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Cryptococcosis, caused by the basidiomycetous fungus Cryptococcus neoformans, is responsible for more than 600,000 deaths annually in AIDS patients. Flucytosine is one of the most commonly used antifungal drugs for its treatment, but its resistance and regulatory mechanisms have never been investigated at the genome scale in C. neoformans. In the present study, we performed comparative transcriptome analysis by employing two-component system mutants (tco1⌬ and tco2⌬) exhibiting opposing flucytosine susceptibility. As a result, a total of 177 flucytosine-responsive genes were identified, and many of them were found to be regulated by Tco1 or Tco2. Among these, we discovered an APSES-like transcription factor, Mbs1 (Mbp1-and Swi4-like protein 1). Expression analysis revealed that MBS1 was regulated in response to flucytosine in a Tco2/Hog1-dependent manner. Supporting this, C. neoformans with the deletion of MBS1 exhibited increased susceptibility to flucytosine. Intriguingly, Mbs1 played pleiotropic roles in diverse cellular processes of C. neoformans. Mbs1 positively regulated ergosterol biosynthesis and thereby affected polyene and azole drug susceptibility. Mbs1 was also involved in genotoxic and oxidative stress responses. Furthermore, Mbs1 promoted production of melanin and capsule and thereby was required for full virulence of C. neoformans. In conclusion, Mbs1 is considered to be a novel antifungal therapeutic target for treatment of cryptococcosis.

Objectives: The aim of this study was to investigate the utility of a combined compressed sensing and parallel imaging (C-SENSE) technique for single breath-hold, double arterial phase (AP) examinations in gadoxetate-enhanced magnetic resonance imaging (MRI) of the liver. Materials and Methods: We retrospectively reviewed single breath-hold, double AP images obtained by using a C-SENSE technique for gadoxetate-enhanced dynamic liver MRI in a total of 127 patients (89 men and 38 women; mean age, 62.6 ± 7.5 [range, 29-87] years). For qualitative analysis, 3 readers independently scored the timing of the AP images, degree of artifacts, and overall image quality on both the first and second AP images (AP1 and AP2, respectively). The combined scores of AP1 and AP2 (AP1 + AP2) were determined by using the better scores from the 2 sets. Focal lesion detectability was assessed for 124 lesions with arterial enhancement on AP1 and AP2, and on simultaneous review of both AP1 and AP2. Then, in 62 patients whose previous gadoxetate-enhanced single AP images were available, AP timing and overall image quality were compared between single and double AP images. Wilcoxon signed rank test was performed for each comparison. Fleiss kappa value was calculated for analysis of interreader agreement. Results: Optimal AP timing was achieved in 86% of AP1, 65% of AP2, and 90% of AP1 + AP2 images; results were significantly better for AP1 and AP1 + AP2 images than for AP2 images (P < 0.001 for both comparisons). Respiratory motion artifacts were negligible in 73% of the AP1 + AP2 images, which was significantly better than the corresponding values for the AP1 (61%, P < 0.001) or AP2 (50%, P < 0.001) images. Overall image quality was significantly better for AP1 + AP2 (excellent in 54%) than for AP1 (49%, P < 0.001) or AP2 (39%, P < 0.001) images. Lesion detectability was comparable between AP1 and AP2 images and was significantly better on AP1 + AP2. Comparison of single and double AP imaging techniques showed better AP timing (P = 0.004) and fewer respiratory motion artifacts (P < 0.001) for AP1 + AP2 than for the single AP images. Conclusions: The C-SENSE technique may facilitate single breath-hold, double AP imaging with optimal timing and reduced respiratory motion artifacts in gadoxetate-enhanced dynamic MRI of the liver.

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The purpose of this study was to develop and test the performance of a deep learning-based algorithm to detect ileocolic intussusception using abdominal radiographs of young children. For the training set, children (≤5 years old) who underwent abdominal radiograph and ultrasonography (US) for suspicion of intussusception from March 2005 to December 2017 were retrospectively included and divided into control and intussusception groups according to the US results. A YOLOv3-based algorithm was developed to recognize the rectangular area of the right abdomen and to diagnose intussusception. For the validation set, children (≤5 years old) who underwent both radiograph and US from January to August 2018 with the suspicion of intussusception were included. Diagnostic performances of an algorithm and radiologists were compared. Total 681 children including 242 children in intussusception group were included in the training set and 75 children including 25 children in intussusception group were included in the validation set. The sensitivity of the algorithm was higher compared with that of the radiologists (0.76 vs. 0.46, p = 0.013), while specificity was not different between the algorithm and the radiologists (0.96 vs. 0.92, p = 0.32). Deep learning-based algorithm can aid screening of intussusception using abdominal radiography in young children.

