CT-based radiomic phenotypes of lung adenocarcinoma: a preliminary comparative analysis with targeted next-generation sequencing

ObjectivesThis study aimed to explore the relationship between computed tomography (CT)-based radiomic phenotypes and genomic profiles, including expression of programmed cell death-ligand 1 (PD-L1) and the 10 major genes, such as epidermal growth factor receptor (EGFR), tumor protein 53 (TP53), and Kirsten rat sarcoma viral oncogene (KRAS), in patients with lung adenocarcinoma (LUAD).MethodsIn total, 288 consecutive patients with pathologically confirmed LUAD were enrolled in this retrospective study. Radiomic features were extracted from preoperative CT images, and targeted genomic data were profiled through next-generation sequencing. PD-L1 expression was assessed by immunohistochemistry staining (chi-square test or Fisher's exact test for categorical data and the Kruskal–Wallis test for continuous data). A total of 1,013 radiomic features were obtained from each patient's CT images. Consensus clustering was used to cluster patients on the basis of radiomic features.ResultsThe 288 patients were classified according to consensus clustering into four radiomic phenotypes: Cluster 1 (n = 11) involving mainly large solid masses with a maximum diameter of 5.1 ± 2.0 cm; Clusters 2 and 3 involving mainly part-solid and solid masses with maximum diameters of 2.1 ± 1.4 cm and 2.1 ± 0.9 cm, respectively; and Cluster 4 involving mostly small ground-glass opacity lesions with a maximum diameter of 1.0 ± 0.9 cm. Differences in maximum diameter, PD-L1 expression, and TP53, EGFR, BRAF, ROS1, and ERBB2 mutations among the four clusters were statistically significant. Regarding targeted therapy and immunotherapy, EGFR mutations were highest in Cluster 2 (73.1%); PD-L1 expression was highest in Cluster 1 (45.5%).ConclusionOur findings provide evidence that CT-based radiomic phenotypes could non-invasively identify LUADs with different molecular characteristics, showing the potential to provide personalized treatment decision-making support for LUAD patients

Diagnostic significance of CK19, TG, Ki67 and galectin-3 expression for papillary thyroid carcinoma in the northeastern region of China

<p>Abstract</p> <p>Background</p> <p>To evaluate the expression and differential diagnostic significance of CK19, TG, Ki67 and galectin-3 in papillary thyroid carcinoma (PTC) (metastatic and non metastatic), follicular adenoma and nodular goiter in patients from the northeastern part of China.</p> <p>Methods</p> <p>441 PTC specimens and 151 other benign thyroid specimens (97 cases of nodular goiter, 54 cases of nonmalignant follicular adenoma) were collected. Immunohistochemistry for CK19, TG, Ki67 and galectin-3 was performed.</p> <p>Results</p> <p>CK19, TG, Ki67 and galectin-3 expression was 96.37% (425/441), 82.77% (365/441), and 40.59% (179/441), 96.82% (427/441), respectively, for the PTC group and the expression of these markers in the benign thyroid lesions group was 25.83% (39/151), 79.47% (120/151), and 37.09% (56/151), 50.99% (77/151), respectively. The expression of CK19 and galectin-3 in PTC was much higher than that in the nonmalignant group (p < 0.05). However, the expression of TG, Ki67 did not differ among these two groups (p > 0.05). The diagnostic efficiency of CK19 and galectin-3 for PTC was 96.37% (537/592) and 84.63% (501/592). CK19 and galectin-3 expression rate in PTC was higher than that in benign disease cases.</p> <p>Conclusions</p> <p>The diagnostic efficiency of CK19 for PTC was slightly better than galectin-3. The utilization of these markers combined with morphologic evaluation may be helpful in the differential diagnosis of papillary thyroid carcinoma in the northeastern region of China.</p

Three-Dimensional MoS2/Reduced Graphene Oxide Nanosheets/Graphene Quantum Dots Hybrids for High-Performance Room-Temperature NO2 Gas Sensors

