Prediction of epidermal growth factor receptor (EGFR) mutation status in lung adenocarcinoma patients on computed tomography (CT) images using 3-dimensional (3D) convolutional neural network.

Background: Noninvasively detecting epidermal growth factor receptor (EGFR) mutation status in lung adenocarcinoma patients before targeted therapy remains a challenge. This study aimed to develop a 3-dimensional (3D) convolutional neural network (CNN)-based deep learning model to predict EGFR mutation status using computed tomography (CT) images. Methods: We retrospectively collected 660 patients from 2 large medical centers. The patients were divided into training (n=528) and external test (n=132) sets according to hospital source. The CNN model was trained in a supervised end-to-end manner, and its performance was evaluated using an external test set. To compare the performance of the CNN model, we constructed 1 clinical and 3 radiomics models. Furthermore, we constructed a comprehensive model combining the highest-performing radiomics and CNN models. The receiver operating characteristic (ROC) curves were used as primary measures of performance for each model. Delong test was used to compare performance differences between different models. Results: Compared with the clinical [training set, area under the curve (AUC) =69.6%, 95% confidence interval (CI), 0.661-0.732; test set, AUC =68.4%, 95% CI, 0.609-0.752] and the highest-performing radiomics models (training set, AUC =84.3%, 95% CI, 0.812-0.873; test set, AUC =72.4%, 95% CI, 0.653-0.794) models, the CNN model (training set, AUC =94.3%, 95% CI, 0.920-0.961; test set, AUC =94.7%, 95% CI, 0.894-0.978) had significantly better predictive performance for predicting EGFR mutation status. In addition, compared with the comprehensive model (training set, AUC =95.7%, 95% CI, 0.942-0.971; test set, AUC =87.4%, 95% CI, 0.820-0.924), the CNN model had better stability. Conclusions: The CNN model has excellent performance in non-invasively predicting EGFR mutation status in patients with lung adenocarcinoma and is expected to become an auxiliary tool for clinicians.

[68Ga]Ga-labeled FAPI Conjugated with Gly-Pro Sequence for PET Imaging of Malignant Tumors.

PURPOSE: To improve tumor uptake and prolong tumor retention, a novel fibroblast activation protein (FAP) ligand based on a quinoline-based FAP inhibitor (FAPI) conjugated with the Gly-Pro sequence and 1,4,7,10-tetraazacyclododecane-N,N',N″,N‴-tetraacetic acid (DOTA) was radiolabeled with [68Ga]GaCl3 ([68Ga]Ga-DOTA-GPFAPI-04). Due to the tumor heterogeneity, this study aimed to further validate the preclinical value of [68Ga]Ga-DOTA-GPFAPI-04 PET imaging in tumor mice models with different FAP expression levels. METHODS: [68Ga]Ga-DOTA-GPFAPI-04 was synthesized and its partition coefficient was measured. The stability of [68Ga]Ga-DOTA-GPFAPI-04 was tested in phosphate-buffered saline (PBS, pH 7.4) and fetal bovine serum (FBS). Small animal PET and semi-quantitative studies were conducted in Panc-1 and A549 xenograft tumor mice models compared with [68Ga]Ga-DOTA-FAPI-04. Immunofluorescent and immunohistochemical staining and western blot assay were performed to confirm FAP expression in xenograft tumors. RESULTS: [68Ga]Ga-DOTA-GPFAPI-04 exhibited a radiochemical purity of > 99% and high stability in PBS and FBS. [68Ga]Ga-DOTA-GPFAPI-04 had higher hydrophilic property than [68Ga]Ga-DOTA-FAPI-04 (-4.09 ± 0.05 vs -3.45 ± 0.05). Small animal PET and semi-quantitative analysis revealed Panc-1 xenograft tumor displayed higher tumor uptake of [68Ga]Ga-DOTA-GPFAPI-04 and tumor-to-background ratios compared to A549 xenograft tumor, consistent with the results of immunofluorescence, immunohistochemistry, and western blot. Moreover, [68Ga]Ga-DOTA-GPFAPI-04 demonstrated higher tumor accumulation and longer tumor retention than [68Ga]Ga-DOTA-FAPI-04 in both Panc-1 and A549 xenograft tumors. Furthermore, the FAP-binding specificity of [68Ga]Ga-DOTA-GPFAPI-04 was confirmed in vivo by co-injection of unlabeled GPFAPI-04. CONCLUSION: [68Ga]Ga-DOTA-GPFAPI-04 showed more favorable in vivo tumor imaging and longer tumor retention compared to [68Ga]Ga-DOTA-FAPI-04, which has high potential to be a promising PET probe for detecting FAP-positive tumors.

