms were manually labeled.After preprocessing,ResNet18 lightweight network was used to construct DL models for identifying the ultrasonogram category was normal or abnormal(with any manifestation of GA).Five-fold cross-validation method was adopted to evaluate the efficacy of the DL models constructed with 2,3,4 or 6 residual blocks,i.e.model 1,2,3 and 4,respectively,and the computational cost and the amount of parameters of each model were recorded.The efficacy of the models were verified using test set,and the best DL model was screened.Results The computational cost of model 1,2,3 and 4 was 7 558.27,2 963.73,4 012.33 and 6 093.39 M,respectively,while the amount of parameters was 4.61,4.91,4.91 and 5.28 M,respectively.Model 2 had the least computational cost with parameters only slightly more than model 1.In test set,no significant difference of accuracy nor the area under the curve was found among 4 models(all P＞0.05).The sensitivity of model 2 was higher than that of model 3,while its specificity was lower only than that of model 3(both P＜0.05),hence model 2 was the best DL model.Conclusion Improved ResNet18 lightweight DL models could be used for automatically detecting GA based on ultrasonogram of MTP1,among which model 2 was the best one.

Objective To explore the value of improved ResNet18 lightweight deep learning(DL)models for automatically detecting gouty arthritis(GA)based on ultrasonogram of the first metatarsophalangeal joint(MTP1).Methods A total of 2 401 ultrasonograms obtained from 260 patients with suspected gout who underwent MTP1 ultrasound examination were included and divided into training set(1 910 ultrasonograms from 209 cases)and test set(491 ultrasonograms from 51 cases)at the ratio of 4∶1.GA lesions on ultrasonograms were manually labeled.After preprocessing,ResNet18 lightweight network was used to construct DL models for identifying the ultrasonogram category was normal or abnormal(with any manifestation of GA).Five-fold cross-validation method was adopted to evaluate the efficacy of the DL models constructed with 2,3,4 or 6 residual blocks,i.e.model 1,2,3 and 4,respectively,and the computational cost and the amount of parameters of each model were recorded.The efficacy of the models were verified using test set,and the best DL model was screened.Results The computational cost of model 1,2,3 and 4 was 7 558.27,2 963.73,4 012.33 and 6 093.39 M,respectively,while the amount of parameters was 4.61,4.91,4.91 and 5.28 M,respectively.Model 2 had the least computational cost with parameters only slightly more than model 1.In test set,no significant difference of accuracy nor the area under the curve was found among 4 models(all P＞0.05).The sensitivity of model 2 was higher than that of model 3,while its specificity was lower only than that of model 3(both P＜0.05),hence model 2 was the best DL model.Conclusion Improved ResNet18 lightweight DL models could be used for automatically detecting GA based on ultrasonogram of MTP1,among which model 2 was the best one.

Objective:To explore classification models for radiosensitive lipid metabolites in human peripheral blood by combining lipidomics with multiple machine learning (ML) algorithms.Methods:Totally 97 peripheral blood samples were collected from 25 leukemia cases admitted to a general hospital in Beijing from March to September 2023 who were ready to undergo bone marrow transplantation, including 0 Gy blood samples before irradiation in the control group ( n=24), and 73 blood samples after irradiation at doses of 4, 8 and 12 Gy in the radiation group ( n=73), and the targeted lipidomic based on the ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) platform method to analyze the differences of different lipids between control and radiation groups. Then, lipids responsive to radiation doses of 0-12 Gy were identified using linear regression. Finally, classification models were constructed using five ML algorithms based on the training set, followed by the validation and evaluation of these models using the validation set. Results:Compared with the control group, the differences in the concentration changes of 62 lipids in 9 classes of lipid metabolites sensitive to radiation group were statistically significant ( t=-4.91 to 4.74, P<0.05), including sphingomyelins(SMs), cholesteryl esters(CEs), ceramides(Cers), phosphatidylinositols(PIs), hexosylceramides(HexCers), lysophosphatidylcholines (LysoPCs), phosphatidylcholines (PCOs), phosphatidylethanolamines (PEs), and lysophosphatidylethanolamines (LysoPEs). Twenty lipids responsive to radiation doses of 0-12 Gy were identified, namely 11 SMs, 7 CEs, 1 Cer, and 1 PI. The five models based on ML algorithms of decision tree (DT), support vector machine (SVM), light gradient boosting machine (Light GBM), random forest (RF), and K-nearest neighbors (KNN) all exhibited high goodness of fit (F1=0.69-1.00) and high sensitivity. The evaluation and validation metrics revealed that the RF-based model yielded the optimal radiation classification discrimination (sensitivity: 1.00; accuracy: 0.72; F1 score: 0.80). Conclusions:Lipid metabolites responsive to radiation and lipids responsive to radiation dose in human samples were identified using targeted lipidomics. The RF-based model can provide new ideas for exploring models of human radiosensitive lipid metabolites.