This study presents three-dimensional (3D) MoS2/reduced graphene oxide (rGO)/graphene quantum dots (GQDs) hybrids with improved gas sensing performance for NO2 sensors. GQDs were introduced to prevent the agglomeration of nanosheets during mixing of rGO and MoS2. The resultant MoS2/rGO/GQDs hybrids exhibit a well-defined 3D nanostructure, with a firm connection among components. The prepared MoS2/rGO/GQDs-based sensor exhibits a response of 23.2% toward 50 ppm NO2 at room temperature. Furthermore, when exposed to NO2 gas with a concentration as low as 5 ppm, the prepared sensor retains a response of 15.2%. Compared with the MoS2/rGO nanocomposites, the addition of GQDs improves the sensitivity to 21.1% and 23.2% when the sensor is exposed to 30 and 50 ppm NO2 gas, respectively. Additionally, the MoS2/rGO/GQDs-based sensor exhibits outstanding repeatability and gas selectivity. When exposed to certain typical interference gases, the MoS2/rGO/GQDs-based sensor has over 10 times higher sensitivity toward NO2 than the other gases. This study indicates that MoS2/rGO/GQDs hybrids are potential candidates for the development of NO2 sensors with excellent gas sensitivity

Synthesis of Cu2O-Modified Reduced Graphene Oxide for NO2 Sensors

Nowadays, metal oxide semiconductors (MOS)-reduced graphene oxide (rGO) nanocomposites have attracted significant research attention for gas sensing applications. Herein, a novel composite material is synthesized by combining two p-type semiconductors, i.e., Cu2O and rGO, and a p-p-type gas sensor is assembled for NO2 detection. Briefly, polypyrrole-coated cuprous oxide nanowires (PPy/Cu2O) are prepared via hydrothermal method and combined with graphene oxide (GO). Then, the nanocomposite (rGO/PPy/Cu2O) is obtained by using high-temperature thermal reduction under Ar atmosphere. The results reveal that the as-prepared rGO/PPy/Cu2O nanocomposite exhibits a maximum NO2 response of 42.5% and is capable of detecting NO2 at a low concentration of 200 ppb. Overall, the as-prepared rGO/PPy/Cu2O nanocomposite demonstrates excellent sensitivity, reversibility, repeatability, and selectivity for NO2 sensing applications

Analysis of distribution method of designed air quantity in coal mine ventilation—a case study

Abstract In a coal mine, air leakage exists in some roadways through doors and other ventilation structures inevitably. Based on this opinion, there are different views on whether these roadways must be assigned airflow in coal mine ventilation design. This paper analyses some relevant regulations and criteria on the designed air quantity of coal mines. Then, based on the ventilation design of the Guizhou Yizhong Coal Mine, through the study of the calculation of needed air quantity of every working place and its distribution method in coal mine ventilation design, this paper puts forward that explosion-proof door, safety exit, and other short distance roadways with ventilation structures need not assign airflow in coal mine ventilation design, while some long-distance roadways need. Additionally, it presents the main reason to support this opinion, gives the distribution method of inner air leakage quantity, which comes with the calculation of the designed mine total air quantity, puts forward the remedy method for the air leakage through ventilation structures in a coal mine ventilation system, then offers the mine operator with the basic opinions for the day-to-day planning and effective operation of a coal mine ventilation system

Quality inspection of nanoscale patterns produced by Laser Interference Lithography using image analysis techniques

This paper introduces the quality inspection of nanoscale patterns produced by the Laser Interference Lithography (LIL) technology using image analysis techniques. In this paper, patterns of two-beam and four-beam interferences are considered. Image analysis techniques based on the Hough transform (HT) and Maximum Likelihood Estimation (MLE) have been applied to detect and estimate various quality parameters for the two types of textures. The HT and a modified grey-scaled HT are introduced as a global approach for the analysis of the two-beam interference patterns. Surface parameters, such as the period, depth, and their uniformities, can be obtained directly without a priori knowledge of the textures. Due to different pattern structures and strong noise effects, the four-beam patterns are dealt with a different approach, using a statistical method based on the likelihood function to estimate each circle's center and shape. Taking into consideration of noises and defects, another further rejection step is introduced to filter out noises and defects. Results from experimental samples are presented