Construction of a predictive model of 2–3 cm ground-glass nodules developing into invasive lung adenocarcinoma using high-resolution CT

BackgroundThe purpose of this study was to analyze the imaging risk factors for the development of 2–3 cm ground-glass nodules (GGN) for invasive lung adenocarcinoma and to establish a nomogram prediction model to provide a reference for the pathological prediction of 2–3 cm GGN and the selection of surgical procedures.MethodsWe reviewed the demographic, imaging, and pathological information of 596 adult patients who underwent 2–3 cm GGN resection, between 2018 and 2022, in the Department of Thoracic Surgery, Second Affiliated Hospital of the Air Force Medical University. Based on single factor analysis, the regression method was used to analyze multiple factors, and a nomogram prediction model for 2–3 cm GGN was established.Results(1) The risk factors for the development of 2–3 cm GGN during the invasion stage of the lung adenocarcinoma were pleural depression sign (OR = 1.687, 95%CI: 1.010–2.820), vacuole (OR = 2.334, 95%CI: 1.222–4.460), burr sign (OR = 2.617, 95%CI: 1.008–6.795), lobulated sign (OR = 3.006, 95%CI: 1.098–8.227), bronchial sign (OR = 3.134, 95%CI: 1.556–6.310), diameter of GGN (OR = 3.118, 95%CI: 1.151–8.445), and CTR (OR = 172.517, 95%CI: 48.023–619.745). (2) The 2–3 cm GGN risk prediction model was developed based on the risk factors with an AUC of 0.839; the calibration curve Y was close to the X-line, and the decision curve was drawn in the range of 0.0–1.0.ConclusionWe analyzed the risk factors for the development of 2–3  cm GGN during the invasion stage of the lung adenocarcinoma. The predictive model developed based on the above factors had some clinical significance

Soil Microbial Community Structure and Physicochemical Properties in <i>Amomum tsaoko</i>-based Agroforestry Systems in the Gaoligong Mountains, Southwest China

Amomum tsaoko is cultivated in forests of tropical and subtropical regions of China, and the planting area is expanding gradually. However, little attention has been paid to the impact of A. tsaoko cultivation on the soil characteristics of the regions. We analyzed the effects of the A. tsaoko-forest agroforestry system (AFs) on the composition of soil microbial communities with increasing stand ages. We also compared the soil physicochemical properties, microbial biomass, and phospholipid fatty acid (PLFA) composition between native forest (NF) and AFs. The results showed that the level of total carbon, nitrogen, and organic matter dramatically dropped in AFs with increasing stand ages. pH affected other soil properties and showed close correlation to total carbon (P = 0.0057), total nitrogen (P = 0.0146), organic matter (P = 0.0075), hydrolyzable nitrogen (P = 0.0085), available phosphorus (P &lt; 0.0001), and available potassium (P = 0.0031). PLFAs of bacteria (F = 4.650, P = 0.037), gram-positive bacteria (F = 6.640, P = 0.015), anaerobe (F = 5.672, P = 0.022), and total PLFA (F = 4.349, P = 0.043) were significantly affected by different treatments, with the greatest value for NF treatment, and least value for AF5. However, the microbial biomass declined during the initial 5 years of cultivation, but it reached the previous level after more than 10 years of cultivation. Our research suggests that AFs is a profitable land-use practice in the Gaoligong Mountains and that AFs showed a recovering trend of the soil nutrient condition with increasing stand ages. However, the severe loss of nitrogen in the soil of AFs requires additional nitrogen during cultivation to restore it to pre-cultivation levels

Spatiotemporal Patterns of Urban Land Use Change in Typical Cities in the Greater Mekong Subregion (GMS)

