Evaluation of machine learning models on protein level inference from prioritized RNA features.

The parallel measurement of transcriptome and proteome revealed unmatched profiles. Since proteomic analysis is more expensive and challenging than transcriptomic analysis, the question of how to use messenger RNA (mRNA) expression data to predict protein level is extremely important. Here, we comprehensively evaluated 13 machine learning models on inferring protein expression levels using RNA expression profile. A total of 20 proteogenomic datasets from three mainstream proteomic platforms with >2500 samples of 13 human tissues were collected for model evaluation. Our results highlighted that the appropriate feature selection methods combined with classical machine learning models could achieve excellent predictive performance. The voting ensemble model outperformed other candidate models across datasets. Adding the mRNA proxy model to the regression model further improved the prediction performance. The dataset and gene characteristics could affect the prediction performance. Finally, we applied the model to the brain transcriptome of cerebral cortex regions to infer the protein profile for better understanding the functional characteristics of the brain regions. This benchmarking work not only provides useful hints on the inherent correlation between transcriptome and proteome, but also has practical value of the transcriptome-based prediction of protein expression levels.

Efficient Catalytic Elimination of Chlorobenzene Based on the Water Vapor-Promoting Effect within Mn-Based Catalysts: Activity Enhancement and Polychlorinated Byproduct Inhibition.

Achieving no or low polychlorinated byproduct selectivity is essential for the chlorinated volatile organic compounds (CVOCs) degradation, and the positive roles of water vapor may contribute to this goal. Herein, the oxidation behaviors of chlorobenzene over typical Mn-based catalysts (MnO2 and acid-modified MnO2) under dry and humid conditions were fully explored. The results showed that the presence of water vapor significantly facilitates the deep mineralization of chlorobenzene and restrains the formation of Cl2 and dichlorobenzene. This remarkable water vapor-promoting effect was conferred by the MnO2 substrate, which could suitably synergize with the postconstructed acidic sites, leading to good activity, stability, and desirable product distribution of acid-modified MnO2 catalysts under humid conditions. A series of experiments including isotope-traced (D2O and H218O) CB-TPO provided complete insights into the direct involvement of water molecules in chlorobenzene oxidation reaction and attributed the root cause of the water vapor-promoting effect to the proton-rich environment and highly reactive water-source oxygen species rather than to the commonly assumed cleaning effect or hydrogen proton transfer processes (generation of active OOH). This work demonstrates the application potential of Mn-based catalysts in CVOCs elimination under practical application conditions (containing water vapor) and provides the guidance for the development of superior industrial catalysts.

Parenting Desire Among Sexual Minority Women in China: From the Stigma Perspective.

In China, women who are childless or have children outside of heterosexual marriage are generally stigmatized. Consequently, Chinese sexual minority women are challenged for their willingness to have children. This study explored how multiple (structural-interpersonal-individual) levels of sexual minority stigma are related to parenting desire among Chinese sexual minority women. Furthermore, it examined the mediation mechanism of individual stigma and the moderation effect of outness to one's family in the link between structural/interpersonal stigma and parenting desire. Participants (265 lesbian and 193 bisexual women) completed online measures of structural stigma (adherence to Confucianism), interpersonal stigma (discrimination events), individual stigma (internalized homophobia and rejection sensitivity), outness to one's family, and parenting desire. Lesbian women reported lower structural and individual stigma and parenting desire levels than bisexual women. Sexual minority women's high adherence to Confucianism, internalized homophobia, and rejection sensitivity were positively associated with their increased parenting desires. Notably, adherence to Confucianism and discrimination events were associated with parenting desire through internalized homophobia, but not rejection sensitivity; moreover, outness to one's family buffered the direct link between adherence to Confucianism and parenting desire and strengthened the direct link between discrimination events and internalized homophobia and the indirect link between discrimination events and parenting desire. This study contributes to a robust understanding of how sexual minority stigma is connected to parenting desire among sexual minority women in Chinese sociocultural contexts, providing cultural-specific evidence to support theories of stigma and minority stress.

