Miniaturized leaky-wave antenna with backward-to-forward beam scanning and suppressed open stop-band based on substrate-integrated plasmonic waveguide.

This work presents a theoretical design and experimental demonstration of a novel miniaturized leaky-wave antenna (LWA) using composite waveguide based on substrate-integrated plasmonic waveguide (SIPW). The SIPW is designed by embedding hybrid dual spoof surface plasmon polariton (SSPP) structure into a three-layer substrate integrated waveguide (SIW). Due to the slow-wave effect of SIPW, the proposed miniaturized composite waveguide forms slowed phase velocity and decreased lower cutoff frequency. To excite backward-to-forward beam scanning mode and suppress the open stop-band, an asymmetric sinusoidal modulated structure is introduced to the surface of the composite waveguide. The experimental results indicate that the proposed SIPW-based LWA can achieve continuous beam scanning from the backward to the forward direction within the bandwidth of 10.6-13.7 GHz, passing through the broadside at 11.6 GHz.

Experimental realization of a transmissive microwave metasurface for dual vector vortex beams generation.

This work presents a theoretical design and experimental demonstration of a transmissive microwave metasurface for generating dual-vector vortex beams (VVBs). The proposed metasurface consists of an array of pixelated dartboard discretization meta-atoms. By rotating the meta-atoms from 0° to 180°, a Pancharatnam-Barry (P-B) phase covering the full 360° range is achieved, with a transmittance exceeding 90% over the frequency range from 9.7 to 10.2 GHz. The measured results demonstrate that when a linearly polarized microwave normally impinges on the metasurface, the transmitted beams correspond to the dual VVBs with different directions. A good agreement among Poincaré sphere theory, full-wave simulation, and experimental measurement is observed. This proposed transmissive microwave metasurface for VVBs may offer promising applications in communications and radar detection.

Effective recovery of the nitritation process through hydrogen peroxide.

This study successfully achieved stable nitritation by adding hydrogen peroxide (H2O2) to the nitrification sludge whose nitritation stability had been destroyed. The batch experiment demonstrated that, the activity of ammonia-oxidizing bacteria (AOB) was restored more rapidly than that of nitrite oxidizing bacteria (NOB) after the addition of H2O2, thereby selectively promoting AOB enrichment and NOB washout. When the H2O2 concentration was 6.25 mg/L, the NOB activity was significantly reduced and the nitrite accumulation rate (NAR) was more than 95% after 18 cycles of nitrifying sludge restoration. As a result, H2O2 treatment enabled a nitrifying reactor to recover stable nitritation performance via H2O2 treatment, with the NAR and ammonia removal efficiency (ARE) both exceeding 90%. High-throughput sequencing analysis revealed that H2O2 treatment was successful in restoring nitritation, as the relative abundance of Nitrosomonas in the nitrifying reactor increased from 6.43% to 41.97%, and that of Nitrolancea decreased from 17.34% to 2.37%. Recovering nitritation by H2O2 inhibition is a low operational cost, high efficiency, and non-secondary pollution nitritation performance stabilization method. By leveraging the varying inhibition degrees of H2O2 on AOB and NOB, stable nitrification can be efficiently restored at a low cost and without causing secondary pollution.

Transfer learning-based PET/CT three-dimensional convolutional neural network fusion of image and clinical information for prediction of EGFR mutation in lung adenocarcinoma.