Diagnostic efficacy of absolute and relative myocardial blood flow of stress dynamic CT myocardial perfusion for detecting myocardial ischemia in patients with hemodynamically significant coronary artery disease.

Introduction: Stress dynamic computed tomography myocardial perfusion imaging (CT-MPI) is an accurate quantitative method for diagnosing myocardial ischemia in coronary artery disease (CAD). However, its clinical application has been limited, partly due to the varied cutoff values for absolute myocardial blood flow (MBFa) and the uncertain value of the relative myocardial blood flow ratio (MBF-ratio). This study aimed to compare the diagnostic efficacy of and investigate the optimal cutoff values for MBFa and the MBF-ratio in CT-MPI for diagnosing myocardial ischemia in patients with hemodynamically significant CAD. Methods: Patients with suspected or known hemodynamically significant CAD who underwent CT-MPI + CT angiography and invasive coronary angiography (ICA)/fractional flow reserve (FFR) between October 2020 and December 2023 were retrospectively evaluated. ICA ≥80% or FFR ≤0.8 were set as the diagnostic standards for functional ischemia. The patients and vessels were categorized into ischemic and non-ischemic groups, and differences in MBFa and the MBF-ratio were compared between the groups. The area under the curve (AUC) and optimal cutoff values were calculated. Diagnostic efficacy parameters, such as sensitivity, specificity, and accuracy, were also compared. In addition, a consistency test was performed. Results: A total of 46 patients (mean age: 65.37 ± 8.25 years; 120 vessels) were evaluated. Hemodynamically significant stenosis was detected in 30/46 patients (48%) and 81/120 vessels (67.5%). The MBFa and MBF-ratio values were significantly lower in the ischemic than in the non-ischemic group; in the per-vessel analysis, the MBFa values were 73 vs. 128 (P < 0.001) and the MBF-ratio values were 0.781 vs. 0.856 (P < 0.001), respectively. The optimal cutoff values for MBFa and the MBF-ratio were 117.71 and 0.67, respectively. MBFa demonstrated a sensitivity, specificity, accuracy, AUC, positive predictive value, negative predictive value, and kappa value of 97.44%, 74.07%, 81.66%, 0.936 [95% confidence interval (CI): 0.876-0.973, P < 0.001], 63.33%, 98.36%, and 0.631 (95% CI: 0.500-0.762), respectively. The corresponding values for the MBF-ratio were 92.31%, 85.19%, 87.5%, 0.962 (95% CI: 0.911-0.989, P < 0.001), 75%, 95.83%, and 0.731 (95% CI: 0.606-0.857, P < 0.001), with no significant difference (P = 0.1225). Conclusion: Both MBFa and the MBF-ratio exhibit excellent diagnostic performance for myocardial ischemia in patients with hemodynamically significant CAD. The MBF-ratio is more robust than MBFa for interpreting CT-MPI findings in clinical practice, which is useful for radiologists and clinicians implementing CT-MPI.

Construction and validation of a clinical differentiation model between peripheral lung cancer and solitary pulmonary tuberculosis.