A novel phage carrying capsule depolymerase effectively relieves pneumonia caused by multidrug-resistant Klebsiella aerogenes.

BACKGROUND: Klebsiella aerogenes can cause ventilator-associated pneumonia by forming biofilms, and it is frequently associated with multidrug resistance. Phages are good antibiotic alternatives with unique advantages. There has been a lack of phage therapeutic explorations, kinetic studies, and interaction mechanism research targeting K. aerogenes. METHODS: Plaque assay, transmission electron microscopy and whole-genome sequencing were used to determine the biology, morphology, and genomic characteristics of the phage. A mouse pneumonia model was constructed by intratracheal/endobronchial delivery of K. aerogenes to assess the therapeutic effect of phage in vivo. Bioinformatics analysis and a prokaryotic protein expression system were used to predict and identify a novel capsule depolymerase. Confocal laser scanning microscopy, Galleria mellonella larvae infection models and other experiments were performed to clarify the function of the capsule depolymerase. RESULTS: A novel lytic phage (pK4-26) was isolated from hospital sewage. It was typical of the Podoviridae family and exhibited serotype specificity, high lytic activity, and high environmental adaptability. The whole genome is 40,234 bp in length and contains 49 coding domain sequences. Genomic data show that the phage does not carry antibiotic resistance, virulence, or lysogenic genes. The phage effectively lysed K. aerogenes in vivo, reducing mortality and alleviating pneumonia without promoting obvious side effects. A novel phage-derived depolymerase was predicted and proven to be able to digest the capsule, remove biofilms, reduce bacterial virulence, and sensitize the bacteria to serum killing. CONCLUSIONS: The phage pK4-26 is a good antibiotic alternative and can effectively relieve pneumonia caused by multidrug-resistant K. aerogenes. It carries a depolymerase that removes biofilms, reduces virulence, and improves intrinsic immune sensitivity.

Primary bone tumor detection and classification in full-field bone radiographs via YOLO deep learning model.

OBJECTIVES: Automatic bone lesions detection and classifications present a critical challenge and are essential to support radiologists in making an accurate diagnosis of bone lesions. In this paper, we aimed to develop a novel deep learning model called You Only Look Once (YOLO) to handle detecting and classifying bone lesions on full-field radiographs with limited manual intervention. METHODS: In this retrospective study, we used 1085 bone tumor radiographs and 345 normal bone radiographs from two centers between January 2009 and December 2020 to train and test our YOLO deep learning (DL) model. The trained model detected bone lesions and then classified these radiographs into normal, benign, intermediate, or malignant types. The intersection over union (IoU) was used to assess the model's performance in the detection task. Confusion matrices and Cohen's kappa scores were used for evaluating classification performance. Two radiologists compared diagnostic performance with the trained model using the external validation set. RESULTS: In the detection task, the model achieved accuracies of 86.36% and 85.37% in the internal and external validation sets, respectively. In the DL model, radiologist 1 and radiologist 2 achieved Cohen's kappa scores of 0.8187, 0.7927, and 0.9077 for four-way classification in the external validation set, respectively. The YOLO DL model illustrated a significantly higher accuracy for intermediate bone tumor classification than radiologist 1 (95.73% vs 88.08%, p = 0.004). CONCLUSIONS: The developed YOLO DL model could be used to assist radiologists at all stages of bone lesion detection and classification in full-field bone radiographs. KEY POINTS: • YOLO DL model can automatically detect bone neoplasms from full-field radiographs in one shot and then simultaneously classify radiographs into normal, benign, intermediate, or malignant. • The dataset used in this retrospective study includes normal bone radiographs. • YOLO can detect even some challenging cases with small volumes.

Shoulder MRI-based radiomics for diagnosis and severity staging assessment of surgically treated supraspinatus tendon tears.

