Integrated bioinformatics analysis identifies immune-related epithelial-mesenchymal transition prognostic biomarkers and immune infiltrates in patients with lung adenocarcinoma

Background:Lung cancer,particularly lung adenocarcinoma(LUAD),is highly lethal.Understanding the critical interaction between epithelial-mesenchymal transition(EMT)and the immune status of patients is imperative for clinical assessment.Methods:We conducted bioinformatics analysis to identify potential immune-related EMT(iEMT)prognostic genes and explored the immune status in LUAD.Using data from The CancerGenome Atlas andGSE68465,differentially expressed genes,were identified,and a risk modelwas constructed.Cluster analysis was conducted using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways.Results:Our findings revealed 69 differentially expressed iEMT genes,with risk values demonstrating independent prognostic significance for both The Cancer Genome Atlas and GSE68465 samples.The risk value was positively correlated with tumor stage.Immune cell infiltration analysis showed a significant decrease in resting dendritic cells and an increase in CD4 memory T cells in high-risk groups with poor survival prognoses.The immunotherapy analysis revealed weak immunotherapeutic effects in the high-risk group.Conclusions:This study provides insights into potential aberrant differential iEMT genes and risk models and explores immune landscapes that inform personalized immunotherapy in patients with LUAD.

Application of Low Tube Voltage, Low-concentration Contrast Agent Using a 320-row CT in Coronary CT Angiography: Evaluation of Image Quality, Radiation Dose and Iodine Intake

The effect of low voltage and low concentration contrast agent on image quality of coronary CT angiography,radiation dose and iodine intake was evaluated.A total of 121 patients with body mass index(BMI)<26 kg/m2 and heart rate(HR)<70 beats/min were randomly divided into four groups:group A(n=31,80 kVp,270 mgl/mL);group B(n=33,100 kVp,270 mgl/mL);group C(h=30,100 kVp,320 mgl/mL);group D(w=27,100 kVp,400 mgl/mL).The automatic current modulation system and the iterative algorithm for reconstruction were adopted in each group.The CT values and SD values of the aortic root(AR),subcutaneous fat,left coronary artery opening(LCA),and right coronary artery opening(RCA)were measured in all groups,the signalto-noise ratio(SNR)and contrast noise ratio(CNR)were calculated,and effective radiation dose and iodine intake were recorded.The subjective assessment for image quality was performed by two physicians using a 4-point scale.The results were compared using the one-way ANOVA and rank sum tests.The image quality of the four groups met the clinical diagnostic requirements.The CT values of AR in groups A,B,C,and D were 537.6±71.4,447.2±81.9,445.2±64.9 and 518.5±94.9 Hu,respectively,with no significant difference between group A and group D,or between group B and group C,while CT values in groups B and C were significantly lower than those in groups A and D(P<0.05).In groups A,B,C,and D,the LCA SNR values were 22.7±9.1,23.3±9.1,23.3±7.7 and 26.6±8.9,and the RCA CNR values were 26.9±9.&28.5±11.4,27.7土&8 and 32」±10.6,respectively.The AR visual scores in groups A,B,C and D were 3.8±0.2,3.9±0.3,3.9±0.3 and 4.0±0.3,respectively.There were no significant differences in SNR,CNR and visual score among the four groups(P>0.05).The radiation doses in groups A,B,C and D were 2.6±1.4,3.6±1.&4.9±3.5 and 4.9±2.8 mSv,respectively.The radiation dose in group A was significantly less than that in the rest three groups(P<0.05).The iodine intakes in groups A,B,C and D were 14.9±1.5,15.0±1.5,17.7±2.0 and 18.1±2.5 g,respectively.There was no significant difference in the intake of iodine between groups C and D,or between groups A and B,while iodine intake in groups A and B were significantly reduced as compared with that in groups C and D(P<0.05).It was concluded that for patients with low BMI and controlled HR,compared to 100 kVp tube voltage combined with multiple concentration contrast agents,80 kVp combined with 270 mgl/mL contrast agent is enough to ensure the quality of the images,and can reduce the radiation dose significantly,while reducing the amount of iodine intake notably,thus reducing the incidence of adverse reaction.