OBJECTIVE: To establish and validate a clinical model for differentiating peripheral lung cancer (PLC) from solitary pulmonary tuberculosis (SP-TB) based on clinical and imaging features. MATERIALS AND METHODS: Retrospectively, 183 patients (100 PLC, 83 SP-TB) in our hospital were randomly divided into a training group and an internal validation group (ratio 7:3), and 100 patients (50 PLC, 50 SP-TB) in Sichuan Provincial People's Hospital were identified as an external validation group. The collected qualitative and quantitative variables were used to determine the independent feature variables for distinguishing between PLC and SP-TB through univariate logistic regression, multivariate logistic regression. Then, traditional logistic regression models and machine learning algorithm models (decision tree, random forest, xgboost, support vector machine, k-nearest neighbors, light gradient boosting machine) were established using the independent feature variables. The model with the highest AUC value in the internal validation group was used for subsequent analysis. The receiver operating characteristic curve (ROC), calibration curve, and decision curves analysis (DCA) were used to assess the model's discrimination, calibration, and clinical usefulness. RESULT: Age, smoking history, maximum diameter of lesion, lobulation, spiculation, calcification, and vascular convergence sign were independent characteristic variables to differentiate PLC from SP-TB. The logistic regression model had the highest AUC value of 0.878 for the internal validation group, based on which a quantitative visualization nomogram was constructed to discriminate the two diseases. The area under the ROC curve (AUC) of the model in the training, internal validation, and external validation groups were 0.915 (95 % CI: 0.866-0.965), 0.878 (95 % CI: 0.784-0.971), and 0.912 (95 % CI: 0.855-0.969), respectively, and the calibration curves fitted well. Decision curves analysis (DCA) confirmed the good clinical benefit of the model. CONCLUSION: The model constructed based on clinical and imaging features can accurately differentiate between PLC and SP-TB, providing potential value for developing reasonable clinical plans.

Insights into comparative genomics, structural features, and phylogenetic relationship of species from Eurasian Aster and its related genera (Asteraceae: Astereae) based on complete chloroplast genome.

Aster L. is an economically and phylogenetically important genus in the tribe Astereae. Here, the complete plastomes of the eight Aster species were assembled and characterized using next-generation sequencing datasets. The results indicated the complete plastomes of Aster had a quadripartite structure. These genomes were 152,045-152,729 bp in length and contained 132-133 genes, including 87 protein-coding genes, 37-38 tRNA genes, and eight rRNA genes. Expansion or contraction of inverted repeat regions and forward, palindromic, complement, and reverse repeats were detected in the eight Aster species. Additionally, our analyses showed the richest type of simple sequence repeats was A/T mononucleotides, and 14 highly variable regions were discovered by analyzing the border regions, sequence divergence, and hotspots. Phylogenetic analyses indicated that 27 species in Astereae were clustered into six clades, i.e., A to D, North American, and outgroup clades, and supported that the genera Heteropappus, Kalimeris, and Heteroplexis are nested within Aster. The results indicated the clades B to D might be considered as genera. Divergence time estimate showed the clades A, B, C, and D diverged at 23.15 Mya, 15.13 Mya, 24.29 Mya, and 21.66 Mya, respectively. These results shed light on the phylogenetic relationships of Aster and provided new information on species identification of Aster and its related genera.

Diagnostic efficacy of [68Ga]Ga-DOTA-GPFAPI-04 in patients with solid tumors in a head-to-head comparison with [18F]F-FDG: results from a prospective clinical study.

PURPOSE: To identify the biodistribution and diagnostic performance of a novel fibroblast activation protein (FAP) targeted positron emission tomography (PET) tracer, [68Ga]Ga-DOTA-GPFAPI-04, in patients with solid tumors in a head-to-head comparison with [18F]F-FDG. METHODS: Twenty-six patients histologically proven with cancers of nasopharyngeal (n = 5), esophagus (n = 5), gastro-esophagus (n = 1), stomach (n = 7), liver (n = 3), and colorectum (n = 5) were recruited for [68Ga]Ga-DOTA-GPFAPI-04 and [18F]F-FDG PET/CT scans on consecutive days. The primary endpoint was the diagnostic efficacy, with the histological diagnosis and the follow-up results selected as the gold standard. The secondary endpoint was the background uptake pattern. Two experienced nuclear medicine physicians who were blinded to the gold standard results while having essential awareness of the clinical context reviewed the images and labeled lesions by consensus for subsequent software-assisted lesion segmentation. Additionally, background organs were automatically segmented, assisted by artificial intelligence. Volume, mean, and maximum standard uptake values (SUVmean and SUVmax) of all segmentations were recorded. P < 0.05 was deemed as statistically significant. RESULTS: Significant glandular uptake of [68Ga]Ga-DOTA-GPFAPI-04 was detected in the thyroid, pancreas, and submandibular glands, while moderate uptake was observed in the parotid glands. The myocardium and myometrium exhibited 2-3 times higher uptake of the radiotracer than that of the background levels in blood and liver. A total of 349 targeted lesions, consisting of 324 malignancies and 25 benign lesions, were segmented. [68Ga]Ga-DOTA-GPFAPI-04 is more sensitive than [18F]F-FDG, especially for abdominopelvic dissemination (1.000 vs. 0.475, P < 0.001). Interestingly, [18F]F-FDG demonstrated higher sensitivity for lung metastasis compared to [68Ga]Ga-DOTA-GPFAPI-04 (0.845 vs. 0.682, P = 0.003). The high glandular uptake made it difficult to delineate lesions in close proximity and masked two metastatic lesions in these organs. CONCLUSION: Despite prominent glandular uptake, [68Ga]Ga-DOTA-GPFAPI-04 demonstrates favorable diagnostic performance. It is a promising probe scaffold for further development of FAP-targeted tumor theranostic agents.