OBJECTIVE: To develop and validate MRI-based radiomics models capable of evaluating supraspinatus tendon tears within the shoulder joints by using arthroscopy as the reference standard. METHODS: A total of 432 patients (332 in the training set and 100 in the external validation set) with intact supraspinatus tendon (n = 202) and supraspinatus tendon tear (n = 230, 130 full-thickness tears and 100 partial-thickness tears) were enrolled. Radiomics features were extracted from fat-saturated T2-weighted coronal images. Two radiomics signature models for detecting supraspinatus tendon abnormalities (tear or not), and stage lesion severity (full- or partial-thickness tear) and radiomics scores (Rad-score), were constructed and calculated using multivariate logistic regression analysis. The diagnostic performance of the two models was validated using ROC curves on the training and validation datasets. RESULTS: For the radiomics model of no tears or tears, thirteen features from MR images were used to build the radiomics signature with an AUC value of 0.98 in the training set, 0.97 in the internal validation set, and 0.98 in the external validation set. For the radiomics model of full- or partial-thickness tears, thirteen features from MR images were used to build the radiomics signature with an AUC value of 0.79 in the training set, 0.69 in the internal validation set, and 0.77 in the external validation set. CONCLUSION: The proposed radiomics models in this study can accurately rule out supraspinatus tendon tears and are capable of assessing the severity staging of tears with moderate accuracy based on shoulder MR images. KEY POINTS: • The radiomics model of no tears or tears achieved a high overall accuracy of 93.6%, sensitivity of 91.6%, and specificity of 95.2% for supraspinatus tendon tears. • The radiomics model of full- or partial-thickness tears displayed moderate performance with an accuracy of 76.4%, a sensitivity of 79.2%, and a specificity of 74.3% for supraspinatus tendon tears severity staging.

Lumbar MR-based radiomics nomogram for detecting minimal residual disease in patients with multiple myeloma.

OBJECTIVES: Minimal residual disease (MRD) is a standard for assessing treatment response in multiple myeloma (MM). MRD negativity is considered to be the most powerful predictor of long-term good outcomes. This study aimed to develop and validate a radiomics nomogram based on magnetic resonance imaging (MRI) of the lumbar spine to detect MRD after MM treatment. METHODS: A total of 130 MM patients (55 MRD negative and 75 MRD positive) who had undergone MRD testing through next-generation flow cytometry were divided into a training set (n = 90) and a test set (n = 40). Radiomics features were extracted from lumbar spinal MRI (T1-weighted images and fat-suppressed T2-weighted images) by means of the minimum redundancy maximum relevance method and the least absolute shrinkage and selection operator algorithm. A radiomics signature model was constructed. A clinical model was established using demographic features. A radiomics nomogram incorporating the radiomics signature and independent clinical factor was developed using multivariate logistic regression analysis. RESULTS: Sixteen features were used to establish the radiomics signature. The radiomics nomogram included the radiomics signature and the independent clinical factor (free light chain ratio) and showed good performance in detecting the MRD status (area under the curve: 0.980 in the training set and 0.903 in the test set). CONCLUSIONS: The lumbar MRI-based radiomics nomogram showed good performance in detecting MRD status in MM patients after treatment, and it is helpful for clinical decision-making. KEY POINTS: • The presence or absence of minimal residual disease status has a strong predictive significance for the prognosis of patients with multiple myeloma. • A radiomics nomogram based on lumbar MRI is a potential and reliable tool for evaluating minimal residual disease status in MM.

Positive allosteric modulators of the α7 nicotinic acetylcholine receptor: SAR investigation around PNU-120596.

The α7 nicotinic acetylcholine receptor is a calcium permeable, ligand-gated ion channel that modulates synaptic transmission in the hippocampus, thalamus, and cerebral cortex. Previously disclosed work described PNU-120596 that acts as a powerful positive allosteric modulator of the α7 nicotinic acetylcholine receptor. The initial structure-activity relationships around PNU-120596 were gleaned from screening a large thiazole library. Independent systematic examination of the aryl and heteroaryl groups resulted in compounds with enhanced potency and improved physico-chemical properties culminating in the identification of 16 (PHA-758454). In the presence of acetylcholine, 16 enhanced evoked currents in rat hippocampal neurons. In a rat model of impaired sensory gating, treatment with 16 led to a reversal of the gating deficit in a dose-dependent manner. These results demonstrate that aryl heteroaryl ureas, like compound 16, may be useful tools for continued exploration of the unique biology of the α7 nicotinic acetylcholine receptor.