BACKGROUND: To introduce a three-dimensional convolutional neural network (3D CNN) leveraging transfer learning for fusing PET/CT images and clinical data to predict EGFR mutation status in lung adenocarcinoma (LADC). METHODS: Retrospective data from 516 LADC patients, encompassing preoperative PET/CT images, clinical information, and EGFR mutation status, were divided into training (n = 404) and test sets (n = 112). Several deep learning models were developed utilizing transfer learning, involving CT-only and PET-only models. A dual-stream model fusing PET and CT and a three-stream transfer learning model (TS_TL) integrating clinical data were also developed. Image preprocessing includes semi-automatic segmentation, resampling, and image cropping. Considering the impact of class imbalance, the performance of the model was evaluated using ROC curves and AUC values. RESULTS: TS_TL model demonstrated promising performance in predicting the EGFR mutation status, with an AUC of 0.883 (95%CI = 0.849-0.917) in the training set and 0.730 (95%CI = 0.629-0.830) in the independent test set. Particularly in advanced LADC, the model achieved an AUC of 0.871 (95%CI = 0.823-0.919) in the training set and 0.760 (95%CI = 0.638-0.881) in the test set. The model identified distinct activation areas in solid or subsolid lesions associated with wild and mutant types. Additionally, the patterns captured by the model were significantly altered by effective tyrosine kinase inhibitors treatment, leading to notable changes in predicted mutation probabilities. CONCLUSION: PET/CT deep learning model can act as a tool for predicting EGFR mutation in LADC. Additionally, it offers clinicians insights for treatment decisions through evaluations both before and after treatment.

New research progress on 18F-FDG PET/CT radiomics for EGFR mutation prediction in lung adenocarcinoma: a review.

Lung cancer, the most frequently diagnosed cancer worldwide, is the leading cause of cancer-associated deaths. In recent years, significant progress has been achieved in basic and clinical research concerning the epidermal growth factor receptor (EGFR), and the treatment of lung adenocarcinoma has also entered a new era of individualized, targeted therapies. However, the detection of lung adenocarcinoma is usually invasive. 18F-FDG PET/CT can be used as a noninvasive molecular imaging approach, and radiomics can acquire high-throughput data from standard images. These methods play an increasingly prominent role in diagnosing and treating cancers. Herein, we reviewed the progress in applying 18F-FDG PET/CT and radiomics in lung adenocarcinoma clinical research and how these data are analyzed via traditional statistics, machine learning, and deep learning to predict EGFR mutation status, all of which achieved satisfactory results. Traditional statistics extract features effectively, machine learning achieves higher accuracy with complex algorithms, and deep learning obtains significant results through end-to-end methods. Future research should combine these methods to achieve more accurate predictions, providing reliable evidence for the precision treatment of lung adenocarcinoma. At the same time, facing challenges such as data insufficiency and high algorithm complexity, future researchers must continuously explore and optimize to better apply to clinical practice.

Transmissive Pancharatnam-Berry metasurfaces with stable amplitude and precise phase modulations using dartboard discretization configuration.

Metasurfaces are ultra-thin artificial structures capable of flexibly manipulating electromagnetic (EM) waves. Among various applications, phase modulation of electromagnetic (EM) waves using metasurfaces holds great significance. The Pancharatnam-Berry (P-B) metasurfaces provides a complete 2π phase modulation by simply rotating the meta-atom. However, the fixed lattice in rotation employed by traditional P-B metasurfaces often results in unstable amplitude and imprecise P-B phase, leading to performance degradation. In this work, we demonstrate transmissive P-B metasurfaces with stable amplitude and precise phase modulation. To ensure stable amplitude and precise P-B phase, we adopt a dartboard discretization configuration with a hexagonal lattice for the meta-atom design. By applying topology optimization to the encoding sequence formed by surface pixels and dimensions, we significantly enhancing the high transmissive bandwidth of the optimized meta-atom. Furthermore, the optimized meta-atom exhibits a stable amplitude and precise P-B phase for each rotation angle. As proof-of-concept demonstrations, two metasurfaces for single and multiplexed vortex beams generating are designed utilizing the optimized meta-atom. Both the simulated and measured results indicate high mode purity of generated vortex beams. The design method can also be readily extended to other high performance metasurfaces with stable amplitude and precise phase manipulations, which can enhance the efficiency and capacity of metasurface-assisted holographic imaging and 6 G wireless communication systems.

The predictive value of [18F]FDG PET/CT radiomics combined with clinical features for EGFR mutation status in different clinical staging of lung adenocarcinoma.