A highly resolved nuclear phylogeny uncovers strong phylogenetic conservatism and correlated evolution of fruit color and size in Solanum L.

Mutualisms between plants and fruit-eating animals were key to the radiation of angiosperms. Still, phylogenetic uncertainties limit our understanding of fleshy-fruit evolution, as in the case of Solanum, a genus with remarkable fleshy-fruit diversity, but with unresolved phylogenetic relationships. We used 1786 nuclear genes from 247 species, including 122 newly generated transcriptomes/genomes, to reconstruct the Solanum phylogeny and examine the tempo and mode of the evolution of fruit color and size. Our analysis resolved the backbone phylogeny of Solanum, providing high support for its clades. Our results pushed back the origin of Solanum to 53.1 million years ago (Ma), with most major clades diverging between 35 and 27 Ma. Evolution of Solanum fruit color and size revealed high levels of trait conservatism, where medium-sized berries that remain green when ripe are the likely ancestral form. Our analyses revealed that fruit size and color are evolutionary correlated, where dull-colored fruits are two times larger than black/purple and red fruits. We conclude that the strong phylogenetic conservatism shown in the color and size of Solanum fruits could limit the influences of fruit-eating animals on fleshy-fruit evolution. Our findings highlight the importance of phylogenetic constraints on the diversification of fleshy-fruit functional traits.

A new species, Aster yaoshanensis (Asteracae, Astereae), from Guangxi (China), based on morphology and molecular phylogenetic data.

Aster yaoshanensis sp. nov., a new species of the family Asteraceae is here described and illustrated. The species is presently known only from rock crevices of mountain valleys in Dayaoshan National Nature Reserve, Guangxi autonomous region, China. Phylogenetic analyses based on ITS sequences and complete plastome data have shown that this new species is a member of genus Aster with high support. Morphologically, it mostly resembles A. jishouensis, but it can be easily distinguished from the latter by bract indumentum (glabrous except margin ciliate vs. villous especially on veins abaxially, glabrous adaxially) and color (green vs. purple), shorter corolla (3.2-3.5 mm vs. 4.5-5.3 mm), bract stalk (obvious, ca.1.2 mm vs. sessile), and different distribution (Guangxi vs. Hunan). The detailed description, distribution map, and photos are provided. This study further elucidates the species identification, phylogeny and characteristic evolution of Aster.

A rationally designed nuclei-targeting FAPI 04-based molecular probe with enhanced tumor uptake for PET/CT and fluorescence imaging.