Comparison of clinical safety and efficacy of ultrasound-guided local lauromacrogol injection versus uterine artery embolization in the treatment of caesarean scar pregnancy: a systematic review and meta-analysis.

BACKGROUND: The aim of this systematic review and meta-analysis was to introduce the relatively novel method of ultrasound-guided local lauromacrogol injection (USG-LLI) followed by dilatation and curettage for caesarean scar pregnancy (CSP) and to investigate the clinical safety and efficacy between uterine artery embolization (UAE) and USG-LLI in the treatment of CSP. METHODS: The relevant literature and articles about USG-LLI, UAE and CSP published in eight electronic databases were searched to extract the primary outcomes for the selected articles. Review Manager Software(RevMan) V.5.2 was used for quantitative data synthesis and data analysis. Forest plots, sensitivity analysis and bias analysis were also performed on the included articles. RESULTS: Of 10 studies included in our search, 623 patients were in the USG-LLI group and 627 patients were in the UAE groups. There were no significant differences between the two groups in terms of success rate, blood loss and time to human chorionic gonadotropin (hCG) normalization. However, USG-LLI group patients than UAE group patients had a shorter duration of hospital stay (mean difference [MD] = -1.97; 95% confidence intervals [CI] -2.63 to -1.31; P < 0.05; I2 = 95%), shorter restored menses (MD = -4.84; 95%CI -5.78 to -3.90; P < 0.05; I2 = 95%), and lower complication rates [odds ratio(OR) = 0.21; 95%CI:0.15 to 0.30; P < 0.05]; and cheaper on expenses of hospitalization (MD = -8028.29; 95%CI -10,311.18 to -5745.40; P < 0.05; I2 = 100%). CONCLUSIONS: The results demonstrate that USG-LLI is comparable in curative effect and success rates with UAE in the therapy of CSP, but patients in the USG-LLI group seem to have fewer complications rates, shorter duration of hospital stays and lower costs.

Histone methyltransferase ATX1 dynamically regulates fiber secondary cell wall biosynthesis in Arabidopsis inflorescence stem.

Secondary wall thickening in the sclerenchyma cells is strictly controlled by a complex network of transcription factors in vascular plants. However, little is known about the epigenetic mechanism regulating secondary wall biosynthesis. In this study, we identified that ARABIDOPSIS HOMOLOG of TRITHORAX1 (ATX1), a H3K4-histone methyltransferase, mediates the regulation of fiber cell wall development in inflorescence stems of Arabidopsis thaliana. Genome-wide analysis revealed that the up-regulation of genes involved in secondary wall formation during stem development is largely coordinated by increasing level of H3K4 tri-methylation. Among all histone methyltransferases for H3K4me3 in Arabidopsis, ATX1 is markedly increased during the inflorescence stem development and loss-of-function mutant atx1 was impaired in secondary wall thickening in interfascicular fibers. Genetic analysis showed that ATX1 positively regulates secondary wall deposition through activating the expression of secondary wall NAC master switch genes, SECONDARY WALL-ASSOCIATED NAC DOMAIN PROTEIN1 (SND1) and NAC SECONDARY WALL THICKENING PROMOTING FACTOR1 (NST1). We further identified that ATX1 directly binds the loci of SND1 and NST1, and activates their expression by increasing H3K4me3 levels at these loci. Taken together, our results reveal that ATX1 plays a key role in the regulation of secondary wall biosynthesis in interfascicular fibers during inflorescence stem development of Arabidopsis.

