"Turn-on" and pinhole-free ultrathin core-shell Au@SiO2 nanoparticle-based metal-enhanced fluorescent (MEF) chemodosimeter for Hg2.

This study reports a metal-enhanced fluorescence chemodosimeter for highly sensitive detection of Hg2+ ions. Silica-coated Au nanoparticles (Au@SiO2 NPs) with a pinhole-free 4-5 nm shell were synthesized and functionalized with a monolayer of turn-on fluorescent probes. Compared to other organic fluorescent probes suffering from poor biocompatibility and detection limits, this design of a monolayer of turn-on fluorescent probes immobilized on the Au@SiO2 NPs with a pinhole-free 4-5 nm shell avoids fluorescence quenching and allows the fluorescent probe within the field of the inner Au NPs to experience metal-enhanced fluorescence. With this design, the chemodosimeter permits fluorescence emission in the presence of Hg2+ ions, because they trigger the ring-opening reaction of the fluorescent probe immobilized on the Au@SiO2 NPs. Additionally, the fluorescent probe is distanced by the thin SiO2 shell from directly attaching to the metallic Au NPs, which not only avoids fluorescence quenching but allows the fluorescent probe within the long-ranged field of the inner Au NPs to experience metal-enhanced fluorescence. As a result, the detection limit for the chemodosimeter can reach up to 5.0 × 10-11 M, nearly two orders of magnitude higher than that achieved for the free fluorescent probe. We also demonstrate the acquisition of images of Hg2+ in HTC116 cells and zebrafish using a simple fluorescence confocal imaging technique. The fluorescence response results for HTC116 cells and zebrafish show that the probes can permeate into cells and organisms. Considering the availability of the many organic fluorescent probes that have been designed, the current designed metal-enhanced fluorescence chemodosimeter holds great potential for fluorescence detection of diverse species and fluorescence imaging.

Effect of screening colonoscopy frequency on colorectal cancer mortality in patients with a family history of colorectal cancer.

BACKGROUND: Colorectal cancer is a common malignant tumor in China, and its incidence in the elderly is increasing annually. Inflammatory bowel disease is a group of chronic non-specific intestinal inflammatory diseases, including ulcerative colitis and Crohn's disease. AIM: To assess the effect of screening colonoscopy frequency on colorectal cancer mortality. METHODS: We included the clinicopathological and follow-up data of patients with colorectal cancer who underwent laparoscopic colectomy or open colectomy at our Gastrointestinal Department between January 2019 and December 2022. Surgical indicators, oncological indicators, and survival rates were compared between the groups. The results of 104 patients who met the above criteria were extracted from the database (laparoscopic colectomy group = 63, open colectomy group = 41), and there were no statistically significant differences in the baseline data or follow-up time between the two groups. RESULTS: Intraoperative blood loss, time to first ambulation, and time to first fluid intake were significantly lower in the laparoscopic colectomy group than in the open colectomy group. The differences in overall mortality, tumor-related mortality, and recurrence rates between the two groups were not statistically significant, and survival analysis showed that the differences in the cumulative overall survival, tumor-related survival, and cumulative recurrence-free rates between the two groups were not statistically significant. CONCLUSION: In elderly patients with colorectal cancer, laparoscopic colectomy has better short-term outcomes than open colectomy, and laparoscopic colectomy has superior long-term survival outcomes compared with open colectomy.

Predicting environmental impacts of smallholder wheat production by coupling life cycle assessment and machine learning.

Wheat grain production is a vital component of the food supply produced by smallholder farms but faces significant threats from climate change. This study evaluated eight environmental impacts of wheat production using life cycle assessment based on survey data from 274 households, then built random forest models with 21 input features to contrast the environmental responses of different farming practices across three shared socioeconomic pathways (SSPs), spanning from 2024 to 2100. The results indicate significant environmental repercussions. Compared to the baseline period of 2018-2020, a similar upward trend in environmental impacts is observed, showing an average annual growth rate of 5.88 % (ranging from 0.45 to 18.56 %) under the sustainable pathway (SSP119) scenario; 5.90 % (ranging from 1.00 to 18.15 %) for the intermediate development pathway (SSP245); and 6.22 % (ranging from 1.16 to 17.74 %) under the rapid economic development pathway (SSP585). Variation in rainfall is identified as the primary driving factor of the increased environmental impacts, whereas its relationship with rising temperatures is not significant. The results suggest adopting farming practices as a vital strategy for smallholder farms to mitigate climate change impacts. Emphasizing appropriate fertilizer application and straw recycling can significantly reduce the environmental footprint of wheat production. Standardized fertilization could reduce the environmental impact index by 11.10 to 47.83 %, while straw recycling might decrease respiratory inorganics and photochemical oxidant formation potential by over 40 %. Combined, these approaches could lower the impact index by 12.31 to 63.38 %. The findings highlight the importance of adopting enhanced farming practices within smallholder farming systems in the context of climate change. SPOTLIGHTS.