BACKGROUND: This study aims to construct radiomics models based on [18F]FDG PET/CT using multiple machine learning methods to predict the EGFR mutation status of lung adenocarcinoma and evaluate whether incorporating clinical parameters can improve the performance of radiomics models. METHODS: A total of 515 patients were retrospectively collected and divided into a training set (n = 404) and an independent testing set (n = 111) according to their examination time. After semi-automatic segmentation of PET/CT images, the radiomics features were extracted, and the best feature sets of CT, PET, and PET/CT modalities were screened out. Nine radiomics models were constructed using logistic regression (LR), random forest (RF), and support vector machine (SVM) methods. According to the performance in the testing set, the best model of the three modalities was kept, and its radiomics score (Rad-score) was calculated. Furthermore, combined with the valuable clinical parameters (gender, smoking history, nodule type, CEA, SCC-Ag), a joint radiomics model was built. RESULTS: Compared with LR and SVM, the RF Rad-score showed the best performance among the three radiomics models of CT, PET, and PET/CT (training and testing sets AUC: 0.688, 0.666, and 0.698 vs. 0.726, 0.678, and 0.704). Among the three joint models, the PET/CT joint model performed the best (training and testing sets AUC: 0.760 vs. 0.730). The further stratified analysis found that CT_RF had the best prediction effect for stage I-II lesions (training set and testing set AUC: 0.791 vs. 0.797), while PET/CT joint model had the best prediction effect for stage III-IV lesions (training and testing sets AUC: 0.722 vs. 0.723). CONCLUSIONS: Combining with clinical parameters can improve the predictive performance of PET/CT radiomics model, especially for patients with advanced lung adenocarcinoma.

Association Analysis of Maximum Standardized Uptake Values Based on 18F-FDG PET/CT and EGFR Mutation Status in Lung Adenocarcinoma.

(1) Background: To investigate the association between maximum standardized uptake value (SUVmax) based on 18F-FDG PET/CT and EGFR mutation status in lung adenocarcinoma. (2) Methods: A total of 366 patients were retrospectively collected and divided into the EGFR mutation group (n = 228) and EGFR wild-type group (n = 138) according to their EGFR mutation status. The two groups' general information and PET/CT imaging parameters were compared. A hierarchical binary logistic regression model was used to assess the interaction effect on the relationship between SUVmax and EGFR mutation in different subgroups. Univariate and multivariate logistic regression was used to analyze the association between SUVmax and EGFR mutation. After adjusting for confounding factors, a generalized additive model and smooth curve fitting were applied to address possible non-linearities. (3) Results: Smoking status significantly affected the relationship between SUVmax and EGFR mutation (p for interaction = 0.012), with an interaction effect. After adjusting for age, gender, nodule type, bronchial sign, and CEA grouping, in the smoking subgroup, curve fitting results showed that the relationship between SUVmax and EGFR mutation was approximately linear (df = 1.000, c2 = 3.897, p = 0.048); with the increase in SUVmax, the probability of EGFR mutation gradually decreased, and the OR value was 0.952 (95%CI: 0.908-0.999; p = 0.045). (4) Conclusions: Smoking status can affect the relationship between SUVmax and EGFR mutation status in lung adenocarcinoma, especially in the positive smoking history subgroup. Fully understanding the effect of smoking status will help to improve the accuracy of SUVmax in predicting EGFR mutations.

Tannins amount determines whether tannase-containing bacteria are probiotic or pathogenic in IBD.

The role of dietary tannin in inflammatory bowel disease (IBD) is still not clear. Therefore, we aim to study the effect of TA in the progression of IBD. Dextran sulphate sodium (DSS)-induced model was used to mimic IBD. Metagenomics and metabolomics were performed to study the alteration of intestinal microbiota and metabolites. NCM460 and THP-1 cells were used for in vitro study. The amount of TA was associated with the outcomes of DSS-induced IBD as evidenced by in vivo and in vitro studies. Metabolomic and metagenomic analyses revealed that TA-induced enrichment of microbial metabolite gallic acid (GA) was responsible for the action of TA. Mechanistically, protective dose of GA promoted colonic mucus secretion to suppress bacterial infection and that it ameliorated DSS-induced epithelial damage by inhibiting p53 signaling, whereas toxic dose of GA directly caused epithelial damage by promoting cell cycle arrest. Therapeutic experiment showed protective dose of GA-promoted recovery of DSS-induced colonic inflammation. The role of tannase-containing bacteria can be transformed under different conditions in IBD progression.

