CellTrackVis: interactive browser-based visualization for analyzing cell trajectories and lineages.

BACKGROUND: Automatic cell tracking methods enable practitioners to analyze cell behaviors efficiently. Notwithstanding the continuous development of relevant software, user-friendly visualization tools have room for further improvements. Typical visualization mostly comes with main cell tracking tools as a simple plug-in, or relies on specific software/platforms. Although some tools are standalone, limited visual interactivity is provided, or otherwise cell tracking outputs are partially visualized. RESULTS: This paper proposes a self-reliant visualization system, CellTrackVis, to support quick and easy analysis of cell behaviors. Interconnected views help users discover meaningful patterns of cell motions and divisions in common web browsers. Specifically, cell trajectory, lineage, and quantified information are respectively visualized in a coordinated interface. In particular, immediate interactions among modules enable the study of cell tracking outputs to be more effective, and also each component is highly customizable for various biological tasks. CONCLUSIONS: CellTrackVis is a standalone browser-based visualization tool. Source codes and data sets are freely available at http://github.com/scbeom/celltrackvis with the tutorial at http://scbeom.github.io/ctv_tutorial .

Application of computer-aided diagnosis for Lung-RADS categorization in CT screening for lung cancer: effect on inter-reader agreement.

OBJECTIVES: To evaluate the effects of computer-aided diagnosis (CAD) on inter-reader agreement in Lung Imaging Reporting and Data System (Lung-RADS) categorization. METHODS: Two hundred baseline CT scans covering all Lung-RADS categories were randomly selected from the National Lung Cancer Screening Trial. Five radiologists independently reviewed the CT scans and assigned Lung-RADS categories without CAD and with CAD. The CAD system presented up to five of the most risk-dominant nodules with measurements and predicted Lung-RADS category. Inter-reader agreement was analyzed using multirater Fleiss κ statistics. RESULTS: The five readers reported 139-151 negative screening results without CAD and 126-142 with CAD. With CAD, readers tended to upstage (average, 12.3%) rather than downstage Lung-RADS category (average, 4.4%). Inter-reader agreement of five readers for Lung-RADS categorization was moderate (Fleiss kappa, 0.60 [95% confidence interval, 0.57, 0.63]) without CAD, and slightly improved to substantial (Fleiss kappa, 0.65 [95% CI, 0.63, 0.68]) with CAD. The major cause for disagreement was assignment of different risk-dominant nodules in the reading sessions without and with CAD (54.2% [201/371] vs. 63.6% [232/365]). The proportion of disagreement in nodule size measurement was reduced from 5.1% (102/2000) to 3.1% (62/2000) with the use of CAD (p < 0.001). In 31 cancer-positive cases, substantial management discrepancies (category 1/2 vs. 4A/B) between reader pairs decreased with application of CAD (pooled sensitivity, 85.2% vs. 91.6%; p = 0.004). CONCLUSIONS: Application of CAD demonstrated a minor improvement in inter-reader agreement of Lung-RADS category, while showing the potential to reduce measurement variability and substantial management change in cancer-positive cases. KEY POINTS: • Inter-reader agreement of five readers for Lung-RADS categorization was minimally improved by application of CAD, with a Fleiss kappa value of 0.60 to 0.65. • The major cause for disagreement was assignment of different risk-dominant nodules in the reading sessions without and with CAD (54.2% vs. 63.6%). • In 31 cancer-positive cases, substantial management discrepancies between reader pairs, referring to a difference in follow-up interval of at least 9 months (category 1/2 vs. 4A/B), were reduced in half by application of CAD (32/310 to 16/310) (pooled sensitivity, 85.2% vs. 91.6%; p = 0.004).

Differentiating pulmonary metastasis from benign lung nodules in thyroid cancer patients using dual-energy CT parameters.