BackgroundThe goal of this study was to investigate the expression of sarcosine metabolism-related proteins, namely glycine N-methyltransferase (GNMT), sarcosine dehydrogenase (SARDH), and l-pipecolic acid oxidase (PIPOX), in the different breast cancer subtypes and to assess the implications of differences in expression pattern according to subtype.MethodsWe analyzed the expression of GNMT, SARDH, and PIPOX in a tissue microarray of 721 breast cancer cases using immunohistochemistry (IHC). We classified breast cancer cases into subtype luminal A, luminal B, HER-2, and triple negative breast cancer (TNBC) according to the status for the estrogen receptor (ER), progesterone receptor (PR), HER-2, and Ki-67. Sarcosine metabolism phenotype was stratified according to IHC results for GNMT, SARDH, and PIPOX: GNMT(+), SARDH and PIPOX(-) was classified as high sarcosine type; GNMT(-), SARDH or PIPOX(-) as low sarcosine type; GNMT(+), SARDH or PIPOX(+) as intermediate sarcosine type, and GNMT(-), SARDH and PIPOX(-) as null type.ResultsExpression of sarcosine metabolism-related proteins differed significantly according to breast cancer subtype (GNMT, p = 0.005; SARDH, p = 0.012; tumoral PIPOX, p = 0.008; stromal PIPOX, p < 0.001). These proteins were the most frequently expressed in HER-2 type tumors and the least in TNBC. Sarcosine metabolism phenotype also varied according to breast cancer subtype, with high sarcosine type the most common in HER-2, and null type the most common in TNBC (p = 0.003). Univariate analysis revealed that GNMT expression (p = 0.042), tumoral PIPOX negativity (p = 0.039), and high sarcosine type (p = 0.021) were associated with shorter disease-free survival (DFS). Multivariate analysis also revealed GNMT expression was an independent factor for shorter DFS (hazard ratio: 2.408, 95% CI: 1.154-5.024, p = 0.019).ConclusionExpressions of sarcosine metabolism-related proteins varied according to subtype of breast cancer, with HER-2 type tumors showing elevated expression of these proteins, and TNBC subtype showing decreased expression of these proteins. Expression of sarcosine metabolism-related proteins was also associated with breast cancer prognosis.

Background: The reported diagnostic performance for hepatocellular carcinoma (HCC) of each major imaging feature on MRI using standardized definitions of the Liver Imaging Reporting and Data System (LI-RADS) is variable. It is important to know the actual performance of each LI-RADS major imaging feature for imaging diagnosis of HCC and determine the sources of heterogeneity between the reported results. Purpose: To systematically determine the performance of each major imaging feature of LI-RADS for diagnosing HCC using either extracellular contrast agent-enhanced MRI (ECA-MRI) or gadoxetate disodium-enhanced MRI (EOB-MRI). Study Type: Systematic review and meta-analysis. Subjects: Sixteen original articles with 3542 lesions. Field Strength: A 1.5 T and 3.0 T. Assessment: Data extraction was independently performed by two reviewers who identified and reviewed original articles reporting the diagnostic performance of each LI-RADS major imaging feature-arterial phase hyperenhancement (APHE), observation size, washout appearance, enhancing "capsule," and threshold growth-using MRI. Study characteristics, study population characteristics, MRI characteristics, contrast agent, LI-RADS version, reference standards, and study outcomes were extracted from included studies. Risk of bias and concerns regarding applicability were evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Statistical Tests: Bivariate random-effects models were used to obtain summary estimates of the diagnostic performance of each LI-RADS major imaging feature. Hierarchical summary receiver operating characteristic curves were plotted. Metaregression analyses were performed to explore potential sources of heterogeneity. Results: The pooled per-observation sensitivities and specificities for diagnosing HCC were 85% (95% confidence interval [CI] = 78%-89%) and 57% (95% CI = 44%-70%) for arterial phase hyperenhancement (APHE), 77% (95% CI = 72%-82%), and 74% (95% CI = 63%-83%) for washout appearance, and 52% (95% CI = 41%-64%) and 90% (95% CI = 85%-94%) for enhancing "capsule," respectively. Data Conclusions: Among the LI-RADS major features, the sensitivity was the highest for APHE and the specificity was the highest for enhancing "capsule" in the diagnosis of HCC. Evidence Level: 3 Technical Efficacy: Stage 2

Background Sarcopenia is defined as the loss of skeletal muscle mass and is associated with negative clinical outcomes. This study aimed to establish sex-specific cutoff values for the skeletal muscle area (SMA) and skeletal muscle index (SMI) at the third lumbar vertebral (L3) level using computed tomography (CT) imaging to identify sarcopenia in healthy Korean liver donors. Methods This retrospective study included 659 healthy liver donors (408 men and 251 women) aged 20 to 60 years who had undergone abdominal CT examinations between January 2017 and December 2018. Assessment of body composition was performed with an automated segmentation technique using a deep-learning system. Sex-specific SMA and SMI distributions were assessed, and cutoff values for determining sarcopenia were defined as values at either two standard deviations (SDs) below the mean reference value or below the fifth percentile. Results Using the SD definition, cutoff values for SMA and SMI were 117.04 cm 2 and 39.33 cm 2 /m 2 , respectively, in men and 71.39 cm 2 and 27.77 cm 2 /m 2 , respectively, in women. Using the fifth percentile definition, cutoff values for SMA and SMI were 126.88 cm 2 and 40.96 cm 2 /m 2 , respectively, in men and 78.85 cm 2 and 30.60 cm 2 /m 2 , respectively, in women. Conclusion Our data provide sex-specific cutoff values for the SMA and SMI at the L3 level measured by CT imaging in a healthy Korean population, which may be applicable for identifying sarcopenia in this population.