Comparison of Various Parameters of DWI in Distinguishing Solitary Pulmonary Nodules

In order to prospectively assess various parameters of diffusion weighted imaging (DWI)in differential diagnosis of benign and malignant solitary pulmonary nodules (SPNs),58 patients (40 men and 18 women,and mean age of 48.1±10.4years old) with SPNs undergoing conventional MR,DWI using b=500s/mm^2 on a 1.5T MR scanner, were studied.Various DWI parameters [apparent diffusion coefficient (ADC),lesion-to-spinal cord signal intensity ratio (LSR),signal intensity (SI)score] were calculated and compared between malignant and benign SPNs groups.A receiver operating characteristic (ROC)curve analysis was employed to compare the diagnostic capabilities of all the parameters for discrimination between benign and malignant SPNs.The results showed that there were 42 malignant and 16 benign SPNs.The ADC was significantly,lower in malignant SPNs (1.40±0.44)×10^-3mm^2/s than in benign SPNs (1.81±0.58)×10^-3mm^2/ s.The LSR and SI scores were significantly increased in malignant SPNs (0.90±0.37 and 2.8±1.2)as compared with those in benign SPNs (0.68±0.39 and 2.2±1.2).The area under the ROC curves (AUC)of all parameters was not significantly different between malignant SPNs and benign SPNs.It was suggested that as three reported parameters for DWI,ADC,LSR and SI scores are all feasible for discrimination of malignant and benign SPNs.The three parameters have equal diagnostic performance.

IgG4-Related Disease:A Retrospective Chinese Study of Features and Treatment Response of 98 Patients Including 4 Rare Cases

The features and treatment of 98 Chinese patients with immunoglobulin G4 (IgG4)-related disease (IgG4-RD) referred to a single tertiary referring centre were reviewed. Patientsdiagnosed with IgG4-RD according to the comprehensive diagnostic criteria (CDC) were includedin the retrospective study from May 2012 to March 2019. We collcted data on clinical, laboratory,imaging, histological features and treatment. Totally, 98 patients with IgG4-RD were enrolled.The common clinical manifestations included abdominal pain, salivary gland swelling andlymphadenopathy. 51% of the patients had multiple organs involvement. Lymph nodes, pancreasand salivary glands were most commonly involved. Four rare sites including ulna, cerebellum,scalp, and mammary gland were found. The serum IgG4 level was increased by 85.7%. The serumIgG4 level was positively correlated with the number of involved organs, IgG and IgG4/IgG. LowC3 and C4 levels were observed in 37.5% and 12.2% patients respectively, and all patients withkidney involvement had hypocomplementemia. A total of 54 patients underwent tissue biopsies,and 55.6%, 31.5% and 11.1% cases were diagnosed as definite, probable and possible IgG4-RD,respectively. Eighty-eight patients received glucocorticoids (GCs) therapy. Five patients underwentradical surgery to remove the lesion. 73% of them presented a complete or partial remission. IgG4-RD is a systemic fibroinflammatory disease with involvement of multiple organs throughout thebody including some rare sites. Most IgG4-RD patients had increased serum IgG4 levels andpatients with kidney involvement showed bypocomplementermia. GCs therapy is effective. Moreresearch is needed to provide a more reliable basis for the diagnosis and treatment of patients.

Balanced Quantization： An Effective and Efficient Approach toQuantized Neural Networks

Quantized neural networks (QNNs), which use low bitwidth numbers for representing parameters and performing computations, have been proposed to reduce the computation complexity, storage size and memory usage. In QNNs, parameters and activations are uniformly quantized, such that the multiplications and additions can be accelerated by bitwise operations. However, distributions of parameters in neural networks are often imbalanced, such that the uniform quantization determined from extremal values may underutilize available bitwidth. In this paper, we propose a novel quantization method that can ensure the balance of distributions of quantized values. Our method first recursively partitions the parameters by percentiles into balanced bins, and then applies uniform quantization. We also introduce computationally cheaper approximations of percentiles to reduce the computation overhead introduced. Overall, our method improves the prediction accuracies of QNNs without introducing extra computation during inference, has negligible impact on training speed, and is applicable to both convolutional neural networks and recurrent neural networks. Experiments on standard datasets including ImageNet and Penn Treebank confirm the effectiveness of our method. On ImageNet, the top-5 error rate of our 4-bit quantized GoogLeNet model is 12.7%, which is superior to the state-of-the-arts of QNNs.