Mrakia polaris sp. nov. and Mrakia amundsenii sp. nov. (Mrakiaceae, Cystofilobasidiales), two novel psychrophilic yeast species isolated from Arctic habitats.

Four yeast strains belonging to the basidiomycetous yeast genus Mrakia were isolated from diverse habitats in the Ny-Ålesund region (Svalbard, High Arctic): two from vascular plants, one from seawater and one from freshwater. Phylogenetic analysis, based on the ITS region and the D1/D2 domain of the 28S rRNA gene, identified these four strains as representing two novel species within the genus Mrakia. The names Mrakia polaris sp. nov. (MycoBank number: MB 852063) and Mrakia amundsenii sp. nov. (MycoBank number: MB 852064) are proposed. These two new species show distinct psychrophilic adaptations, as they exhibit optimal growth at temperatures between 10 and 15°C, while being unable to grow at 25°C. The holotype of M. polaris sp. nov. is CPCC 300345T, and the holotype of M. amundsenii sp. nov. is CPCC 300572T.

Predicting Microwave Ablation Early Efficacy in Pulmonary Malignancies via Δ Radiomics Models.

OBJECTIVE: This study aimed to explore the value of preoperative and postoperative computed tomography (CT)-based radiomic signatures and Δ radiomic signatures for evaluating the early efficacy of microwave ablation (MWA) for pulmonary malignancies. METHODS: In total, 115 patients with pulmonary malignancies who underwent MWA treatment were categorized into response and nonresponse groups according to relevant guidelines and consensus. Quantitative image features of the largest pulmonary malignancies were extracted from CT noncontrast scan images preoperatively (time point 0, TP0) and immediately postoperatively (time point 1, TP1). Critical features were selected from TP0 and TP1 and as Δ radiomics signatures for building radiomics models. In addition, a combined radiomics model (C-RO) was developed by integrating radiomics parameters with clinical risk factors. Prediction performance was assessed using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). RESULTS: The radiomics model using Δ features outperformed the radiomics model using TP0 and TP1 features, with training and validation AUCs of 0.892, 0.808, and 0.787, and 0.705, 0.825, and 0.778, respectively. By combining the TP0, TP1, and Δ features, the logistic regression model exhibited the best performance, with training and validation AUCs of 0.945 and 0.744, respectively. The DCA confirmed the clinical utility of the Δ radiomics model. CONCLUSIONS: A combined prediction model, including TP0, TP1, and Δ radiometric features, can be used to evaluate the early efficacy of MWA in pulmonary malignancies.

Value of High-Resolution MRI in the Diagnosis of Brachial Plexus Injury in Infants and Young Children.

Purpose: To investigate the value of high-resolution MRI based on 3D-short inversion time inversion recovery sampling perfection with application-optimized contrasts (3D-STIR SPACE) sequence for the diagnosis of brachial plexus injury in infants and young children. Methods: Physical examination, electromyography (EMG) and MRI data of 26 children with brachial plexus injury were retrospectively analyzed. Sensitivity, specificity, and accuracy were calculated for the three tests. The agreement among these examinations was analyzed with the Kappa test. P<0.05 was considered statistically significant. Results: Of the 26 children, 3 cases had normal MRIs, 23 cases had unilateral brachial plexus injury diagnosed with MRI, and a total of 73 nerve roots and/or sheaths were involved. Among the 23 cases with aberrant MRI findings, there were 19 cases of nerve root thickening (42 nerve roots), 4 cases of nerve root sleeve expansion (5 nerve roots), 17 cases of pseudomeningeal cysts (34 nerve roots), 2 cases of nerve root loosening (2 nerve roots), 8 cases of nerve root dissection (11 nerve roots), 19 cases with increased nerve signal (43 nerve roots), and 9 cases with an increased signal of the muscles on the affected side. As for the diagnosis of brachial plexus injury, the sensitivity and the accuracy of physical examination, EMG and MRI were 0.92, 0.86, and 0.88, respectively. The agreement between MRI and physical examination was substantial (κ=0.780, P=0.000), as did the agreement between MRI and EMG (κ=0.611, P=0.005). Conclusion: High-resolution MRI based on 3D-STIR SPACE sequence plays a role in the diagnosis and evaluation of brachial plexus injury in infants and young children. It can accurately identify the injured nerve and characterize related pathological alterations. Besides EMG and physical examination, it can be used as a valuable tool for screening and monitoring of brachial plexus injury in infants and children.

Preoperative prediction of extramural venous invasion in rectal cancer by dynamic contrast-enhanced and diffusion weighted MRI: a preliminary study.