OBJECTIVES: To explore the importance of quantitative characteristics of dual-energy CT (DECT) between pulmonary metastasis and benign lung nodules in thyroid cancer. METHODS: In this retrospective study, we identified 63 patients from our institution's database with pathologically proven thyroid cancer who underwent DECT to assess pulmonary metastasis. Among these patients, 22 had 55 pulmonary metastases, and 41 had 97 benign nodules. If nodules showed increased iodine uptake on I-131 single-photon emission computed tomography-computed tomography or increased size in follow-up CT, they were considered metastatic. We compared the clinical findings and DECT parameters of both groups and performed a receiver operating characteristic analysis to evaluate the optimal cutoff values of the DECT parameters. RESULTS: Patients with metastases were significantly older than patients with benign nodules (p = 0.048). The DECT parameters of the metastatic nodules were significantly higher than those of the benign nodules (iodine concentration [IC], 5.61 ± 2.02 mg/mL vs. 1.61 ± 0.98 mg/mL; normalized IC [NIC], 0.60 ± 0.20 vs. 0.16 ± 0.11; NIC using pulmonary artery [NICPA], 0.60 ± 0.44 vs. 0.15 ± 0.11; slope of the spectral attenuation curves [λHU], 5.18 ± 2.54 vs. 2.12 ± 1.39; and Z-effective value [Zeff], 10.0 ± 0.94 vs. 8.79 ± 0.75; all p < 0.001). In the subgroup analysis according to nodule size, all DECT parameters of the metastatic nodules in all subgroups were significantly higher than those of the benign nodules (all p < 0.05). The cutoff values for IC, NIC, λHU, NICPA, and Zeff for diagnosing metastases were 3.10, 0.29, 3.57, 0.28, and 9.34, respectively (all p < 0.001). CONCLUSIONS: DECT parameters can help to differentiate metastatic and benign lung nodules in thyroid cancer. KEY POINTS: • DECT parameters can help to differentiate metastatic and benign lung nodules in patients with thyroid cancer. • DECT parameters showed a significant difference between benign lung nodules and lung metastases, even for nodules with diameters ≥ 3 mm and < 5 mm. • Among the DECT parameters, the highest diagnostic accuracy for differentiating pulmonary metastases from benign lung nodules was achieved with the NIC and IC, followed by the NICPA and λHU, and their cutoff values were 0.29, 3.10, 0.28, and 3.57, respectively.

Utility of a Deep Learning Algorithm for Detection of Reticular Opacity on Chest Radiography in Patients With Interstitial Lung Disease.

BACKGROUND. Deep learning has been heavily explored for pulmonary nodule detection on chest radiographs. Detection of reticular opacity in interstitial lung disease (ILD) is challenging and may also benefit from a deep learning algorithm (DLA). OBJECTIVE. The purpose of this study was to evaluate the utility of a DLA for detection of reticular opacity on chest radiographs of patients with surgically confirmed ILD. METHODS. This retrospective study included 197 patients (130 men, 67 women; mean age, 62.6 ± 7.6 [SD] years) with surgically proven ILD between January 2017 and December 2018 who underwent preoperative chest radiography and chest CT within a 30-day interval. A total of 197 age- and sex-matched control patients with normal chest radiographs were randomly selected. A commercially available DLA was used to detect lower lobe or subpleural abnormalities; those matching the reticular opacity location on CT were deemed true-positive. Six readers (three thoracic radiologists, three residents) independently reviewed radiographs with and without the DLA for the presence of reticular opacity. Interobserver agreement was assessed. Diagnostic performance was compared among interpretations. Subanalysis was performed according to CT-based classification of the severity of reticular opacity. Performance of the DLA was also assessed on 102 chest radiographs from a second institution (51 patients with ILD, 51 matched patients in the control group). RESULTS. Interobserver agreement was moderate (κ = 0.517) for readers alone and almost perfect (κ = 0.870) for readers using the DLA. Sensitivity, specificity, and accuracy of the DLA for reticular opacity were 98.0%, 99.0%, and 98.5%; of pooled readers alone were 77.3%, 92.3%, and 84.8%; and of readers using the DLA were 93.8%, 97.3%, and 95.6%. All metrics were significantly better (all p ≤ .002) for the DLA and for readers using the DLA than for readers alone. Sensitivity for readers without and with the DLA were 66.7% and 86.8% for mild disease, 84.2% and 98.8% for moderate disease, and 87.3% and 100.0% for severe disease. The DLA had 100.0% accuracy at the second institution. CONCLUSION. The DLA outperformed readers in detection of reticular opacity, and use of the DLA improved reader performance and interobserver agreement. The benefit of the DLA was more notable in sensitivity than in specificity and was maintained in mild disease. CLINICAL IMPACT. Use of the DLA may facilitate detection of reticular opacity on chest radiographs in the early stages of ILD.