Automated pancreatic segmentation and fat fraction evaluation based on a self-supervised transfer learning network.

Accurate segmentation of the pancreas from abdominal computed tomography (CT) images is challenging but essential for the diagnosis and treatment of pancreatic disorders such as tumours and diabetes. In this study, a dataset with 229 sets of high-resolution CT images was generated and annotated. We proposed a novel 3D segmentation model named nnTransfer (nonisomorphic transfer learning) net, which employs generative model structure for self-supervision to facilitate the network's learning of image attributes from unlabelled data. The effectiveness for pancreas segmentation of nnTransfer was assessed using the Hausdorff distance (HD) and Dice similarity coefficient (DSC) on the dataset. Additionally, a histogram analysis with local thresholding was used to achieve automated whole-volume measurement of pancreatic fat (fat volume fraction, FVF). The proposed technique performed admirably on the dataset, with DSC: 0.937 ± 0.019 and HD: 2.655 ± 1.479. The mean pancreas volume and FVF of the pancreas were 91.95 ± 23.90 cm3 and 12.67 % ± 9.84 %, respectively. The nnTransfer functioned flawlessly and autonomously, facilitating the use of the FVF to evaluate pancreatic disease, particularly in patients with diabetes.

A signature based on neutrophil extracellular trap-related genes for the assessment of prognosis, immunoinfiltration, mutation and therapeutic response in hepatocellular carcinoma.

BACKGROUND: Liver cancer is a highly lethal and aggressive form of cancer that poses a significant threat to patient survival. Within this category, liver hepatocellular carcinoma (LIHC) represents the most common subtype of liver cancer. Despite decades of research and treatment, the overall survival rate for LIHC has not significantly improved. Improved models are necessary to differentiate high-risk cases and predict possible treatment options for LIHC patients. Recent studies have identified a set of genes associated with neutrophil extracellular traps (NETs) that may contribute to tumor growth and metastasis; however, their prognostic value in LIHC has yet to be established. This study aims to construct a prognostic signature based on a set of NET-related genes (NRGs) for patients diagnosed with LIHC. METHODS: The transcriptomic data and clinical information concerning LIHC patients were procured from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium LIHC (ICLIHC) databases, respectively. To determine the NRG subtypes, the k-means algorithm was employed, along with consensus clustering. The aforementioned analysis aided the construction of a prognostic signature utilizing the last absolute shrinkage and selection operator Cox analysis. To validate the prognostic model, an external dataset, receiver operating characteristic curve, and principal component analysis were utilized. Moreover, the immune microenvironment and the proportion of immune cells between high- and low-risk cases were scrutinized by ESTIMATE and CIBERSORT algorithms. Finally, gene set enrichment analysis was executed to investigate the potential mechanism of NRGs in the pathogenesis and prognosis of LIHC. RESULTS: Two molecular subtypes of LIHC were identified based on the expression patterns of differentially expressed NRGs (DE-NRGs). The two subtypes demonstrated significant differences in survival rates and immune cell expression levels. The study results demonstrated the role of NRGs in antigen presentation, which led to the promotion of tumor immune escape. A risk model was developed and validated with strong overall survival prediction ability. The model, comprising 34 NRGs, showed a strong ability to predict prognosis. CONCLUSION: We built a dependable prognostic signature based on NRGs for LIHC. We identified that NRGs could have a significant interaction in LIHC's immune microenvironment and therapeutic response. This finding offers insight into the molecular mechanisms and targeted therapy for LIHC.

Preoperative Grading of Rectal Cancer with Multiple DWI Models, DWI-Derived Biological Markers, and Machine Learning Classifiers.