A CT-based radiomics nomogram for differentiation of squamous cell carcinoma and non-Hodgkin's lymphoma of the palatine tonsil.

OBJECTIVES: Accurate preoperative differentiation between squamous cell carcinoma (SCC) and non-Hodgkin's lymphoma (NHL) in the palatine tonsil is crucial because of their different treatment. This study aimed to construct and validate a contrast-enhanced CT (CECT)-based radiomics nomogram for preoperative differentiation of SCC and NHL in the palatine tonsil. METHODS: This study enrolled 135 patients with a pathological diagnosis of SCC or NHL from two clinical centers, who were divided into training (n = 94; SCC = 50, NHL = 44) and external validation sets (n = 41; SCC = 22, NHL = 19). A radiomics signature was constructed from radiomics features extracted from routine CECT images and a radiomics score (Rad-score) was calculated. A clinical model was established using demographic features and CT findings. The independent clinical factors and Rad-score were combined to construct a radiomics nomogram. Performance of the clinical model, radiomics signature, and nomogram was assessed using receiver operating characteristics analysis and decision curve analysis. RESULTS: Eleven features were finally selected to construct the radiomics signature. The radiomics nomogram incorporating gender, mean CECT value, and radiomics signature showed better predictive value for differentiating SCC from NHL than the clinical model for training (AUC, 0.919 vs. 0.801, p = 0.004) and validation (AUC, 0.876 vs. 0.703, p = 0.029) sets. Decision curve analysis demonstrated that the radiomics nomogram was more clinically useful than the clinical model. CONCLUSIONS: A CECT-based radiomics nomogram was constructed incorporating gender, mean CECT value, and radiomics signature. This nomogram showed favorable predictive efficacy for differentiating SCC from NHL in the palatine tonsil, and might be useful for clinical decision-making. KEY POINTS: • Differential diagnosis between SCC and NHL in the palatine tonsil is difficult by conventional imaging modalities. • A radiomics nomogram integrated with the radiomics signature, gender, and mean contrast-enhanced CT value facilitates differentiation of SCC from NHL with improved diagnostic efficacy.

Heterosexual Marital Intention: The Influences of Confucianism and Stigma Among Chinese Sexual Minority Women and Men.

In traditional Confucianist culture in China, marriage and offspring are highly valued, placing sexual minority adults under tremendous pressure to marry an opposite sex partner. This study explored how Confucianism and stigma were associated with the intention to pursue a heterosexual marriage among Chinese sexual minority individuals as well as the moderating mechanisms of gender and age. Cross-sectional data were collected from 747 participants via online social networks from March to June 2020. Items assessed Confucianism values (communalism, filial piety, traditional gender roles); stigma (rejection sensitivity, social discrimination); and heterosexual marital intention (HMI). A total of 1.7% (n = 12) participants had ever been married, 11.6% (n = 87) planned to marry a different-sex partner, 60.4% (n = 451) had no intention to pursue a heterosexual marriage, and 26.4% (n = 197) had no specific marital plan. Bisexual participants scored significantly higher than homosexual individuals in HMI. Sexual minority adults with high levels of Confucianism and stigma were more likely to intend to marry. Importantly, both individual stigma (rejection sensitivity) and interpersonal stigma (social discrimination) partially mediated the relationship between Confucianism and HMI. Confucianism had a stronger impact on HMI for men than women, and age moderated the influence of Confucianism (including communalism and filial piety) on HMI, with a stronger impact for younger than older generations. This study contributes to a better understanding of how Confucianism and stigma may be connected to the intention to pursue a heterosexual marriage, suggesting culture-modified theories of stigma and sexual minority stress are needed to explain the experiences of sexual minority people in contemporary China.

Spinal MRI-Based Radiomics Analysis to Predict Treatment Response in Multiple Myeloma.