Decolorization of Textile Dye by Spore Surface Displayed Small Laccase for the Enhanced Thermal Stability and Robust Repeated Reaction.

In this study, we tried to decolorize synthetic dyes using small laccase (SLAC) from Streptomyces coelicolor, which is resistant to pH, temperature change, and traditional inhibitors for the actual industrial applications using spore surface display system. We inserted SLAC-His6 tag at the C-terminal of CotE anchoring motif. The proper surface expression of CotE-SLAC fusion protein on the surface of Bacillus subtilis spore was verified with flow cytometry using FITC labeled anti-His6 tag antibody. After 6 h of reaction, more than 90% of Indigo carmine was decomposed using recombinant SLAC displaying Bacillus spore, whereas less than 10% of Indigo carmine was decomposed with wild type spore. Over 70% of laccase activity was retained with recombinant SLAC displaying spore, which was heat-treated for 3 h at 90°C. For eight rounds of repeated decomposition of Indigo carmine, no significant decrease of enzymatic activity was observed. This showed the robust characteristics of spore display format for repeated and harsh condition reactions.

Use of a Commercially Available Deep Learning Algorithm to Measure the Solid Portions of Lung Cancer Manifesting as Subsolid Lesions at CT: Comparisons with Radiologists and Invasive Component Size at Pathologic Examination.

Background The solid portion size of lung cancer lesions manifesting as subsolid lesions is key in their management, but the automatic measurement of such lesions by means of a deep learning (DL) algorithm needs evaluation. Purpose To evaluate the performance of a commercially available DL algorithm for automatic measurement of the solid portion of surgically proven lung adenocarcinomas manifesting as subsolid lesions. Materials and Methods Surgically proven lung adenocarcinomas manifesting as subsolid lesions on CT images between January 2018 and December 2018 were retrospectively included. Five radiologists independently measured the maximal axial diameter of the solid portion of lesions. The DL algorithm automatically segmented and measured the maximal axial diameter of the solid portion. Reader measurements, software measurements, and invasive component size at pathologic examination were compared by using intraclass correlation coefficient (ICC) and Bland-Altman plots. Results A total of 448 patients (mean age, 63 years ± 10 [standard deviation]; 264 women) with 448 lesions were evaluated (invasive component size, 3-65 mm). The measurement agreements between each radiologist and the DL algorithm were very good (ICC range, 0.82-0.89). When a radiologist was replaced with the DL algorithm, the ICCs ranged from 0.87 to 0.90, with an ICC of 0.90 among five radiologists. The mean difference between the DL algorithm and each radiologist ranged from -3.7 to 1.5 mm. The widest 95% limit of agreement between the DL algorithm and each radiologist (-15.7 to 8.3 mm) was wider than pairwise comparisons of radiologists (-7.7 to 13.0 mm). The agreement between the DL algorithm and invasive component size at pathologic evaluation was good, with an ICC of 0.67. Measurements by the DL algorithm (mean difference, -6.0 mm) and radiologists (mean difference, -7.5 to -2.3 mm) both underestimated invasive component size. Conclusion Automatic measurements of solid portions of lung cancer manifesting as subsolid lesions by the deep learning algorithm were comparable with manual measurements and showed good agreement with invasive component size at pathologic evaluation. © RSNA, 2021 Online supplemental material is available for this article.

Computer-aided Detection of Subsolid Nodules at Chest CT: Improved Performance with Deep Learning-based CT Section Thickness Reduction.

