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.

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.

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.

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.

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 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.

Kinetic modeling and parametric imaging of 18 F-PSMA-11: An evaluation based on total-body dynamic positron emission tomography scans.

BACKGROUND: The prostate-specific membrane antigen (PSMA) targeted positron-emitting tomography (PET) tracers are increasingly used in clinical practice, with novel tracers constantly being developed. Recently, 18 F-PSMA-11 has been gaining growing interest for several merits; however, direct in vivo visualization of its kinetic features in humans remains lacking. PURPOSE: To visualize the kinetic features of 18 F-PSMA-11 in healthy subjects and patients with prostate cancer derived from the total-body dynamic PET scans. METHODS: A total of 8 healthy volunteers (7 males; 1 female) and 3 patients with prostate cancer underwent total-body PET/CT imaging at 1 and 2 h post injection (p.i.) of 18 F-PSMA-11, of which 7 healthy subjects and 3 patients underwent total-body dynamic PET scans lasting 30 min. Reversible two-tissue compartments (2TC) and Patlak models were fitted based on the voxel-based time activity curves (TACs), with the parametric images generated subsequently. Additionally, semi-automated segmentation of multiple organs was performed in the dynamic images to measure the SUVmean at different time points and in the parametric images to estimate the mean value of the kinetic parameters of these organs. RESULTS: 18 F-PSMA-11 showed quick accumulation within prostate cancer, as early as 45 s after tracer injection. It was rapidly cleared from blood circulation and predominantly excreted through the urinary system. High and rapid radiotracer accumulation was observed in the liver, spleen, lacrimal glands, and salivary glands, whereas gradual accumulation was observed in the skeleton. Prostate cancer tissue is visualized in all parametric images, and best seen in DV and Patlak Ki images. Patlak Ki showed a good correlation with 2TC Ki values (r = 0.858, p < 0.05) but less noise than 2TC images. A scanning time point of 30-35 min p.i. was then suggested for satisfactory tumor to background ratio. CONCLUSION: Prostate cancer tissue is visible in most parametric images, and is better shown by Patlak Ki and 2TC DV images. Patlak Ki is consistent with, and thus is preferred over, 2TC Ki images for substantially quicker calculation. Based on the dynamic imaging analysis, a shorter uptake time (30-35 min) might be preferred for a better balance of tumor to background ratio.

Synthesis of Silver Nanoparticles from Silver Closo-Dodecaborate Film for Enhanced Hydrogen Evolution.

The icosahedral closo dodecaborate cluster [B12 H12 ]2- is gaining increasing interest due to its unique properties including the ease of functionalization, 3D aromaticity, and formation of metal salts with high ion conductivity. In this work, simple and effective preparation of silver closo dodecaborte (Ag2 B12 H12 ) films is reported by an electrochemical route. The size of the Ag2 B12 H12 particles in the films can be tuned from nanometers to micrometers by varying the electrochemical parameters. Ag nanoclusters with controllable sizes are successfully generated via electrochemical reduction reactions or thermal anneal of the Ag2 B12 H12 films. When tested for hydrogen evolution reaction (HER) in an acidic solution, the as-prepared Ag nanoparticles deliver a current density of 10 mA cm-2 at 376 mV overpotential. This research sheds light on a new synthesis of [B12 H12 ]2- based thin films, the generation of metal nano-powders, and their application in HER or other applications.

Computed Tomography Manifestations in Patients with Rifampin Primary Drug-Resistant Tuberculosis in an Infectious Disease Hospital in the Yi Autonomous Prefecture, China.