PURPOSE: Fibroblast activation protein inhibitor (FAPI) -based probes have been widely studied in the diagnosis of various malignant tumors with positron emission tomography/computed tomography (PET/CT). However, current imaging studies of FAPI-based probes face challenges in rapid clearance rate and potential false-negative results. Furthermore, FAPI has been rarely explored in optical imaging. Considering this, further modifications are imperative to improve the properties of FAPI-based probes to address existing limitations and broaden their application scenarios. In this study, we rationally introduced methylene blue (MB) to FAPIs, thereby imparting nuclei-targeting and fluorescence imaging capabilities to the probes. Furthermore, we evaluated the added value of FAPI-based fluorescence imaging to traditional PET/CT, exploring the potential application of FAPI-based probes in intraoperative fluorescence imaging. METHODS: A new FAPI-based probe, namely NOTA-FAPI-MB, was designed for both PET/CT and fluorescence imaging by conjugation of MB. The targeting efficacy of the probe was evaluated on fibroblast activation protein (FAP)-transfected cell line and human primary cancer-associated fibroblasts (CAFs). Subsequently, PET/CT and fluorescence imaging were conducted on tumor-bearing mice. The tumor detection and boundary delineation were assessed by fluorescence imaging of tissues from hepatocellular carcinoma (HCC) patients. RESULTS: NOTA-FAPI-MB demonstrated exceptional targeting ability towards FAP-transfected cells and CAFs in comparison to NOTA-FAPI. This benefit arises from the cationic methylene blue (MB) affinity for anionic nucleic acids. PET/CT imaging of tumor-bearing mice revealed significantly higher tumor uptake of [18F]F-NOTA-FAPI-MB (standard uptake value of 2.20 ± 0.31) compared to [18F]F-FDG (standard uptake value of 1.66 ± 0.14). In vivo fluorescence imaging indicated prolonged retention at the tumor site, with retention lasting up to 24 h. In addition, the fluorescent probes enabled more precise lesion detection and tumor margin delineation than clinically used indocyanine green (ICG), achieving a 100.0% (6/6) tumor-positive rate for NOTA-FAPI-MB while 33.3% (2/6) for ICG. These findings highlighted the potential of NOTA-FAPI-MB in guiding intraoperative surgical procedures. CONCLUSIONS: The NOTA-FAPI-MB was successfully synthesized, in which FAPI and MB simultaneously contributed to the targeting effect. Notably, the nuclear delivery mechanism of the probes improved intracellular retention time and targeting efficacy, broadening the imaging time window for fluorescence imaging. In vivo PET/CT demonstrated favorable performance of NOTA-FAPI-MB compared to [18F]F-FDG. This study highlights the significance of fluorescence imaging as an adjunct technique to PET/CT. Furthermore, the encouraging results obtained from the imaging of human HCC tissues hold promise for the potential application of NOTA-FAPI-MB in intraoperative fluorescent surgery guidance within clinical settings.

Boron nanosheets boosting solar thermal water evaporation.

Hydrogel-based solar vapour generators (SVGs) are promising for wastewater treatment and desalination. The performance of SVG systems is governed by solar thermal conversion and water management. Progress has been made in achieving high energy conversion efficiency, but the water evaporation rates are still unsatisfactory under 1 sun irradiation. This study introduced novel two-dimensional (2D) boron nanosheets as additives into hydrogel-based SVGs. The resulting SVGs exhibit an outstanding evaporation rate of 4.03 kg m-2 h-1 under 1 sun irradiation. This significant improvement is attributed to the 2D boron nanosheets, which leads to the formation of a higher content of intermediate water and reduced water evaporation enthalpy to 845.11 kJ kg-1. The SVGs into which boron nanosheets were incorporated also showed high salt resistance and durability, demonstrating their great potential for desalination applications.

Nuclear phylogenomics of Asteraceae with increased sampling provides new insights into convergent morphological and molecular evolution.

Convergent morphological evolution is widespread in flowering plants, and understanding this phenomenon relies on well-resolved phylogenies. Nuclear phylogenetic reconstruction using transcriptome datasets has been successful in various angiosperm groups, but it is limited to taxa with available fresh materials. Asteraceae, which are one of the two largest angiosperm families and are important for both ecosystems and human livelihood, show multiple examples of convergent evolution. Nuclear Asteraceae phylogenies have resolved relationships among most subfamilies and many tribes, but many phylogenetic and evolutionary questions regarding subtribes and genera remain, owing to limited sampling. Here, we increased the sampling for Asteraceae phylogenetic reconstruction using transcriptomes and genome-skimming datasets and produced nuclear phylogenetic trees with 706 species representing two-thirds of recognized subtribes. Ancestral character reconstruction supports multiple convergent evolutionary events in Asteraceae, with gains and losses of bilateral floral symmetry correlated with diversification of some subfamilies and smaller groups, respectively. Presence of the calyx-related pappus may have been especially important for the success of some subtribes and genera. Molecular evolutionary analyses support the likely contribution of duplications of MADS-box and TCP floral regulatory genes to innovations in floral morphology, including capitulum inflorescences and bilaterally symmetric flowers, potentially promoting the diversification of Asteraceae. Subsequent divergences and reductions in CYC2 gene expression are related to the gain and loss of zygomorphic flowers. This phylogenomic work with greater taxon sampling through inclusion of genome-skimming datasets reveals the feasibility of expanded evolutionary analyses using DNA samples for understanding convergent evolution.