Background Studies on the optimal CT section thickness for detecting subsolid nodules (SSNs) with computer-aided detection (CAD) are lacking. Purpose To assess the effect of CT section thickness on CAD performance in the detection of SSNs and to investigate whether deep learning-based super-resolution algorithms for reducing CT section thickness can improve performance. Materials and Methods CT images obtained with 1-, 3-, and 5-mm-thick sections were obtained in patients who underwent surgery between March 2018 and December 2018. Patients with resected synchronous SSNs and those without SSNs (negative controls) were retrospectively evaluated. The SSNs, which ranged from 6 to 30 mm, were labeled ground-truth lesions. A deep learning-based CAD system was applied to SSN detection on CT images of each section thickness and those converted from 3- and 5-mm section thickness into 1-mm section thickness by using the super-resolution algorithm. The CAD performance on each section thickness was evaluated and compared by using the jackknife alternative free response receiver operating characteristic figure of merit. Results A total of 308 patients (mean age ± standard deviation, 62 years ± 10; 183 women) with 424 SSNs (310 part-solid and 114 nonsolid nodules) and 182 patients without SSNs (mean age, 65 years ± 10; 97 men) were evaluated. The figures of merit differed across the three section thicknesses (0.92, 0.90, and 0.89 for 1, 3, and 5 mm, respectively; P = .04) and between 1- and 5-mm sections (P = .04). The figures of merit varied for nonsolid nodules (0.78, 0.72, and 0.66 for 1, 3, and 5 mm, respectively; P < .001) but not for part-solid nodules (range, 0.93-0.94; P = .76). The super-resolution algorithm improved CAD sensitivity on 3- and 5-mm-thick sections (P = .02 for 3 mm, P < .001 for 5 mm). Conclusion Computer-aided detection (CAD) of subsolid nodules performed better at 1-mm section thickness CT than at 3- and 5-mm section thickness CT, particularly with nonsolid nodules. Application of a super-resolution algorithm improved the sensitivity of CAD at 3- and 5-mm section thickness CT. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Goo in this issue.

Ischemia-induced Netrin-4 promotes neovascularization through endothelial progenitor cell activation via Unc-5 Netrin receptor B.

Endothelial progenitor cells (EPCs) promote neovascularization and tissue repair by migrating to vascular injury sites; therefore, factors that enhance EPC homing to damaged tissues are of interest. Here, we provide evidence of the prominent role of the Netrin-4 (NTN4)-Unc-5 Netrin receptor B (UNC5B) axis in EPC-specific promotion of ischemic neovascularization. Our results showed that NTN4 promoted the proliferation, chemotactic migration, and paracrine effects of small EPCs (SEPCs) and significantly increased the incorporation of large EPCs (LEPCs) into tubule networks. Additionally, NTN4 prominently augmented neovascularization in mice with hindlimb ischemia by increasing the homing of exogenously transplanted EPCs to the ischemic limb and incorporating EPCs into vessels. Moreover, silencing of UNC5B, an NTN4 receptor, abrogated the NTN4-induced cellular activities of SEPCs in vitro and blood-flow recovery and neovascularization in vivo in ischemic muscle by reducing EPC homing and incorporation. These findings suggest NTN4 as an EPC-based therapy for treating angiogenesis-dependent diseases.

Deep learning-based differentiation of invasive adenocarcinomas from preinvasive or minimally invasive lesions among pulmonary subsolid nodules.

OBJECTIVES: To evaluate a deep learning-based model using model-generated segmentation masks to differentiate invasive pulmonary adenocarcinoma (IPA) from preinvasive lesions or minimally invasive adenocarcinoma (MIA) on CT, making comparisons with radiologist-derived measurements of solid portion size. METHODS: Four hundred eleven subsolid nodules (SSNs) (120 preinvasive lesions or MIAs and 291 IPAs) in 333 patients who underwent surgery between June 2010 and August 2016 were retrospectively included to develop the model (370 SSNs in 293 patients for training and 41 SSNs in 40 patients for tuning). Ninety SSNs of 2 cm or smaller (45 preinvasive lesions or MIAs and 45 IPAs) resected in 2018 formed a validation set. Six radiologists measured the solid portion of each nodule. Performances of the model and radiologists were assessed using receiver operating characteristics curve analysis. RESULTS: The deep learning model differentiated IPA from preinvasive lesions or MIA with areas under the curve (AUCs) of 0.914, 0.956, and 0.833 for the training, tuning, and validation sets, respectively. The mean AUC of the radiologists was 0.835 in the validation set, without significant differences between radiologists and the model (p = 0.97). The sensitivity, specificity, and accuracy of the model were 71% (32/45), 87% (39/45), and 79% (71/90), respectively, whereas the corresponding values of the radiologists were 75.2% (203/270), 76.7% (207/270), and 75.9% (410/540) with a 5-mm threshold for the solid portion size. CONCLUSIONS: The performance of the model for differentiating IPA from preinvasive lesions or MIA was comparable to that of the radiologists' measurements of solid portion size. KEY POINTS: • A deep learning-based model differentiated IPA from preinvasive lesions or MIA with AUCs of 0.914 and 0.956 for the training and tuning sets, respectively. • In the validation set including subsolid nodules of 2 cm or smaller, the model showed an AUC of 0.833, being on par with the performance of the solid portion size measurements made by the radiologists (AUC, 0.835; p = 0.97). • SSNs with a solid portion measuring > 10 mm on CT showed a high probability of being IPA (positive predictive value, 93.5-100.0%).