Purpose: This study aimed to investigate clinical features and computed tomography (CT) manifestations of rifampicin primary drug-resistant pulmonary tuberculosis in Liangshan Yi Autonomous Prefecture. Patients and Methods: A total of 100 inpatients with confirmed primary rifampicin-resistant pulmonary tuberculosis were recruited from January 2020 to December 2022 at an infectious disease hospital located in the Liangshan Yi Autonomous Prefecture. Additionally, 100 inpatients with confirmed drug-susceptible pulmonary tuberculosis during the same period were matched to the rifampicin-resistant group based on gender, age, and ethnicity. The clinical characteristics of the two groups were recorded separately. Furthermore, the CT manifestations in these patients were independently analyzed by three radiologists. Results: The results showed that comorbid diabetes mellitus was more prevalent in the drug-resistant tuberculosis (DR-TB) group than in the drug-susceptible tuberculosis (DS-TB) group (9% vs 0%, p=0.0032). In terms of imaging presentation, DR-TB patients exhibited a higher frequency of calcifications (55% vs 35.00%, p=0.0068), greater median number of cavities (5 vs 2, p=0.0027), and larger maximum cavity diameter (52.08±25.55 mm vs 42.72±17.48 mm, p=0.0097). Additionally, bilateral involvement was more common in DR-TB patients at the site of the lesion (89% vs 76%, p=0.0246), with a higher prevalence in the right middle (82% vs 68%, p=0.0332), right lower (82% vs 68%, p=0.0332), left upper (91% vs 77%, p=0.0113), and left lower lobes (92% vs 66%, p<0.0001). Conversely, the involvement of only one lobe was less frequent in patients with DR-TB than in those with DS-TB (4% vs 13%, p=0.0398), whereas the involvement of all five lobes was more common (68% vs 51%, p=0.0209). Conclusion: Patients with DR-TB exhibit a higher prevalence of severe imaging manifestations, highlighting the importance of CT in the early detection and diagnosis of DR-TB.

Phylogenomics insights into gene evolution, rapid species diversification, and morphological innovation of the apple tribe (Maleae, Rosaceae).

Maleae is one of the most widespread tribes of Rosaceae and includes several important fruit crops and ornamental plants. We used nuclear genes from 62 transcriptomes/genomes, including 26 newly generated transcriptomes, to reconstruct a well-supported phylogeny and study the evolution of fruit and leaf morphology and the possible effect of whole genome duplication (WGD). Our phylogeny recovered 11 well-supported clades and supported the monophyly of most genera (except Malus, Sorbus, and Pourthiaea) with at least two sampled species. A WGD was located to the most recent common ancestor (MRCA) of Maleae and dated to c. 54 million years ago (Ma) near the Early Eocene Climatic Optimum, supporting Gillenieae (x = 9) being a parental lineage of Maleae (x = 17) and including duplicate regulatory genes related to the origin of the fleshy pome fruit. Whole genome duplication-derived paralogs that are retained in specific lineages but lost in others are predicted to function in development, metabolism, and other processes. An upshift of diversification and innovations of fruit and leaf morphologies occurred at the MRCA of the Malinae subtribe, coinciding with the Eocene-Oligocene transition (c. 34 Ma), following a lag from the time of the WGD event. Our results provide new insights into the Maleae phylogeny, its rapid diversification, and morphological and molecular evolution.

A radiomics model enables prediction venous sinus invasion in meningioma.

OBJECTIVE: Preoperative prediction of meningioma venous sinus invasion would facilitate the selection of surgical approaches and predicting the prognosis. To predict venous sinus invasion in meningiomas, we used radiomic signatures to construct a model based on preoperative contrast-enhanced T1-weighted (T1C) and T2-weighted (T2) magnetic resonance imaging. METHODS: In total, 599 patients with pathologically confirmed meningioma were retrospectively enrolled. For each patient enrolled in this study, 1595 radiomic signatures were extracted from T1C and T2 image sequences. Pearson correlation analysis and recursive feature elimination were used to select the most relevant signatures extracted from different image sequences, and logistic regression algorithms were used to build a radiomic model for risk prediction of meningioma sinus invasion. Furthermore, a nomogram was built by incorporating clinical characteristics and radiomic signatures, and a decision curve analysis was used to evaluate the clinical utility of the nomogram. RESULTS: Twenty radiomic signatures that were significantly related to venous sinus invasion were screened from 3190 radiomic signatures. Venous sinus invasion was associated with tumor position, and the clinicoradiomic model that incorporated the above characteristics (20 radiomic signatures and tumor position) had the best discriminating ability. The areas under the curve for the training and validation cohorts were 0.857 (95% confidence interval [CI], 0.824-0.890) and 0.824 (95% CI, 0.752-0.8976), respectively. INTERPRETATION: The clinicoradiomic model had good predictive performance for venous sinus invasion in meningioma, which can aid in devising surgical strategies and predicting prognosis.

Computed tomography findings in patients with pulmonary tuberculosis and diabetes at an infectious disease hospital in China: a retrospective cross-sectional study.