Background: this study aimed to utilize various diffusion-weighted imaging (DWI) techniques, including mono-exponential DWI, intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), for the preoperative grading of rectal cancer. Methods: 85 patients with rectal cancer were enrolled in this study. Mann-Whitney U tests or independent Student's t-tests were conducted to identify DWI-derived parameters that exhibited significant differences. Spearman or Pearson correlation tests were performed to assess the relationships among different DWI-derived biological markers. Subsequently, four machine learning classifier-based models were trained using various DWI-derived parameters as input features. Finally, diagnostic performance was evaluated using ROC analysis with 5-fold cross-validation. Results: With the exception of the pseudo-diffusion coefficient (Dp), IVIM-derived and DKI-derived parameters all demonstrated significant differences between low-grade and high-grade rectal cancer. The logistic regression-based machine learning classifier yielded the most favorable diagnostic efficacy (AUC: 0.902, 95% Confidence Interval: 0.754-1.000; Specificity: 0.856; Sensitivity: 0.925; Youden Index: 0.781). Conclusions: utilizing multiple DWI-derived biological markers in conjunction with a strategy employing multiple machine learning classifiers proves valuable for the noninvasive grading of rectal cancer.

Computed tomographic imaging features to differentiate gastric schwannomas from gastrointestinal stromal tumours: a matched case-control study.

To investigate clinical data and computed tomographic (CT) imaging features in differentiating gastric schwannomas (GSs) from gastric stromal tumours (GISTs) in matched patients, 31 patients with GSs were matched with 62 patients with GISTs (1:2) in sex, age, and tumour site. The clinical and imaging data were analysed. A significant (P < 0.05) difference was found in the tumour margin, enhancement pattern, growth pattern, and LD values between the 31 patients with GSs and 62 matched patients with GISTs. The GS lesions were mostly (93.5%) well defined while only 61.3% GIST lesions were well defined.The GS lesions were significantly (P = 0.036) smaller than the GIST lesions, with the LD ranging 1.5-7.4 (mean 3.67 cm) cm for the GSs and 1.0-15.30 (mean 5.09) cm for GIST lesions. The GS lesions were more significantly (P = 0.001) homogeneously enhanced (83.9% vs. 41.9%) than the GIST lesions. The GS lesions were mainly of the mixed growth pattern both within and outside the gastric wall (74.2% vs. 22.6%, P < 0.05) compared with that of GISTs. No metastasis or invasion of adjacent organs was present in any of the GS lesions, however, 1.6% of GISTs experienced metastasis and 3.2% of GISTs presented with invasion of adjacent organs. Heterogeneous enhancement and mixed growth pattern were two significant (P < 0.05) independent factors for distinguishing GS from GIST lesions. In conclusion: GS and GIST lesions may have significantly different features for differentiation in lesion margin, heterogeneous enhancement, mixed growth pattern, and longest lesion diameter, especially heterogeneous enhancement and mixed growth pattern.

Diagnostic Accuracy of CT-Guided Percutaneous Pulmonary Biopsy for Distinguishing Benign and Malignant Solitary Pulmonary Nodules.

Background: Isolated pulmonary nodules (SPNs) are small, circular lesions within lung tissue, often challenging to diagnose due to their size and lack of typical imaging features. Timely diagnosis is crucial for treatment decisions. However, the difficulty in qualitative diagnosis necessitates clinical biopsies. Objective: This study aimed to assess the diagnostic accuracy of CT-guided percutaneous lung biopsy for SPNs and identify potential risk factors for malignancy. Methods: We conducted a retrospective analysis of 112 patients with SPNs who underwent CT-guided core needle biopsy (CT-CNB) between June 2020 and June 2022. Histological and cytological results were obtained for all patients, and clinical data and imaging characteristics were compared between benign and malignant SPN groups. Binary logistic regression was used to analyze risk factors for malignancy, and complications were observed. Results: Cytological and histological specimens were successfully obtained for all patients. The cohort consisted of 43 patients with benign SPNs and 69 with malignant SPNs. Among the malignant SPN group, 67 cases were confirmed via CT-CNB and 2 through surgery, resulting in a sensitivity of 97.10% and specificity of 100.00%. The malignant nodules comprised 45 adenocarcinomas, 14 squamous cell carcinomas, 8 metastatic tumors, and 2 small cell carcinomas. Notably, 2 initially diagnosed as malignant cases were found to have chronic inflammation on preoperative biopsy but revealed adenocarcinoma and squamous cell carcinoma post-surgery. The benign nodules encompassed 20 granulomatous inflammation cases, 15 chronic inflammation, 3 fungal granulomas, 2 hamartomas, and 1 fibrous tissue. Cytological smears exhibited a sensitivity of 81.3% and a specificity of 100.0% for malignancy. Significantly, age ≥60, elevated tumor markers, and specific imaging signs (burr, foliation, pleural pull) were identified as risk factors for malignant SPNs using Binary Logistic regression (all P < .05). Conclusions: CT-guided percutaneous lung biopsy demonstrates excellent diagnostic efficacy and safety for distinguishing benign and malignant SPNs.