Phase-to-pattern inverse design for a fast realization of a functional metasurface by combining a deep neural network and a genetic algorithm.

Metasurface provides an unprecedented means to manipulate electromagnetic waves within a two-dimensional planar structure. Traditionally, the design of meta-atom follows the pattern-to-phase paradigm, which requires a time-consuming brute-forcing process. In this work, we present a fast inverse meta-atom design method for the phase-to-pattern mapping by combining the deep neural network (DNN) and genetic algorithm (GA). The trained classification DNN with an accuracy of 92% controls the population generated by the GA within an arbitrary preset small phase range, which could greatly enhance the optimization efficiency with less iterations and a higher accuracy. As proof-of-concept demonstrations, two reflective functional metasurfaces including an orbital angular momentum generator and a metalens have been numerically investigated. The simulated results agree very well with the design goals. In addition, the metalens is also experimentally validated. The proposed method could pave a new avenue for the fast design of the meta-atoms and functional meta-devices.

The application of pre-hospital first aid mode in patients with acute stroke: meta-analysis.

To systematically evaluate the application effect of pre-hospital and in-hospital emergency mode in patients with acute stroke. The study was conducted by systematic search of Chinese (CNKI, Wanfang and VIP) and English (PubMed, EMBASE and Cochrane Library) databases. The case-control studies comparing the role of pre-hospital and in-hospital emergency mode for patients with acute stroke were included in this study. Outcome indicators included the time from admission to thrombolytic therapy (DNT), the time from calling for help to receiving professional treatment, the first aid effect (effective rate, disability rate and mortality), complications and prognosis. Meta-analysis was performed using RevMan 5.3. Seventeen studies were included in the final analysis. Compared with traditional emergency measures, pre-hospital and in-hospital emergency measures can significantly reduce DNT (mean difference [MD] = -22.63, p < 0.00001), time from call to professional treatment (MD: -13.22, p < 0.00001), disability rate (RR = 0.88, p = 0.004), fatality rate (RR = 0.58, p < 0.00001), central cerebral fever (RR = 0.44, p = 0.0009), and gastrointestinal bleeding (RR = 0.44, p = 0.002). In addition, daily living ability (MD = 16.56, p < 0.00001) and emergency response rate (RR = 1.50, p < 0.00001) were significantly improved. The pre-hospital and in-hospital emergency mode has a significant emergency effect in patients with acute stroke, which is a protective factor. This emergency mode can be widely used in clinical practice.

Association between squamous cell carcinoma antigen level and EGFR mutation status in Chinese lung adenocarcinoma patients.

BACKGROUND: To investigate the association between squamous cell carcinoma antigen (SCCAg) level and epidermal growth factor receptor (EGFR) mutation status in Chinese lung adenocarcinoma patients. METHODS: We retrospectively analyzed 293 patients with lung adenocarcinoma, divided into EGFR mutant group (n = 178) and EGFR wild-type group (n = 115). The general data and laboratory parameters of the two groups were compared. We used univariable and multivariable logistic regression to analyze the association between SCCAg level and EGFR mutation. Generalized additive model was used for curve fitting, and a hierarchical binary logistic regression model was used for interaction analysis. RESULTS: Squamous cell carcinoma antigen level in the EGFR wild-type group was significantly higher than that in the mutant group (p < 0.001). After adjusting for confounding factors, we found that elevated SCCAg was associated with a lower probability of EGFR mutation, with an OR of 0.717 (95% CI: 0.543-0.947, p = 0.019). For the tripartite SCCAg groups, the increasing trend of SCCAg was significantly associated with the decreasing probability of EGFR mutation (p for trend = 0.015), especially for Tertile 3 versus Tertile 1 (OR = 0.505; 95% CI: 0.258-0.986; p = 0.045). Curve fitting showed that there was an approximate linear negative relationship between continuous SCCAg and EGFR mutation probability (p = 0.020), which was first flattened and then decreased (p < 0.001). The association between the two was consistent among different subgroups, suggesting no interaction (all p > 0.05). CONCLUSION: There is a negative association between SCCAg level and EGFR mutation probability in Chinese lung adenocarcinoma patients.