Background::Hypothermia therapy has been suggested to attenuate myocardial necrosis; however, the clinical implementation as a valid therapeutic strategy has failed, and new approaches are needed to translate into clinical applications. This study aimed to assess the feasibility, safety, and efficacy of a novel selective intracoronary hypothermia (SICH) device in mitigating myocardial reperfusion injury.Methods::This study comprised two phases. The first phase of the SICH was performed in a normal porcine model for 30 minutes ( n = 5) to evaluate its feasibility. The second phase was conducted in a porcine myocardial infarction (MI) model of myocardial ischemia/reperfusion which was performed by balloon occlusion of the left anterior descending coronary artery for 60 minutes and maintained for 42 days. Pigs in the hypothermia group ( n = 8) received hypothermia intervention onset reperfusion for 30 minutes and controls ( n = 8) received no intervention. All animals were followed for 42 days. Cardiac magnetic resonance analysis (five and 42 days post-MI) and a series of biomarkers/histological studies were performed. Results::The average time to lower temperatures to a steady state was 4.8 ± 0.8 s. SICH had no impact on blood pressure or heart rate and was safely performed without complications by using a 3.9 F catheter. Interleukin-6 (IL-6), tumor necrosis factor-α, C-reactive protein (CRP), and brain natriuretic peptide (BNP) were lower at 60 min post perfusion in pigs that underwent SICH as compared with the control group. On day 5 post MI/R, edema, intramyocardial hemorrhage, and microvascular obstruction were reduced in the hypothermia group. On day 42 post MI/R, the infarct size, IL-6, CRP, BNP, and matrix metalloproteinase-9 were reduced, and the ejection fraction was improved in pigs that underwent SICH.Conclusions::The SICH device safely and effectively reduced the infarct size and improved heart function in a pig model of MI/R. These beneficial effects indicate the clinical potential of SICH for treatment of myocardial reperfusion injury.

This study reported two women with extreme obesity who underwent metabolic surgery due to their mutations in leptin receptor (LEPR).Genomic DNA was extracted from the anticoagulant blood samples of the two patients and their parents.A panel of genes related to metabolic diseases or whole exon sequencing was screened and the results were confirmed by Sanger sequencing.This is the first time that these three mutations in LEPR were reported.Two patients complained insatiety and early-onset obesity since childhood at clinics.Patient 1 was a 39-year-old woman with height 150 cm,weight 130 kg,and BMI 57.8 kg/m2.Serum leptin level was 156.4 μg/L.A homozygous mutation of c.2317G＞T was found in exon 15 of LEPR gene in patient 1,which was descended from her father and mother respectively.Patient 2 was a 37-year-old woman with height 158 cm,weight 167 kg,and BMI 67 kg/m2.Serum leptin level was 193.4 μg/L.Genetic analysis showed compound heterozygous mutations of c.1482delT and c.1892C ＞ A.Her father showed heterozygous c.1482delT mutation,and her mother carried heterozygous c.1892C ＞ A mutation.Two patients all underwent metabolic surgery with body weight reduction of about 22 kg and 40 kg respectively after first six months.However,the follow-up studies showed that the body weight of patient 1 rebounded to pre-surgery level in two years and patient 2 did not further lose weight in the following six months.