BACKGROUND: To explore the value of the quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) parameters in assessing preoperative extramural venous invasion (EMVI) in rectal cancer. METHODS: Eighty-two rectal adenocarcinoma patients who had underwent MRI preoperatively were enrolled in this study. The differences in quantitative DCE-MRI and DWI parameters including Krans, Kep and ADC values were analyzed between MR-detected EMVI (mrEMVI)-positive and -negative groups. Multivariate logistic regression analysis was performed to build the combined prediction model for pathologic EMVI (pEMVI) with statistically significant quantitative parameters. The performance of the model for predicting pEMVI was evaluated using receiver operating characteristic (ROC) curve. RESULTS: Of the 82 patients, 24 were mrEMVI-positive and 58 were -negative. In the mrEMVI positive group, the Ktrans and Kep values were significantly higher than those in the mrEMVI negative group (P < 0.01), but the ADC values were significantly lower (P < 0.01). A negative correlation was observed between the Ktrans vs ADC values and Kep vs ADC values in patients with rectal cancer. Among the four quantitative parameters, Ktrans and ADC value were independently associated with mrEMVI by multivariate logistic regression analysis. ROC analysis showed that combined prediction model based on quantitative DCE parameters and ADC values had a good prediction efficiency for pEMVI in rectal cancer. CONCLUSION: The quantitative DCE-MRI parameters, Krans, Kep and ADC values play important role in predicting EMVI of rectal cancer, with Ktrans and ADC value being independent predictors of EMVI in rectal cancer.

Modified Look-Locker Inverse-Recovery (MOLLI) Sequence of Quantitative Imaging in Dirty Magnetic Resonance Longitudinal Relaxation Time Diagnostic Value of GE Combined with Longitudinal Relaxation Time Quantitative Imaging for Myocardial Amyloidosis.

The pathological changes of myocarditis include degeneration and necrosis of myocardial cells and infiltration of inflammatory cells in the myocardial interstitium, accompanied by obvious myocardial fibrosis. Myocardial fibrosis is a determinant of ventricular remodeling and an important indicator of the classification of clinical risk factors and has an important value in evaluating the prognosis of heart disease. Cardiac magnetic resonance (CMR) is the "gold standard" for evaluating the shape and function of the heart, and it can show the characteristic pathological changes of myocardial tissue. The traditional gadolinium imaging agent delays the enhanced sequence images to visually show the extent of the affected myocardial fibrosis, but it cannot effectively identify small focal fibrosis or widespread diffuse fibrosis. The CMR longitudinal relaxation time quantitative technique can directly measure the relaxation time (T1) determined by the myocardial tissue and does not depend on the signal strength of the reference tissue and can quantitatively analyze the affected myocardium. In this study, the initial and enhanced quantitative imaging techniques of CMR were used to measure the magnetic value of the myocardium in patients with myocarditis, to explore the diagnostic value of myocardial fibrosis, and to analyze the correlation between cardiac fibrosis and cardiac function.

Application of texture analysis based on T2-weighted magnetic resonance images in discriminating Gleason scores of prostate cancer.

OBJECTIVE: To investigate the value of texture analysis in magnetic resonance images for the evaluation of Gleason scores (GS) of prostate cancer. METHODS: Sixty-six prostate cancer patients are retrospective enrolled, which are divided into five groups namely, GS = 6, 3 + 4, 4 + 3, 8 and 9-10 according to postoperative pathological results. Extraction and analysis of texture features in T2-weighted MR imaging defined tumor region based on pathological specimen after operation are performed by texture software OmniKinetics. The values of texture are analyzed by single factor analysis of variance (ANOVA), and Spearman correlation analysis is used to study the correlation between the value of texture and Gleason classification. Receiver operating characteristic (ROC) curve is then used to assess the ability of applying texture parameters to predict Gleason score of prostate cancer. RESULTS: Entropy value increases and energy value decreases as the elevation of Gleason score, both with statistical difference among five groups (F = 10.826, F = 2.796, P < 0.05). Energy value of group GS = 6 is significantly higher than that of groups GS = 8 and 9-10 (P < 0.005), which is similar between three groups (GS = 3 + 4, 8 and 9-10). The entropy and energy values correlate with GS (r = 0.767, r = -0.692, P < 0.05). Areas under ROC curves (AUC) of combination of entropy and energy are greater than that of using energy alone between groups GS = 6 and ≥7. Analogously, AUC of combination of entropy and energy are significantly higher than that of using entropy alone between groups GS≤3 + 4 and ≥4 + 3, as well as between groups GS≤4 + 3 and ≥8. CONCLUSION: Texture analysis on T2-weighted images of prostate cancer can evaluate Gleason score, especially using the combination of entropy and energy rendering better diagnostic efficiency.