Kawasaki disease with peritonsillar abscess as the first symptom: A case report.

BACKGROUND: Kawasaki disease (KD), also known as mucocutaneous lymph node syndrome, is an acute, self-limiting vasculitis of unknown aetiology that mainly involves the medium and small arteries and can lead to serious cardiovascular complications, with a 25% incidence of coronary artery aneurysms. Periton-Sillar abscesses are a rare symptom of KD and is easily misdiagnosed at its early stages. CASE SUMMARY: A 5-year-old boy who presented to a community hospital with a 3-d fever, difficulty in opening his mouth, and neck pain and was originally treated for throat infection without improvement. On the basis of laboratory tests, ultrasound of submandibular and superficial lymph nodes and computed tomography of the neck, the clinician diagnosed the periamygdala abscess and sepsis that did not resolve after antibiotic therapy. On the fifth day of admission, the child developed conjunctival congestion, prune tongue, perianal congestion and desquamation, and slightly stiff and swollen bunions on both feet. A diagnosis of KD was reached with complete remission after intravenous immunoglobulin treatment. CONCLUSION: Children with neck pain, lymph node enlargement, or airway obstruction as the main manifestations are poorly treated with intravenous broad-spectrum antibiotics. Clinicians should not rush invasive operations such as neck puncture, incision, and drainage and should be alert for KD when it cannot be explained by deep neck space infection and early treatment with aspirin combined with gammaglobulin.

Insights into Stereoselectivity Switch in Michael Addition-Initiated Tandem Mannich Cyclizations and Their Extension from Enamines to Vinyl Ethers.

Both cis- and trans- tetracyclic spiroindolines are the core of many important biologically active indole alkaloids, but the divergent synthesis of these important motifs is largely hampered by the limited stereoselectivity control. A facile stereoinversion protocol is reported here in Michael addition-initiated tandem Mannich cyclizations for constructing tetracyclic spiroindolines, providing an easy access to two diastereoisomeric cores of monoterpene indole alkaloids with high selectivity. The mechanistic studies including in situ NMR experiments, control experiments, and DFT calculations reveal that the reaction undergoes a unique retro-Mannich/re-Mannich rearrangement including a C-C bond cleavage that is very rare for a saturated six-membered carbocycle. Insights into the stereoinversion process have been uncovered, and the major effects were determined to be the electronic properties of N-protecting groups of the indole with the aid of Lewis acid catalysts. By understanding these insights, the stereoselectivity switching strategy is also smoothly applied from enamine substrates to vinyl ether substrates, which are enriched greatly for the divergent synthesis and stereocontrol of monoterpene indole alkaloids. The current reaction also proves to be very practical and was successfully applied to the gram-scale total synthesis of strychnine and deethylibophyllidine in short routes.

Sophoricoside attenuates autoimmune­mediated liver injury through the regulation of oxidative stress and the NF­κB signaling pathway.

The prevalence of autoimmune hepatitis (AIH) is increasing, yet specific pharmacotherapies remain to be explored. The present study aimed to investigate the effects of sophoricoside (SOP), a bioactive component of medical herbs, on AIH and to elucidate the underlying mechanisms. Bioinformatic approaches were used to predict the potential targets and underlying regulatory mechanisms of SOP on AIH. The effects of SOP on AIH were evaluated by determining the expression levels of inflammatory cytokines, histological liver injury and hepatic fibrosis in an improved chronic cytochrome P450 2D6 (CYP2D6)­AIH mouse model and in a model of concanavalin­A (ConA)­induced acute immune­mediated liver injury. The antioxidant activity of SOP was detected in in vivo and in vitro experiments. The selected signal targeted by SOP in AIH was further confirmed using western blot analysis and immunofluorescence staining. The results of bioinformatic analysis revealed that the targets of SOP in AIH were related to oxidative stress and the NF­κB gene set. The NF­κB transcription factor family is a key player that controls both innate and adaptive immunity. The activation of the NF­κB signaling pathway is often associated with autoimmune disorders. In the animal experiments, SOP attenuated CYP2D6/ConA­induced AIH, as evidenced by a significant reduction in the levels of hepatic enzymes in serum, inflammatory cytokine expression and histological lesions in the liver. The oxidative response in AIH was also significantly inhibited by SOP, as evidenced by a decrease in the levels of hepatic malondialdehyde, and elevations in the total antioxidant capacity and glutathione peroxidase levels. The results of the in vivo and in vitro experiments revealed that SOP significantly reduced the enhanced expression and nuclear translocation of phosphorylated p65 NF­κB in the livers of mice with AIH and in lipopolysaccharide­stimulated AML12 cells. On the whole, the present study demonstrates the protective role of SOP in AIH, which may be mediated by limiting the oxidative response and the activation of the NF­κB signaling pathway in hepatocytes.