Nuclear phylogenomics of angiosperms and insights into their relationships and evolution.

Angiosperms (flowering plants) are by far the most diverse land plant group with over 300,000 species. The sudden appearance of diverse angiosperms in the fossil record was referred to by Darwin as the "abominable mystery," hence contributing to the heightened interest in angiosperm evolution. Angiosperms display wide ranges of morphological, physiological, and ecological characters, some of which have probably influenced their species richness. The evolutionary analyses of these characteristics help to address questions of angiosperm diversification and require well resolved phylogeny. Following the great successes of phylogenetic analyses using plastid sequences, dozens to thousands of nuclear genes from next-generation sequencing have been used in angiosperm phylogenomic analyses, providing well resolved phylogenies and new insights into the evolution of angiosperms. In this review we focus on recent nuclear phylogenomic analyses of large angiosperm clades, orders, families, and subdivisions of some families and provide a summarized Nuclear Phylogenetic Tree of Angiosperm Families. The newly established nuclear phylogenetic relationships are highlighted and compared with previous phylogenetic results. The sequenced genomes of Amborella, Nymphaea, Chloranthus, Ceratophyllum, and species of monocots, Magnoliids, and basal eudicots, have facilitated the phylogenomics of relationships among five major angiosperms clades. All but one of the 64 angiosperm orders were included in nuclear phylogenomics with well resolved relationships except the placements of several orders. Most families have been included with robust and highly supported placements, especially for relationships within several large and important orders and families. Additionally, we examine the divergence time estimation and biogeographic analyses of angiosperm on the basis of the nuclear phylogenomic frameworks and discuss the differences compared with previous analyses. Furthermore, we discuss the implications of nuclear phylogenomic analyses on ancestral reconstruction of morphological, physiological, and ecological characters of angiosperm groups, limitations of current nuclear phylogenomic studies, and the taxa that require future attention.

Using Multi-phase CT Radiomics Features to Predict EGFR Mutation Status in Lung Adenocarcinoma Patients.

RATIONALE AND OBJECTIVES: This study aimed to non-invasively predict epidermal growth factor receptor (EGFR) mutation status in patients with lung adenocarcinoma using multi-phase computed tomography (CT) radiomics features. MATERIALS AND METHODS: A total of 424 patients with lung adenocarcinoma were recruited from two hospitals who underwent preoperative non-enhanced CT (NE-CT) and enhanced CT (including arterial phase CT [AP-CT], and venous phase CT [VP-CT]). Patients were divided into training (n = 297) and external validation (n = 127) cohorts according to hospital. Radiomics features were extracted from the NE-CT, AP-CT, and VP-CT images, respectively. The Wilcoxon test, correlation analysis, and simulated annealing were used for feature screening. A clinical model and eight radiomics models were established. Furthermore, a clinical-radiomics model was constructed by incorporating multi-phase CT features and clinical risk factors. Receiver operating characteristic curves were used to evaluate the predictive performance of the models. RESULTS: The predictive performance of multi-phase CT radiomics model (AUC of 0.925 [95% CI, 0.879-0.971] in the validation cohort) was higher than that of NE-CT, AP-CT, VP-CT, and clinical models (AUCs of 0.860 [95% CI,0.794-0.927], 0.792 [95% CI, 0.713-0.871], 0.753 [95% CI, 0.669-0.838], and 0.706 [95% CI, 0.620-0.791] in the validation cohort, respectively) (all P < 0.05). The predictive performance of the clinical-radiomics model (AUC of 0.927 [95% CI, 0.882-0.971] in the validation cohort) was comparable to that of multi-phase CT radiomics model (P > 0.05). CONCLUSION: Our multi-phase CT radiomics model showed good performance in identifying the EGFR mutation status in patients with lung adenocarcinoma, which may assist personalized treatment decisions.