OBJECTIVE: The aim of this study was to explore the clinical utility of spinal magnetic resonance imaging-based radiomics to predict treatment response (TR) in patients with multiple myeloma (MM). METHODS: A total of 123 MM patients (85 in the training cohort and 38 in the test cohort) with complete response (CR) (n = 40) or non-CR (n = 83) were retrospectively enrolled in the study. Key feature selection and data dimension reduction were performed using the least absolute shrinkage and selection operator regression. A nomogram was built by combining radiomic signatures and independent clinical risk factors. The prediction performance of the nomogram was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. Treatment response was assessed by determining the serum and urinary levels of M-proteins, serum-free light chain ratio, and the percentage of bone marrow plasma cells. RESULTS: Thirteen features were selected to build a radiomic signature. The International Staging System (ISS) stage was selected as an independent clinical factor. The radiomic signature and nomogram showed better calibration and higher discriminatory capacity (AUC of 0.929 and 0.917 for the radiomics and nomogram in the training cohort, respectively, and 0.862 and 0.874 for the radiomics and nomogram in the test cohort, respectively) than the clinical model (AUC of 0.661 and 0.674 in the training and test cohort, respectively). Decision curve analysis confirmed the clinical utility of the radiomics model. CONCLUSIONS: Nomograms incorporating a magnetic resonance imaging-based radiomic signature and ISS stage help predict the response to chemotherapy for MM and can be useful in clinical decision-making.

Diffusion kurtosis imaging assessment of the response to radiotherapy in a VX2 bone tumor model: an animal study.

BACKGROUND: Neoadjuvant radiotherapy plays a vital role in the treatment of malignant bone tumors, and non-invasive imaging methods are needed to evaluate the response to treatment. PURPOSE: To assess the value of diffusion kurtosis imaging (DKI) for monitoring early response to radiotherapy in malignant bone tumors. MATERIAL AND METHODS: Treatment response was evaluated in a rabbit VX2 bone tumor model (n = 35) using magnetic resonance imaging (MRI), DKI, and histopathologic examinations. Subjects were divided into three groups: pre-treatment, post-treatment, and control groups. The post-treatment group was subclassified into good response and poor response groups according to the results of histopathologic examination. Apparent diffusion coefficient (ADC) and DKI parameters (mean diffusion coefficient [MD] and mean kurtosis [MK]) were recorded. The relationship between ADC, DKI parameters, and histopathologic changes after radiotherapy was determined using Pearson's correlation coefficient. The diagnostic performance of these parameters was assessed using receiver operating characteristic analysis. RESULTS: MD in the good response group was higher after treatment than before treatment (P < 0.001) and higher than that in the poor response group (P = 0.009). MD was highly correlated with tumor cell density and apoptosis rate (r = -0.771, P < 0.001 and r = 0.625, P < 0.001, respectively). MD was superior to other parameters for determining the curative effect of radiotherapy, with a sensitivity of 75.0%, specificity of 100.0%, and area under the curve of 0.917 (P < 0.001). CONCLUSION: The correlations between MD, tumor cell density, and apoptosis suggest that MD could be useful for assessing the early response to radiotherapy in rabbit VX2 malignant bone tumors.

Optimism and friendship quality as mediators between trait emotional intelligence and life satisfaction in Chinese adolescents: A two-wave longitudinal study.

Using a convenience sample of adolescents (N = 1609; 63.5% female; M age = 16.54), this study explored whether EI predicted adolescent life satisfaction and whether friendship quality and optimism mediated this relationship during the COVID-19 pandemic. The structural equation modeling revealed that EI predicted adolescent life satisfaction, friendship quality, and optimism, friendship quality partially mediated the relationship between EI and life satisfaction, and optimism partially mediated the relationship between EI and friendship quality. These findings prove that psychological or educative approaches focused on EI could increase life satisfaction in adolescents during difficult times such as COVID-19, but EI may be linked with life satisfaction via friendship quality only. Training in optimism approaches and friendship quality enhancement programs could also effectively promote life satisfaction.

Blood-based multi-tissue gene expression inference with Bayesian ridge regression.