Performance of radiomics models for survival prediction in non-small-cell lung cancer: influence of CT slice thickness.

OBJECTIVES: To investigate whether CT slice thickness influences the performance of radiomics prognostic models in non-small-cell lung cancer (NSCLC) patients. METHODS: CT images including 1-, 3-, and 5-mm slice thicknesses acquired from 311 patients who underwent surgical resection for NSCLC between May 2014 and December 2015 were evaluated. Tumor segmentation was performed on CT of each slice thickness and total 94 radiomics features (shape, tumor intensity, and texture) were extracted. The study population was temporally split into development (n = 185) and validation sets (n = 126) for prediction of disease-free survival (DFS). Three radiomics models were built from three different slice thickness datasets (Rad-1, Rad-3, and Rad-5), respectively. Model performance was assessed and compared in three slice thickness datasets and mixed slice thickness dataset using C-indices. RESULTS: In corresponding slice thickness datasets, the C-indices of Rad-1, Rad-3, and Rad-5 for prediction of DFS were 0.68, 0.70, and 0.68 in the development set, and 0.73, 0.73, and 0.76 in the validation set (p = 0.40-0.89 and 0.27-0.90, respectively). Performance of the models was not significantly changed when they were applied to different slice thicknesses data in the validation set (C-index, 0.73-0.76, 0.72-0.73, 0.75-0.76; p = 0.07-0.92). In the mixed slice thickness dataset, performances of the models were similar to or slightly lower than their performances in the corresponding slice thickness datasets (C-index, 0.72-0.75 vs. 0.73-0.76) in the validation set. CONCLUSIONS: The performance of radiomics models for predicting DFS in NSCLC patients was not significantly affected by CT slice thickness. KEY POINTS: • Three radiomics models based on 1-, 3-, and 5-mm CT datasets showed C-indices for predicting disease-free survival of 0.68-0.70 in the development set and 0.73-0.76 in the validation set, without statistical differences (p = 0.27-0.90). • Application of the radiomics models to different slice thickness datasets showed no significant differences in performance between the values in the prediction of disease-free survival (p = 0.07-0.99). • Three radiomics models based on 1-, 3-, and 5-mm CT datasets performed well in mixed slice thickness datasets, showing similar or slightly lower performances.

Nitrates administered by spray versus tablet: comparison of coronary vasodilation on CT angiography.