Automatic right ventricular segmentation for cine cardiac magnetic resonance images based on a new deep atlas network.

BACKGROUND: The high morbidity and mortality of heart disease present a significant threat to human health. The development of methods for the quick and accurate diagnosis of heart diseases, enabling their effective treatment, has become a key issue of concern. Right ventricular (RV) segmentation from cine cardiac magnetic resonance (CMR) images plays a significant role in evaluating cardiac function for clinical diagnosis and prognosis. However, due to the complex structure of the RV, traditional segmentation methods are ineffective for RV segmentation. PURPOSE: In this paper, we propose a new deep atlas network to improve the learning efficiency and segmentation accuracy of a deep learning network by integrating multi-atlas. METHODS: First, a dense multi-scale U-net (DMU-net) is presented to acquire transformation parameters from atlas images to target images. The transformation parameters map the atlas image labels to the target image labels. Second, using a spatial transformation layer, the atlas images are deformed based on these parameters. Finally, the network is optimized by backpropagation with two loss functions where the mean squared error function (MSE) is used to measure the similarity of the input images and transformed images. Further, the Dice metric (DM) is used to quantify the overlap between the predicted contours and the ground truth. In our experiments, 15 datasets are used in testing, and 20 cine CMR images are selected as atlas. RESULTS: The mean values and standard deviations for the DM and Hausdorff distance are 0.871 and 4.67 mm, 0.104 and 2.528 mm, respectively. The correlation coefficients of endo-diastolic volume, endo-systolic volume, ejection fraction, and stroke volume are 0.984, 0.926, 0.980, and 0.991, respectively, and the mean differences between all of the mentioned parameters are 3.2, -1.7, 0.02, and 4.9, respectively. Most of these differences are within the allowable range of 95%, indicating that the results are acceptable and show good consistency. The segmentation results obtained in this method are compared with those obtained by other methods that provide satisfactory performance. The other methods provide better segmentation effects at the base, but either no segmentation or the wrong segmentation at the top, which demonstrate that the deep atlas network can improve top-area segmentation accuracy. CONCLUSION: Our results indicate that the proposed method can achieve better segmentation results than the previous methods, with both high relevance and consistency, and has the potential for clinical application.

Influence factors and nomogram for volume reduction rate in benign thyroid nodule after thermal ablation.

BACKGROUND: Thermal ablation is a minimally invasive and safe treatment for benign thyroid nodules, and the volume reduction rate (VRR) of nodule is a primary clinical efficacy indicator. PURPOSE: To screen factors influencing VRR in benign thyroid nodules after thermal ablation and establish a predictable nomogram. MATERIALS AND METHODS: This retrospective study enrolled 238 patients with benign thyroid nodules who underwent thermal ablation between January 2016 and September 2021. Clinical information and imaging characteristics in routine ultrasound (US) and contrast-enhanced ultrasound (CEUS) were evaluated. Factors influencing the VRR ≥75% were screened using multivariate logistic regression, and a predictable nomogram was established. RESULTS: At the 12-month follow-up, the VRR of nodule was 77.0 ± 20.6% (18.4-100%). Seven factors influencing the VRR ≥75.0% were identified: echogenicity, component, calcification, enhancement degree, enhancement defect, ring enhancement, and energy of ablation. A nomogram was established based on the above factors, and the predictive ability of the model was confirmed by internal validation with 1000 bootstrap repetitions. The area under the receiver-operating characteristic curve (AUC) of the model was 0.926, and the calibration curve and decision curve analysis (DCA) revealed that this model demonstrated predictive ability. CONCLUSION: Seven factors influencing VRR in benign thyroid nodules after thermal ablation were screened out in the present study and used to establish a nomogram to predict the probability of VRR ≥75% at the 12-month follow-up. It would be beneficial to make personalized medical decisions to trigger thermal ablation in patients with benign thyroid nodules.