Identification of the three subtypes and the prognostic characteristics of stomach adenocarcinoma: analysis of the hypoxia-related long non-coding RNAs.

Stomach adenocarcinoma (STAD) is one of the most commonly diagnosed cancers. This study analyzed the subtypes and characteristics of STAD subtypes by analyzing hypoxia pathway-related lncRNAs. Potential hub lncRNAs were found and a prognostic model was constructed. Expression profiling data and clinical information of STAD were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Metabolic pathway scores were calculated using single-sample gene set enrichment analysis (ssGSEA) method. Tumor immune microenvironment scores of the samples were assessed by ESTIMATE, MCP-counter, and ssGSEA. Functional analysis of lncRNAs, construction of risk models, and drug sensitivity analysis were performed. Pathway analysis revealed that the hypoxia pathway was a prognostic risk factor. Molecular subtypes were developed based on the hypoxia score-related lncRNAs. Three molecular subtypes (C1, C2, and C3) for gastric STAD were determined. The worst prognosis was in the C2, which was also characterized by the maximum hypoxia pathway-related scores and the maximum immune score. A majority of the immune checkpoints and chemokines were high-expressed in the C2 subtype. Mutations in the C2 subtype were significantly lower than the C1 and C3 subtypes. The subtypes differed in terms of functional and metabolic pathways. Eight hub indicator lncRNAs (MSC-AS1, AC037198.1, LINC00968, AL139393.3, LINC02544, BOLA3-AS1, MIR1915HG, and AC107021.2) capable of predicting patient prognosis were identified. Three hypoxia lncRNA-related molecular subtypes characterized by different prognostic and immune conditions were identified. The results maybe can provide a theoretical basis to improve the clinical diagnosis and treatment of STAD.

Risk analysis in peripheral clinical T1 non-small cell lung cancer correlations between tumor-to-blood standardized uptake ratio on 18F-FDG PET-CT and primary tumor pathological invasiveness: a real-world observational study.

BACKGROUND: Sublobar resection is not suitable for patients with pathological invasiveness [including lymph node metastasis (LNM), visceral pleural invasion (VPI), and lymphovascular invasion (LVI)] of peripheral clinical T1 (cT1) non-small cell lung cancer (NSCLC), while primary tumor maximum standardized uptake value (SUVmax) on 18F-FDG PET-CT is related to pathological invasiveness, the significance differed among different institutions is still challenging. This study explored the relationship between the tumor-to-blood standardized uptake ratio (SUR) of 18F-FDG PET-CT and primary tumor pathological invasiveness in peripheral cT1 NSCLC patients. METHODS: This retrospective study included 174 patients with suspected lung neoplasms who underwent preoperative 18F-FDG PET-CT. We compared the differences of the clinicopathological variables, metabolic and morphological parameters in the pathological invasiveness and less-invasiveness group. We performed a trend test for these parameters based on the tertiles of SUR. The relationship between SUR and pathological invasiveness was evaluated by univariate and multivariate logistics regression models (included unadjusted, simple adjusted, and fully adjusted models), odds ratios (ORs), and 95% confidence intervals (95% CIs) were calculated. A smooth fitting curve between SUR and pathological invasiveness was produced by the generalized additive model (GAM). RESULTS: Thirty-eight point five percent of patients had pathological invasiveness and tended to have a higher SUR value than the less-invasiveness group [6.50 (4.82-11.16) vs. 4.12 (2.04-6.61), P<0.001]. The trend of SUVmax, mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), mean CT value (CTmean), size of the primary tumor, neuron-specific enolase (NSE), the incidence of LNM, adenocarcinoma (AC), and poor differentiation in the tertiles of SUR value were statistically significant (P were <0.001, <0.001, 0.010, <0.001, <0.001, 0.002, 0.033, <0.001, 0.002, and <0.001, respectively). Univariate analysis showed that the risk of pathological invasiveness increased significantly with increasing SUR [OR: 1.13 (95% CI: 1.06-1.21), P<0.001], and multivariate analysis demonstrated SUR, as a continuous variable, was still significantly related to pathological invasiveness [OR: 1.09 (95% CI: 1.01-1.18), P=0.032] after adjusting for confounding covariates. GAM revealed that SUR tended to be linearly and positively associated with pathological invasiveness and E-value analysis suggested robustness to unmeasured confounding. CONCLUSIONS: SUR is linearly and positively associated with primary tumor pathological invasiveness independent of confounding covariates in peripheral cT1 NSCLC patients and could be used as a supplementary risk maker to assess the risk of pathological invasiveness.