MOTIVATION: Gene expression profiling is widely used in basic and cancer research but still not feasible in many clinical applications because tissues, such as brain samples, are difficult and not ethnical to collect. Gene expression in uncollected tissues can be computationally inferred using genotype and expression quantitative trait loci. No methods can infer unmeasured gene expression of multiple tissues with single tissue gene expression profile as input. RESULTS: Here, we present a Bayesian ridge regression-based method (B-GEX) to infer gene expression profiles of multiple tissues from blood gene expression profile. For each gene in a tissue, a low-dimensional feature vector was extracted from whole blood gene expression profile by feature selection. We used GTEx RNAseq data of 16 tissues to train inference models to capture the cross-tissue expression correlations between each target gene in a tissue and its preselected feature genes in peripheral blood. We compared B-GEX with least square regression, LASSO regression and ridge regression. B-GEX outperforms the other three models in most tissues in terms of mean absolute error, Pearson correlation coefficient and root-mean-squared error. Moreover, B-GEX infers expression level of tissue-specific genes as well as those of non-tissue-specific genes in all tissues. Unlike previous methods, which require genomic features or gene expression profiles of multiple tissues, our model only requires whole blood expression profile as input. B-GEX helps gain insights into gene expressions of uncollected tissues from more accessible data of blood. AVAILABILITY AND IMPLEMENTATION: B-GEX is available at https://github.com/xuwenjian85/B-GEX. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A CT-based radiomics nomogram for differentiation of lympho-associated benign and malignant lesions of the parotid gland.

OBJECTIVES: Preoperative differentiation between benign lymphoepithelial lesion (BLEL) and mucosa-associated lymphoid tissue lymphoma (MALToma) in the parotid gland is important for treatment decisions. The purpose of this study was to develop and validate a CT-based radiomics nomogram combining radiomics signature and clinical factors for the preoperative differentiation of BLEL from MALToma in the parotid gland. METHODS: A total of 101 patients with BLEL (n = 46) or MALToma (n = 55) were divided into a training set (n = 70) and validation set (n = 31). Radiomics features were extracted from non-contrast CT images, a radiomics signature was constructed, and a radiomics score (Rad-score) was calculated. Demographics and CT findings were assessed to build a clinical factor model. A radiomics nomogram combining the Rad-score and independent clinical factors was constructed using multivariate logistic regression analysis. The performance levels of the nomogram, radiomics signature, and clinical model were evaluated and validated on the training and validation datasets, and then compared among the three models. RESULTS: Seven features were used to build the radiomics signature. The radiomics nomogram incorporating the clinical factors and radiomics signature showed favorable predictive value for differentiating parotid BLEL from MALToma, with AUCs of 0.983 and 0.950 for the training set and validation set, respectively. Decision curve analysis showed that the nomogram outperformed the clinical factor model in terms of clinical usefulness. CONCLUSIONS: The CT-based radiomics nomogram incorporating the Rad-score and clinical factors showed favorable predictive efficacy for differentiating BLEL from MALToma in the parotid gland, and may help in the clinical decision-making process. KEY POINTS: • Differential diagnosis between BLEL and MALToma in parotid gland is rather difficult by conventional imaging modalities. • A radiomics nomogram integrated with the radiomics signature, demographics, and CT findings facilitates differentiation of BLEL from MALToma with improved diagnostic efficacy.

Structure-function analysis of ß-arrestin Kurtz reveals a critical role of receptor interactions in downregulation of GPCR signaling in vivo.