Computed tomography features of gastric leiomyoma versus gastric stromal tumor: a case-control study with propensity score matching.

OBJECTIVE: To differentiate gastric leiomyomas (GLs) and gastric stromal tumors (GSTs) based on preoperative enhanced computed tomography characteristics. METHODS: Twenty-six pathologically confirmed GLs were propensity score-matched to 26 GSTs in a 1:1 ratio based on sex, age, tumor site, and tumor size. Tumor shape and contour, mucosal ulceration, growth pattern, enhancement pattern and degree, longest diameter, and longest diameter/vertical diameter ratio were compared between the groups. Hemorrhage, calcification, peripheral invasion, and distant metastasis were also included in the regression analysis for differentiation of the two tumors. RESULTS: Mucosal ulceration was significantly more frequent in GSTs than GLs. The enhancement degree of GSTs was significantly higher than that of GLs in the arterial and portal venous phases. Using enhancement degrees of 18 HU and 23 HU in the arterial phase and venous phase as cutoff values, respectively, we found that an enhancement degree of <18 HU in the arterial phase was an independent influential factor for diagnosis of GLs. No significant differences were found in other morphological characteristics. GLs did not metastasize or invade adjacent tissues. CONCLUSION: A low enhancement degree in GLs is the most valuable quantitative feature for differentiating these two similar tumors.

A comparison of the use of contrast media with different iodine concentrations for enhanced computed tomography.

Objective: In this study, we compared the enhancement of blood vessels and liver parenchyma on enhanced computed tomography (CT) of the upper abdomen with two concentrations of contrast media (400 and 300 mg I/mL) based on similar iodine delivery rate (IDR) of 0.88 and 0.9 g I/s and iodine load of 450 mg I/kg. Methods: We randomly assigned 160 patients into two groups: iomeprol 400 mg I/mL (A group) and iohexol 300 mg I/mL (B group). The CT attenuation values of the main anatomical structures in the two groups with different scanning phases were measured and the image quality of the two groups was analyzed and compared. The peak pressure and local discomfort (including fever and pain) during contrast medium injection were recorded. Results: The mean attenuation value of the abdominal aorta was 313.6 ± 29.6 in the A group and 322.4 ± 30.1 in the B group during the late arterial phase (p = 0.8). Meanwhile, the mean enhancement values of the portal vein were 176.2 ± 19.3 and 165.9 ± 24.5 in the A and B groups, respectively, during the portal venous phase (p = 0.6). The mean CT values of liver parenchyma were 117.1 ± 15.3 and 108.8 ± 18.7 in the A and B groups, respectively, during the portal venous phase (p = 0.9). There was no statistical difference in image quality, peak injection pressure (psi), and local discomfort between the two groups (p > 0.05). Conclusion: When a similar IDR and the same iodine load are used, CT images with different concentrations of contrast media have the same subjective and objective quality, and can meet the diagnostic needs.

Radiomics-based analysis of CT imaging for the preoperative prediction of invasiveness in pure ground-glass nodule lung adenocarcinomas.

OBJECTIVE: The purpose of the study is to investigate the performance of radiomics-based analysis in prediction of pure ground-glass nodule (pGGN) lung adenocarcinomas invasiveness using thin-section computed tomography images. METHODS: A total of 382 patients surgically resected single pGGN and pathologically confirmed were enrolled in the retrospective study. The pGGN cases were divided into two groups: the noninvasive group and the invasive adenocarcinoma (IAC) group. 330 patients were randomly assigned to the training and testing cohorts with a ratio of 7:3 (245 noninvasive lesions, 85 IAC lesions), while 52 patients (30 noninvasive lesions, 22 IAC lesions) were assigned to the external validation cohort. A model, radiomics model, and combined clinical-radiographic-radiomic model were built using the LASSO and multivariate backward stepwise regression analysis on the basis of the selected and radiomics features. The area under the curve (AUC) and decision curve analysis (DCA) were used to evaluate and compare the model performance for invasiveness discrimination among the three cohorts. RESULTS: Three clinical-radiographic features (including age, gender and the mean CT value) and three radiomics features were selected for model building. The combined model and radiomics model performed better than the clinical-radiographic model. The AUCs of the combined model in the training, testing, and validation cohorts were 0.856, 0.859, and 0.765, respectively. The DCA demonstrated the radiomics signatures incorporating clinical-radiographic feature was clinically useful in predicting pGGN invasiveness. CONCLUSIONS: The proposed radiomics-based analysis incorporating the clinical-radiographic feature could accurately predict pGGN invasiveness, providing a noninvasive biomarker for the individualized and precise medical treatment of patients.