Feasibility and application of trimetazidine in 18F-FDG PET myocardial metabolic imaging of diabetic mellitus patients with severe coronary artery disease: A prospective, self-controlled study.

BACKGROUND: 18F-FDG PET myocardial metabolic imaging (MMI) is sometimes uninterpretable due to background activity from uncontrolled glucose homeostasis in diabetic mellitus (DM) patients. Trimetazidine is an oral medication that promotes the transformation of myocardial energy supply from free fatty acids to glucose. We aimed to investigate the feasibility and application of trimetazidine in 18F-FDG PET MMI of DM patients. METHODS: With DM patients exhibiting severe coronary artery disease (CAD) symptoms serving as self-controls, the effects of trimetazidine on PET MMI image quality, myocardial viability assessment, quantitative analytical parameters, and 18F-FDG uptake of different myocardial segments were elucidated. RESULTS: The image quality of 18F-FDG MMI was graded visually as good, moderate, and uninterpretable. After trimetazidine, grades of good, moderate, and uninterpretable were observed in 14 (60.9%), 8 (34.8%), and 1 (4.3%) patients, respectively, and in 4 (17.4%), 15 (65.2%), 4 (17.4%) patients without trimetazidine. The myocardial SUV and myocardial to blood pool SUV ratio (M/B ratio) were significantly higher after trimetazidine administration than those before (3.11 ± 1.07 vs 2.32 ± 1.00, 2.67 ± 1.41 vs 1.81 ± 0.75, P all < 0.01). 6 (3, 7) viable myocardium segments were detected with a mismatch score of 10 (6, 17) after trimetazidine, significantly higher than those before trimetazidine [5 (2, 7) and 8 (2, 17), P < 0.05]. Meanwhile, the 18F-FDG uptake in myocardial segments with decreased and normal perfusion showed different ranges of increase (by 15.30%-57.77%). CONCLUSION: Trimetazidine is feasible and effective in DM patients with severe CAD before 18F-FDG PET MMI, which can significantly improve the image quality and increase the number of viable myocardium segments detected. TRIAL REGISTRY: The study was registered in the Chinese Clinical Trial Registry (ChiCTR2000038559).

Relationship between total lesion glycolysis of primary lesions based on 18F-FDG PET/CT and lymph node metastasis in gastric adenocarcinoma: a cross-sectional preliminary study.

OBJECTIVES: We explored the relationship between lymph node metastasis (LNM) and total lesion glycolysis (TLG) of primary lesions determined by 18fluoro-2-deoxyglucose PET/computed tomography (18F-FDG PET/CT) in patients with gastric adenocarcinoma, and evaluated the independent effect of this association. METHODS: This retrospective study included 106 gastric adenocarcinoma patients who were examined by preoperative 18F-FDG PET/CT imaging between April 2016 and April 2020. We measured TLG of primary gastric lesions and evaluated its association with LNM. Multivariate logistic regression and a two-piece-wise linear regression were performed to evaluate the relationship between TLG of primary lesions and LNM. RESULTS: Of the 106 patients, 75 cases (71%) had LNM and 31 cases (29%) did not have LNM. Univariate analyses revealed that a per-SD increase in TLG was independently associated with LNM [odds ratio (OR) = 2.37; 95% confidence interval (CI), 1.42-3.98; P = 0.0010]. After full adjustment of confounding factors, multivariate analyses exhibited that TLG of primary lesions was still significantly associated with LNM (OR per-SD: 2.20; 95% CI, 1.16-4.19; P = 0.0164). Generalized additive model indicated a nonlinear relationship and saturation effect between TLG of primary lesions and LNM. When TLG of primary lesions was <23.2, TLG was significantly correlated with LNM (OR = 1.26; 95% CI, 1.07-1.48; P = 0.0053), whereas when TLG of primary lesions was ≥ 23.2, the probability of LNM was greater than 60%, gradually reached saturation effect, as high as 80% or more. CONCLUSIONS: In this preliminary study, there were saturation and segmentation effects between TLG of primary lesions determined by preoperative 18F-FDG PET/CT and LNM. When TLG of primary lesions was ≥ 23.2, the probability of LNM was greater than 60%, gradually reached saturation effect, as high as 80% or more. TLG of primary lesions is helpful in the preoperative diagnosis of LNM in patients with gastric adenocarcinoma.