BACKGROUND: This study aimed to investigate the relationship between active pulmonary tuberculosis (TB) and type 2 diabetes mellitus (T2DM) by analysing the clinical features and computed tomography (CT) findings of patients with active pulmonary TB and comorbid T2DM (TB-DM) in the LiangShan Yi regions. METHODS: We collected data from 154 hospitalised patients with TB-DM initially confirmed at an infectious disease hospital in the Liangshan Yi Autonomous Prefecture between 1 and 2019, and 31 December 2021. These were matched by sex and age ± 3 years to 145 hospitalised patients with initially confirmed pulmonary TB without comorbid T2DM (TB-NDM) over the same period. The clinical characteristics of the two groups were analysed separately. Three group-blinded radiologists independently analysed the CT findings and classified them into mild-to-moderate and severe groups. Severe chest CT lesion refers to a lesion that is less diffused or moderately dense and either exceeds the total volume of one lung, a high-density fused lesion greater than one-third of the volume of one lung, or a cavitary lesion with a maximum diameter ≥ 4 cm. RESULTS: No significant differences were observed in the presentation of clinical features. Regarding the severity of chest CT manifestation, patients with TB-DM had significantly more severe TB than those with TB-NDM (89.61% vs. 68.97%, P < 0.0001). Regarding CT findings, patients with TB-DM had higher proportions of consolidation (79.22% vs. 52.41%, P < 0.0001), cavitary lesions (85.06% vs. 59.31%, P < 0.0001), bronchiectasis (71.43% vs. 31.03%, P < 0.0001), exudative lesions (88.96% vs. 68.28%, P < 0.0001), and fibrous lesions (93.51% vs. 68.97%, P < 0.0001) than patients with TB-NDM. In conclusion, patients with TB-DM have more severe pulmonary TB CT findings than those without. There were no significant differences in the distribution of lesions in the lung lobes between TB-DM and TB-NDM patients. CONCLUSIONS: Among patients hospitalised with pulmonary TB, those with T2DM had more severe findings on chest CT than those without T2DM. However, the clinical presentation was not significantly different.

Construction of prediction model for KRAS mutation status of colorectal cancer based on CT radiomics.

BACKGROUND: In this study, we used computed tomography (CT)-based radiomics signatures to predict the mutation status of KRAS in patients with colorectal cancer (CRC) and to identify the phase of radiomics signature with the most robust and high performance from triphasic enhanced CT. METHODS: This study involved 447 patients who underwent KRAS mutation testing and preoperative triphasic enhanced CT. They were categorized into training (n = 313) and validation cohorts (n = 134) in a 7:3 ratio. Radiomics features were extracted using triphasic enhanced CT imaging. The Boruta algorithm was used to retain the features closely associated with KRAS mutations. The Random Forest (RF) algorithm was used to develop radiomics, clinical, and combined clinical-radiomics models for KRAS mutations. The receiver operating characteristic curve, calibration curve, and decision curve were used to evaluate the predictive performance and clinical usefulness of each model. RESULTS: Age, CEA level, and clinical T stage were independent predictors of KRAS mutation status. After rigorous feature screening, four arterial phase (AP), three venous phase (VP), and seven delayed phase (DP) radiomics features were retained as the final signatures for predicting KRAS mutations. The DP models showed superior predictive performance compared to AP or VP models. The clinical-radiomics fusion model showed excellent performance, with an AUC, sensitivity, and specificity of 0.772, 0.792, and 0.646 in the training cohort, and 0.755, 0.724, and 0.684 in the validation cohort, respectively. The decision curve showed that the clinical-radiomics fusion model had more clinical practicality than the single clinical or radiomics model in predicting KRAS mutation status. CONCLUSION: The clinical-radiomics fusion model, which combines the clinical and DP radiomics model, has the best predictive performance for predicting the mutation status of KRAS in CRC, and the constructed model has been effectively verified by an internal validation cohort.

Phylogenomics and morphological evolution of the mega-diverse genus Artemisia (Asteraceae: Anthemideae): implications for its circumscription and infrageneric taxonomy.