Left ventricular myocardial motion tracking in cardiac cine magnetic resonance images based on a biomechanical model.

BACKGROUND: Cardiac cine magnetic resonance (CCMR) imaging plays an important role in the clinical cardiovascular disease (CVD) examination and evaluation. OBJECTIVE: To accurately reconstruct the displacement field and describe the motion of the left ventricular myocardium (LVM), this study proposes and tests a new approach for tracking myocardial motion of the left ventricle based on a biomechanical model. METHODS: CCMR imaging data acquired from 103 patients are enrolled, including two simulated and 101 clinical data. A non-rigid image registration method with a combination of a thin-plate spline function and random sample consensus is used to recover the observed displacement field of LVM. Next, a biomechanical model and a material matrix are introduced to solve the dense displacement field of LVM using a finite element framework. Then, the tracking precision and error of results for the two groups are analyzed. RESULTS: Displacement results of the simulated data show correlation coefficient≥0.876 and mean square error≤0.159, while displacement results of the clinical data show Dice≥0.97 and mean contour distance≤0.464. Additionally, the strain results show correlation coefficient≥0.717. CONCLUSIONS: This study demonstrates that the proposed new method enables to accurately track the motion of the LVM and evaluate strain, which has clinical auxiliary value in the diagnosis of CVD.

Probabilistic integration of transcriptome-wide association studies and colocalization analysis identifies key molecular pathways of complex traits.

Integrative genetic association methods have shown great promise in post-GWAS (genome-wide association study) analyses, in which one of the most challenging tasks is identifying putative causal genes and uncovering molecular mechanisms of complex traits. Recent studies suggest that prevailing computational approaches, including transcriptome-wide association studies (TWASs) and colocalization analysis, are individually imperfect, but their joint usage can yield robust and powerful inference results. This paper presents INTACT, a computational framework to integrate probabilistic evidence from these distinct types of analyses and implicate putative causal genes. This procedure is flexible and can work with a wide range of existing integrative analysis approaches. It has the unique ability to quantify the uncertainty of implicated genes, enabling rigorous control of false-positive discoveries. Taking advantage of this highly desirable feature, we further propose an efficient algorithm, INTACT-GSE, for gene set enrichment analysis based on the integrated probabilistic evidence. We examine the proposed computational methods and illustrate their improved performance over the existing approaches through simulation studies. We apply the proposed methods to analyze the multi-tissue eQTL data from the GTEx project and eight large-scale complex- and molecular-trait GWAS datasets from multiple consortia and the UK Biobank. Overall, we find that the proposed methods markedly improve the existing putative gene implication methods and are particularly advantageous in evaluating and identifying key gene sets and biological pathways underlying complex traits.

Statistics in everyone's backyard: An impact study via citation network analysis.

Statistical methodologies are indispensable in data-driven scientific discoveries. In this paper, we make the first effort to understand the impact of recent statistical innovations on other scientific fields. By collecting comprehensive bibliometric data from the Web of Science database for selected statistical journals, we investigate the citation trends and compositions of citing fields over time, and we find increasing citation diversity. Furthermore, in a new setting, we apply a local clustering technique involving personalized PageRank with graph conductance for size selection to find the most relevant statistical innovation for a given external topic in other fields. Through a number of case studies, we show that the results from our citation data analysis align well with our knowledge and intuition about these external topics. Overall, we have found that the statistical theory and methods recently invented by the statistics community have made increasing impact on other scientific fields.

Rapid Construction of Enantioenriched Benzofurochromanes by SaBOX/Copper(II) Catalyzed Enantioselective [3 + 2] Annulation of γ-Chromenes with Quinones.

A rapid construction of enantioenriched benzofurochromanes was developed by SaBOX/copper(II) catalyzed enantioselective [3 + 2] annulation of γ-chromenes with quinones. This process takes advantage of the simple starting materials and a highly efficient chiral SaBOX/copper(II) catalyst system, leading to a variety of benzofurochromanes in up to 96% yield with up to 97% ee.