Circ_0014235 confers Gefitinib resistance and malignant behaviors in non-small cell lung cancer resistant to Gefitinib by governing the miR-146b-5p/YAP/PD-L1 pathway.

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs), such as Gefitinib, have been recommended as the first-line treatment reagent for advanced EGFR-mutant non-small cell lung cancer (NSCLC). However, the mechanisms of drug resistance development are not fully determined. This study aimed to explore the role of circular RNA (circ_0014235) in Gefitinib-resistant NSCLC. The expression of circ_0014235, microRNA-146b-5p (miR-146b-5p) and Yes1 associated transcriptional regulator (YAP) mRNA was detected by quantitative real-time PCR (qPCR). Cell viability was detected by CCK-8 assay. Cell proliferation was assessed by colony formation assay and EdU assay. Cell cycle and cell apoptosis were determined by flow cytometry assay. The expression of marker proteins, YAP protein and programmed death ligand 1 (PD-L1) protein was detected by Western blot. The putative relationship between miR-146b-5p and circ_0014235 or YAP was ensured by dual-luciferase reporter assay and RIP assay. Animal models were established to explore the role of circ_0014235 in vivo. Circ_0014235 was highly expressed in Gefitinib-resistant NSCLC cells. Circ_0014235 downregulation reduced Gefitinib IC50, inhibited cell proliferation and induced cell apoptosis and cell cycle arrest in Gefitinib-resistant NSCLC cells, while these effects were reversed by the inhibition of miR-146b-5p, a target of circ_0014235. In addition, YAP was a target gene of miR-146b-5p, and circ_0014235 relieved miR-146b-5p-mediated inhibition on YAP by targeting miR-146b-5p. MiR-146b-5p restoration-blocked Gefitinib IC50 and cell malignant behaviors were recovered by YAP overexpression. YAP positively regulated PD-L1 expression, and YAP overexpression contributes to Gefitinib IC50 and cell malignant behaviors by upregulating PD-L1. Circ_0014235 confers Gefitinib resistance and malignant behaviors in Gefitinib-resistant NSCLC by governing the miR-146b-5p/YAP/PD-L1 pathway.

Radiomics model based on preoperative 18F-fluorodeoxyglucose PET predicts N2-3b lymph node metastasis in gastric cancer patients.

OBJECTIVE: The aim of the study was to construct and validate 18F-fluorodeoxyglucose (18F-FDG) PET-based radiomics nomogram and use it to predict N2-3b lymph node metastasis in Chinese patients with gastric cancer (GC). METHODS: A total of 127 patients with pathologically confirmed GC who underwent preoperative 18F-FDG PET/CT imaging between January 2014 and September 2020 were enrolled as subjects in this study. We use the LIFEx software to extract PET radiomic features. A radiomics signature (Rad-score) was developed with the least absolute shrinkage and selection operator algorithm. Then a prediction model, which incorporated the Rad-score and independent clinical risk factors, was constructed and presented with a radiomics nomogram. Receiver operating characteristic (ROC) analysis was used to assess the performance of Rad-score and the nomogram. Finally, decision curve analysis (DCA) was applied to evaluate the clinical usefulness of the nomogram. RESULTS: The PET Rad-score, which includes four selected features, was significantly related to pN2-3b (all P < 0.05). The prediction model, which comprised the Rad-score and carcinoembryonic antigen (CEA) level, showed good calibration and discrimination [area under the ROC curve: 0.81(95% confidence interval: 0.74-0.89), P < 0.001)]. The DCA also indicated that the prediction model was clinically useful. CONCLUSION: This study presents a radiomics nomogram consisting of a radiomics signature based on PET images and CEA level that can be conveniently used for personalized prediction of high-risk N2-3b metastasis in Chinese GC patients.