The Greater Mekong Subregion (GMS) has experienced rapid economic growth and urbanization. However, few studies have paid attention to urban land use dynamics, especially spatiotemporal patterns of urban expansion and land use change, in this region. This research aimed to conduct a comprehensive study of urban land use change in Xishuangbanna, Yangon, Vientiane, Phnom Penh, Bangkok, and Ho Chi Minh City, from 1990 to 2015. The analysis was based on land use maps derived from Landsat satellite products and employed urban expansion intensity, sector analysis, gradient-direction analysis, and landscape metrics. The results show Xishuangbanna, Yangon, Vientiane, Phnom Penh, Bangkok, and Ho Chi Minh City all experienced dramatic urban expansion and land use change since 1990, with urban expansion intensities of 15.01, 5.26, 9.15, 1.56, 11.88 and 11.91, respectively. The landscape metrics analysis indicated that urban areas were always aggregated and self-connected, while other land use types showed trends of disaggregation and fragmentation. In the process of urban expansion, paddy and natural land use types were commonly transformed to built up area. The results further reveal several common issues in urban land use, e.g., land fragmentation and loss of natural land use types. Finally, the discussion on the relationship between government policy and land use change for these cities shows land reform and attitude toward foreign direct investments played important roles in urban land use change in GMS

A Destriping Algorithm for SDGSAT-1 Nighttime Light Images Based on Anomaly Detection and Spectral Similarity Restoration

Remote sensing nighttime lights (NTLs) offers a unique perspective on human activity, and NTL images are widely used in urbanization monitoring, light pollution, and other human-related research. As one of the payloads of sustainable development science Satellite-1 (SDGSAT-1), the Glimmer Imager (GI) provides a new multi-spectral, high-resolution, global coverage of NTL images. However, during the on-orbit testing of SDGSAT-1, a large number of stripes with bad or corrupted pixels were observed in the L1A GI image, which directly affected the accuracy and availability of data applications. Therefore, we propose a novel destriping algorithm based on anomaly detection and spectral similarity restoration (ADSSR) for the GI image. The ADSSR algorithm mainly consists of three parts: pretreatment, stripe detection, and stripe restoration. In the pretreatment, salt-pepper noise is suppressed by setting a minimum area threshold of the connected components. Then, during stripe detections, the valid pixel number sequence and the total pixel value sequence are analyzed to determine the location of stripes, and the abnormal pixels of each stripe are estimated by a clustering algorithm. Finally, a spectral-similarity-based method is adopted to restore all abnormal pixels of each stripe in the stripe restoration. In this paper, the ADSSR algorithm is compared with three representative destriping algorithms, and the robustness of the ADSSR algorithm is tested on different sizes of GI images. The results show that the ADSSR algorithm performs better than three representative destriping algorithms in terms of visual and quantitative indexes and still maintains outstanding performance and robustness in differently sized GI images

Analysis of influencing factors and a predictive model of small airway dysfunction in adults

Abstract Background Small airway dysfunction (SAD) is a widespread but less typical clinical manifestation of respiratory dysfunction. In lung diseases, SAD can have a higher-than-expected impact on lung function. The aim of this study was to explore risk factors for SAD and to establish a predictive model. Methods We included 1233 patients in the pulmonary function room of TangDu Hospital from June 2021 to December 2021. We divided the subjects into a small airway disorder group and a non-small airway disorder group, and all participants completed a questionnaire. We performed univariate and multivariate analyses to identify the risk factors for SAD. Multivariate logistic regression was performed to construct the nomogram. The performance of the nomogram was assessed and validated by the Area under roc curve (AUC), calibration curves, and Decision curve analysis (DCA). Results One. The risk factors for small airway disorder were advanced age (OR = 7.772,95% CI 2.284–26.443), female sex (OR = 1.545,95% CI 1.103–2.164), family history of respiratory disease (OR = 1.508,95% CI 1.069–2.126), history of occupational dust exposure (OR = 1.723,95% CI 1.177–2.521), history of smoking (OR = 1.732,95% CI 1.231–2.436), history of pet exposure (OR = 1.499,95% CI 1.065–2.110), exposure to O3 (OR = 1.008,95% CI 1.003–1.013), chronic bronchitis (OR = 1.947,95% CI 1.376–2.753), emphysema (OR = 2.190,95% CI 1.355–3.539) and asthma (OR = 7.287,95% CI 3.546–14.973). 2. The AUCs of the nomogram were 0.691 in the training set and 0.716 in the validation set. Both nomograms demonstrated favourable clinical consistency. 3.There was a dose‒response relationship between cigarette smoking and SAD; however, quitting smoking did not reduce the risk of SAD. Conclusion Small airway disorders are associated with age, sex, family history of respiratory disease, occupational dust exposure, smoking history, history of pet exposure, exposure to O3, chronic bronchitis, emphysema, and asthma. The nomogram based on the above results can effectively used in the preliminary risk prediction