BACKGROUND AND AIMS: Artemisia is a mega-diverse genus consisting of ~400 species. Despite its medicinal importance and ecological significance, a well-resolved phylogeny for global Artemisia, a natural generic delimitation and infrageneric taxonomy remain missing, owing to the obstructions from limited taxon sampling and insufficient information on DNA markers. Its morphological characters, such as capitulum, life form and leaf, show marked variations and are widely used in its infrageneric taxonomy. However, their evolution within Artemisia is poorly understood. Here, we aimed to reconstruct a well-resolved phylogeny for global Artemisia via a phylogenomic approach, to infer the evolutionary patterns of its key morphological characters and to update its circumscription and infrageneric taxonomy. METHODS: We sampled 228 species (258 samples) of Artemisia and its allies from both fresh and herbarium collections, covering all the subgenera and its main geographical areas, and conducted a phylogenomic analysis based on nuclear single nucleotide polymorphisms (SNPs) obtained from genome skimming data. Based on the phylogenetic framework, we inferred the possible evolutionary patterns of six key morphological characters widely used in its previous taxonomy. KEY RESULTS: The genus Kaschgaria was revealed to be nested in Artemisia with strong support. A well-resolved phylogeny of Artemisia consisting of eight highly supported clades was recovered, two of which were identified for the first time. Most of the previously recognized subgenera were not supported as monophyletic. Evolutionary inferences based on the six morphological characters showed that different states of these characters originated independently more than once. CONCLUSIONS: The circumscription of Artemisia is enlarged to include the genus Kaschgaria. The morphological characters traditionally used for the infrageneric taxonomy of Artemisia do not match the new phylogenetic tree. They experienced a more complex evolutionary history than previously thought. We propose a revised infrageneric taxonomy of the newly circumscribed Artemisia, with eight recognized subgenera to accommodate the new results.

Comprehensive phylogenetic analyses of Orchidaceae using nuclear genes and evolutionary insights into epiphytism.

Orchidaceae (with >28,000 orchid species) are one of the two largest plant families, with economically and ecologically important species, and occupy global and diverse niches with primary distribution in rainforests. Among orchids, 70% grow on other plants as epiphytes; epiphytes contribute up to ~50% of the plant diversity in rainforests and provide food and shelter for diverse animals and microbes, thereby contributing to the health of these ecosystems. Orchids account for over two-thirds of vascular epiphytes and provide an excellent model for studying evolution of epiphytism. Extensive phylogenetic studies of Orchidaceae and subgroups have ;been crucial for understanding relationships among many orchid lineages, although some uncertainties remain. For example, in the largest subfamily Epidendroideae with nearly all epiphytic orchids, relationships among some tribes and many subtribes are still controversial, hampering evolutionary analyses of epiphytism. Here we obtained 1,450 low-copy nuclear genes from 610 orchid species, including 431 with newly generated transcriptomes, and used them for the reconstruction of robust Orchidaceae phylogenetic trees with highly supported placements of tribes and subtribes. We also provide generally well-supported phylogenetic placements of 131 genera and 437 species that were not sampled by previous plastid and nuclear phylogenomic studies. Molecular clock analyses estimated the Orchidaceae origin at ~132 million years ago (Ma) and divergences of most subtribes from 52 to 29 Ma. Character reconstruction supports at least 14 parallel origins of epiphytism; one such origin was placed at the most recent common ancestor of ~95% of epiphytic orchids and linked to modern rainforests. Ten occurrences of rapid increase in the diversification rate were detected within Epidendroideae near and after the K-Pg boundary, contributing to ~80% of the Orchidaceae diversity. This study provides a robust and the largest family-wide Orchidaceae nuclear phylogenetic tree thus far and new insights into the evolution of epiphytism in vascular plants.

The value of dual-energy spectral CT in differentiating solitary pulmonary tuberculosis and solitary lung adenocarcinoma.