Application of dual-stream 3D convolutional neural network based on 18F-FDG PET/CT in distinguishing benign and invasive adenocarcinoma in ground-glass lung nodules.

PURPOSE: This work aims to train, validate, and test a dual-stream three-dimensional convolutional neural network (3D-CNN) based on fluorine 18 (18F)-fluorodeoxyglucose (FDG) PET/CT to distinguish benign lesions and invasive adenocarcinoma (IAC) in ground-glass nodules (GGNs). METHODS: We retrospectively analyzed patients with suspicious GGNs who underwent 18F-FDG PET/CT in our hospital from November 2011 to November 2020. The patients with benign lesions or IAC were selected for this study. According to the ratio of 7:3, the data were randomly divided into training data and testing data. Partial image feature extraction software was used to segment PET and CT images, and the training data after using the data augmentation were used for the training and validation (fivefold cross-validation) of the three CNNs (PET, CT, and PET/CT networks). RESULTS: A total of 23 benign nodules and 92 IAC nodules from 106 patients were included in this study. In the training set, the performance of PET network (accuracy, sensitivity, and specificity of 0.92 ± 0.02, 0.97 ± 0.03, and 0.76 ± 0.15) was better than the CT network (accuracy, sensitivity, and specificity of 0.84 ± 0.03, 0.90 ± 0.07, and 0.62 ± 0.16) (especially accuracy was significant, P-value was 0.001); in the testing set, the performance of both networks declined. However, the accuracy and sensitivity of PET network were still higher than that of CT network (0.76 vs. 0.67; 0.85 vs. 0.70). For dual-stream PET/CT network, its performance was almost the same as PET network in the training set (P-value was 0.372-1.000), while in the testing set, although its performance decreased, the accuracy and sensitivity (0.85 and 0.96) were still higher than both CT and PET networks. Moreover, the accuracy of PET/CT network was higher than two nuclear medicine physicians [physician 1 (3-year experience): 0.70 and physician 2 (10-year experience): 0.73]. CONCLUSION: The 3D-CNN based on 18F-FDG PET/CT can be used to distinguish benign lesions and IAC in GGNs, and the performance is better when both CT and PET images are used together.

Investigating the association between ground-glass nodules glucose metabolism and the invasive growth pattern of early lung adenocarcinoma.

BACKGROUND: To explore the association between the glucose metabolism level of lung ground-glass nodules (GGNs), as revealed by 18F-flurodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) imaging, and the invasive pathological growth pattern of early lung adenocarcinoma. METHODS: We retrospectively analyzed patients who underwent PET/CT examination and surgical resection due to persistent GGNs, which were confirmed to be early lung adenocarcinoma by postoperative pathology examination. After adjusting for confounding factors and performing stratified analysis, we explored the association between the maximum standard uptake value of PET (SUVmax) and the invasive pathological growth pattern of early stage lung adenocarcinoma. RESULTS: The proportions of invasive adenocarcinoma (INV) in the SUVmax of Tertile 1, Tertile 2, and Tertile 3 were 52.7%, 73.3%, and 87.1%, respectively. After adjusting for potential confounding factors, the risk of INV gradually increased as the GGN SUVmax increased [odds ratio (OR): 1.520, 95% confidence interval (CI): 1.044-2.213, P=0.029]. This trend was statistically significant (OR: 1.678, 95% CI: 1.064-2.647, P=0.026), especially in Tertile 3 vs. Tertile 1 (OR: 4.879, 95% CI: 1.349-17.648, P=0.016). Curve fitting showed that the SUVmax and INV risk were linearly and positively associated. The association was consistent in different subgroups based on GGN number, type, shape, edge, bronchial sign, vacuole sign, pleural depression sign, diameters, and consolidation-to-tumor ratio, suggesting that there was no significant interaction between different grouping parameters and the association (P for interaction range = 0.129-0.909). CONCLUSIONS: In FDG PET, the glucose metabolism level (SUVmax) of lung GGNs is independently associated with INV risk, and this association is linear and positive.