A Destriping Algorithm for SDGSAT-1 Nighttime Light Images Based on Anomaly Detection and Spectral Similarity Restoration

Remote sensing nighttime lights (NTLs) offers a unique perspective on human activity, and NTL images are widely used in urbanization monitoring, light pollution, and other human-related research. As one of the payloads of sustainable development science Satellite-1 (SDGSAT-1), the Glimmer Imager (GI) provides a new multi-spectral, high-resolution, global coverage of NTL images. However, during the on-orbit testing of SDGSAT-1, a large number of stripes with bad or corrupted pixels were observed in the L1A GI image, which directly affected the accuracy and availability of data applications. Therefore, we propose a novel destriping algorithm based on anomaly detection and spectral similarity restoration (ADSSR) for the GI image. The ADSSR algorithm mainly consists of three parts: pretreatment, stripe detection, and stripe restoration. In the pretreatment, salt-pepper noise is suppressed by setting a minimum area threshold of the connected components. Then, during stripe detections, the valid pixel number sequence and the total pixel value sequence are analyzed to determine the location of stripes, and the abnormal pixels of each stripe are estimated by a clustering algorithm. Finally, a spectral-similarity-based method is adopted to restore all abnormal pixels of each stripe in the stripe restoration. In this paper, the ADSSR algorithm is compared with three representative destriping algorithms, and the robustness of the ADSSR algorithm is tested on different sizes of GI images. The results show that the ADSSR algorithm performs better than three representative destriping algorithms in terms of visual and quantitative indexes and still maintains outstanding performance and robustness in differently sized GI images

Comparative Proteomic Analysis of Human Lung Adenocarcinoma Cisplatin-resistant Cell Strain A549/CDDP

Background and objective Chemotherapy plays an important role in the comprehensive therapy of lung cancer. However, the drug-resistance often causes the failure of the chemotherapy. The aim of this study is to identify differently expressed protein before and after cisplatin resistance of human lung adenocarcinoma cell A549 by proteomic analysis. Methods Cisplatin-resistant cell strain A549/CDDP was established by combining gradually increasing concentration of cisplatin with large dosage impact. Comparative proteomic analysis of A549 and A549/CDDP were carried out by means of two-dimensional gel electrophoresis. The differentially expressed proteins were detected and identified by MALDI-TOF mass spectrometry. Results Eighty-two differentially expressed proteins were screened by analysis the electrophoretic maps of A549 and A549/CDDP. Six differential proteins were analyzed by peptide mass fingerprinting. Glucose regulating protein 75, ribosomal protein S4, mitochondrial ATP synthase F1 complex beta subunit and immunoglobulin heavy chain variable region were identified. All four differentially expressed proteins were over-expressed in A549/CDDP, whereas low-expressed or no-expressed in A549. Conclusion These differentially expressed proteins give some clues to elucidate the mechanism of lung cancer cell resistant of cisplatin, providing the basis of searching for potential target of chemotherapy of lung cancer

miR-24-3p/KLF8 Signaling Axis Contributes to LUAD Metastasis by Regulating EMT

Reprogramming of the tumor immune microenvironment is a salient feature during metastasis in LUAD. miR-24-3p and KLF8, which are key regulators of the tumor immune microenvironment, had been proved to show metastasis-promoting property in LUAD. However, whether miR-24-3p could regulate LUAD metastasis by targeting KLF8 remains unclear. This study explored the functions and mechanisms of miR-24-3p/KLF8 signaling in advanced LUAD. The expression level of miR-24-3p and KLF8 were tested in LUAD patients, and the corelation of miR-24-3p and KLF8 was evaluated. The interaction of miR-24-3p and KLF8 was demonstrated by luciferase reporter activity assay, in vitro migration and invasion studies, and in vivo metastatic studies. miR-24-3p level was downregulated in LUAD and negatively associated with KLF8 mRNA expression. miR-24-3p controls LUAD metastasis by directly targeting KLF8 and inducing Snail and E-cadherin expressions. Targeting the miR-24-3p/KLF8/EMT axis might be of great therapeutic value to advanced LUAD patients