Arrestins control signaling via the G protein coupled receptors (GPCRs), serving as both signal terminators and transducers. Previous studies identified several structural elements in arrestins that contribute to their functions as GPCR regulators. However, the importance of these elements in vivo is unclear, and the developmental roles of arrestins are not well understood. We carried out an in vivo structure-function analysis of Kurtz (Krz), the single ortholog of mammalian ß-arrestins in the Drosophila genome. A combination of Krz mutations affecting the GPCR-phosphosensing and receptor core-binding ("finger loop") functions (Krz-KKVL/A) resulted in a complete loss of Krz activity during development. Endosome recruitment and bioluminescence resonance energy transfer (BRET) assays revealed that the KKVL/A mutations abolished the GPCR-binding ability of Krz. We found that the isolated "finger loop" mutation (Krz-VL/A), while having a negligible effect on GPCR internalization, severely affected Krz function, suggesting that tight receptor interactions are necessary for proper termination of signaling in vivo. Genetic analysis as well as live imaging demonstrated that mutations in Krz led to hyperactivity of the GPCR Mist (also known as Mthl1), which is activated by its ligand Folded gastrulation (Fog) and is responsible for cellular contractility and epithelial morphogenesis. Krz mutations affected two developmental events that are under the control of Fog-Mist signaling: gastrulation and morphogenesis of the wing. Overall, our data reveal the functional importance in vivo of direct ß-arrestin/GPCR binding, which is mediated by the recognition of the phosphorylated receptor tail and receptor core interaction. These Krz-GPCR interactions are critical for setting the correct level of Fog-Mist signaling during epithelial morphogenesis.

CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV).

In this retrospective case series, chest CT scans of 21 symptomatic patients from China infected with the 2019 novel coronavirus (2019-nCoV) were reviewed, with emphasis on identifying and characterizing the most common findings. Typical CT findings included bilateral pulmonary parenchymal ground-glass and consolidative pulmonary opacities, sometimes with a rounded morphology and a peripheral lung distribution. Notably, lung cavitation, discrete pulmonary nodules, pleural effusions, and lymphadenopathy were absent. Follow-up imaging in a subset of patients during the study time window often demonstrated mild or moderate progression of disease, as manifested by increasing extent and density of lung opacities.

Radiomics nomogram for differentiating between benign and malignant soft-tissue masses of the extremities.

BACKGROUND: Preoperative differentiation between malignant and benign tumors is important for treatment decisions. PURPOSE/HYPOTHESIS: To investigate/validate a radiomics nomogram for preoperative differentiation between malignant and benign masses. STUDY TYPE: Retrospective. POPULATION: Imaging data of 91 patients. FIELD STRENGTH/SEQUENCE: T1 -weighted images (570 msec repetition time [TR]; 17.9 msec echo time [TE], 200-400 mm field of view [FOV], 208-512 × 208-512 matrix), fat-suppressed fast-spin-echo (FSE) T2 -weighted images (T2 WIs) (4331 msec TR; 87.9 msec TE, 200-400 mm FOV, 312 × 312 matrix), slice thickness 4 mm, and slice spacing 1 mm. ASSESSMENT: Fat-suppressed FSE T2 WIs were selected for extraction of features. Radiomics features were extracted from fat-suppressed T2 WIs. A radiomics signature was generated from the training dataset using least absolute shrinkage and selection operator algorithms. Independent risk factors were identified by multivariate logistic regression analysis and a radiomics nomogram was constructed. Nomogram capability was evaluated in the training dataset and validated in the validation dataset. Performance of the nomogram, radiomics signature, and clinical model were compared. STATISTICAL TESTS: 1) Independent t-test or Mann-Whitney U-test: for continuous variables. Fisher's exact test or χ2 test: comparing categorical variables between two groups. Univariate analysis: evaluating associations between clinical/morphological characteristics and malignancy. 2) Least absolute shrinkage and selection operator (LASSO)-logistic regression model: selection of malignancy features. 3) Significant clinical/morphological characteristics and radiomics signature were input variables for multiple logistic regression analysis. Area under the curve (AUC): evaluation of ability of the nomogram to identify malignancy. Hosmer-Lemeshow test and decision curve: evaluation and validation of nomogram results. RESULTS: The radiomics nomogram was able to differentiate malignancy from benignity in the training and validation datasets with an AUC of 0.94. The nomogram outperformed both the radiomics signature and clinical model alone. DATA CONCLUSION: This radiomics nomogram is a noninvasive, low-cost preoperative prediction method combining the radiomics signature and clinical model. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:155-163.