Background: To explore the value of dual-energy spectral CT in distinguishing solitary pulmonary tuberculosis (SP-TB) from solitary lung adenocarcinoma (S-LUAD). Methods: A total of 246 patients confirmed SP-TB (n = 86) or S-LUAD (n = 160) were retrospectively included. Spectral CT parameters include CT40keV value, CT70keV value, iodine concentration (IC), water concentration (WC), effective atomic number (Zeff), and spectral curve slope (λ70keV). Data were measured during the arterial phase (AP) and venous phase (VP). Chi-square test was used to compare categorical variables, Wilcoxon rank-sum test was used to compare continuous variables, and a two-sample t-test was used to compare spectral CT parameters. ROC curves were used to calculate diagnostic efficiency. Results: There were significant differences in spectral CT quantitative parameters (including CT40keV value [all P< 0.001] , CT70keV value [all P< 0.001], λ70keV [P< 0.001, and P = 0.027], Zeff [P =0.015, and P = 0.001], and IC [P =0.002, and P = 0.028]) between the two groups during the AP and VP. However, WC (P = 0.930, and P = 0.823) was not statistically different between the two groups. The ROC curve analysis showed that the AUC in the AP and VP was 90.9% (95% CI, 0.873-0.945) and 83.4% (95% CI, 0.780-0.887), respectively. The highest diagnostic performance (AUC, 97.6%; 95% CI, 0.961-0.991) was achieved when all spectral CT parameters were combined with clinical variables. Conclusion: Dual-energy spectral CT has a significant value in distinguishing SP-TB from S-LUAD.

Machine-learning classifiers based on non-enhanced computed tomography radiomics to differentiate anterior mediastinal cysts from thymomas and low-risk from high-risk thymomas: A multi-center study.

Background: This study aimed to investigate the diagnostic value of machine-learning (ML) models with multiple classifiers based on non-enhanced CT Radiomics features for differentiating anterior mediastinal cysts (AMCs) from thymomas, and high-risk from low risk thymomas. Methods: In total, 201 patients with AMCs and thymomas from three centers were included and divided into two groups: AMCs vs. thymomas, and high-risk vs low-risk thymomas. A radiomics model (RM) was built with 73 radiomics features that were extracted from the three-dimensional images of each patient. A combined model (CM) was built with clinical features and subjective CT finding features combined with radiomics features. For the RM and CM in each group, five selection methods were adopted to select suitable features for the classifier, and seven ML classifiers were employed to build discriminative models. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of each combination. Results: Several classifiers combined with suitable selection methods demonstrated good diagnostic performance with areas under the curves (AUCs) of 0.876 and 0.922 for the RM and CM in group 1 and 0.747 and 0.783 for the RM and CM in group 2, respectively. The combination of support vector machine (SVM) as the feature-selection method and Gradient Boosting Decision Tree (GBDT) as the classification algorithm represented the best comprehensive discriminative ability in both group. Comparatively, assessments by radiologists achieved a middle AUCs of 0.656 and 0.626 in the two groups, which were lower than the AUCs of the RM and CM. Most CMs exhibited higher AUC value compared to RMs in both groups, among them only a few CMs demonstrated better performance with significant difference in group 1. Conclusion: Our ML models demonstrated good performance for differentiation of AMCs from thymomas and low-risk from high-risk thymomas. ML based on non-enhanced CT radiomics may serve as a novel preoperative tool.

Nomogram based on MRI can preoperatively predict brain invasion in meningioma.

Predicting brain invasion preoperatively should help to guide surgical decision-making and aid the prediction of meningioma grading and prognosis. However, only a few imaging features have been identified to aid prediction. This study aimed to develop and validate an MRI-based nomogram to predict brain invasion by meningioma. In this retrospective study, 658 patients were examined via routine MRI before undergoing surgery and were diagnosed with meningioma by histopathology. Least absolute shrinkage and selection operator (LASSO) regularization was used to determine the optimal combination of clinical characteristics and MRI features for predicting brain invasion by meningiomas. Logistic regression and receiver operating characteristic (ROC) curve analyses were used to determine the discriminatory ability. Furthermore, a nomogram was constructed using the optimal MRI features, and decision curve analysis was used to validate the clinical usefulness of the nomogram. Eighty-one patients with brain invasion and 577 patients without invasion were enrolled. According to LASSO regularization, tumour shape, tumour boundary, peritumoral oedema, and maximum diameter were independent predictors of brain invasion. The model showed good discriminatory ability for predicting brain invasion in meningiomas, with an AUC of 0.905 (95% CI, 0.871-0.940) vs 0.898 (95% CI, 0.849-0.947) and sensitivity of 93.0% vs 92.6% in the training vs validation cohorts. Our predictive model based on MRI features showed good performance and high sensitivity for predicting the risk of brain invasion in meningiomas and can be applied in the clinical setting.