OBJECTIVES: To compare the coronary vasodilation effects of spray with those induced by tablet administration in coronary CT angiography (CCTA). METHODS: A total of 2024 patients who underwent CCTA were identified for this retrospective study, including 828 patients with spray (spray group) and 1169 with tablets (tablet group). Of these, 93 patients underwent CCTA at least twice using both spray and tablets. The number of measurable segments and diameters of all 18 segments was measured. The number of measurable segments was compared between groups. RESULTS: No statistically significant differences were evident between these two groups in terms of clinical characteristics. All coronary segments except the ramus intermedius (RI) and left posterior descending artery (L-PDA) were significantly larger in the spray group than in the tablet group (all p < 0.001). In peripheral and branch vessels, as well as in central and main coronary arteries, the diameters were significantly larger in the spray group than in the tablet group (all p < 0.001). Although not always statistically significant, all coronary segments tended to be more measurable on CCTA with spray than with tablet. In the subgroup that underwent CCTA twice using both spray and tablets, all coronary segments except the RI, obtuse marginal artery 2 (OM2), and L-PDA were significantly larger in the spray group than in the tablet group (all p < 0.05). CONCLUSION: Lingual isosorbide dinitrate (ISDN) spray was more efficacious than sublingual nitroglycerin (NTG) tablets in coronary vasodilation for CCTA. Therefore, lingual ISDN spray should be preferred over sublingual NTG tablets for CCTA. KEY POINTS: • Lingual ISDN spray was more efficacious than sublingual NTG tablet for coronary vasodilation in coronary CT angiography, even in elderly patients. • The diameters of all coronary segments except RI and L-PDA were significantly larger, and there were significantly more coronary segments greater than 1.5 mm, except RI and L-PDA, in the spray group than in the tablet group in the whole study group. • Even in peripheral and branch vessels, the diameters of coronary arteries were significantly larger in the spray group than in the tablet group, and they were also larger in elderly patients.

Effectiveness of radiologist training in improving reader agreement for Lung-RADS 4X categorization.

OBJECTIVES: To identify the agreement on Lung CT Screening Reporting and Data System 4X categorization between radiologists and an expert-adjudicated reference standard and to investigate whether training led to improvement of the agreement measures and diagnostic potential for lung cancer. METHODS: Category 4 nodules in the Korean Lung Cancer Screening Project were identified retrospectively, and each 4X nodule was matched with one 4A or 4B nodule. An expert panel re-evaluated the categories and determined the reference standard. Nineteen radiologists were asked to determine the presence of CT features of malignancy and 4X categorization for each nodule. A review was performed in two sessions, and training material was given after session 1. Agreement on 4X categorization between radiologists and the expert-adjudicated reference standard and agreement between radiologist-assessed 4X categorization and lung cancer diagnosis were evaluated. RESULTS: The 48 expert-adjudicated 4X nodules and 64 non-4X nodules were evenly distributed in each session. The proportion of category 4X decreased after training (56.4% ± 16.9% vs. 33.4% ± 8.0%; p < 0.001). Cohen's κ indicated poor agreement (0.39 ± 0.16) in session 1, but agreement improved in session 2 (0.47 ± 0.09; p = 0.03). The increase in agreement in session 2 was observed among inexperienced radiologists (p < 0.05), and experienced and inexperienced reviewers exhibited comparable agreement performance in session 2 (p > 0.05). All agreement measures between radiologist-assessed 4X categorization and lung cancer diagnosis increased in session 2 (p < 0.05). CONCLUSION: Radiologist training can improve reader agreement on 4X categorization, leading to enhanced diagnostic performance for lung cancer. KEY POINTS: • Agreement on 4X categorization between radiologists and an expert-adjudicated reference standard was initially poor, but improved significantly after training. • The mean proportion of 4X categorization by 19 radiologists decreased from 56.4% ± 16.9% in session 1 to 33.4% ± 8.0% in session 2. • All agreement measures between the 4X categorization and lung cancer diagnosis increased significantly in session 2, implying that appropriate training and guidance increased the diagnostic potential of category 4X.

New Bacterial Surface Display System Development and Application Based on Bacillus subtilis YuaB Biofilm Component as an Anchoring Motif.

Bacterial surface display system has been adopted in various biotechnological applications. In the case of Bacillus subtilis, most of the studies have been developed using spore based surface display system utilizing the inherent rigidity of spore against heat, alkali, and shear stress. But, spore harvest, purification and separation need additional cost and labor. To eliminate this procedure and to use the gram-positive nature of B. subtilis, YuaB, which is one of the major B. subtilis biofilm components and locates in the cell wall, based cell surface display system, is developed. P43 promoter driven overexpression of YuaB-His6 tag does not hamper bacterial cell growth and promoted biofilm formation of recombinant strain. Flow cytometry of recombinant strain and its protoplast using FITC-Anti His6 antibody, verified that YuaB locate in plasma membrane and protrude to the outside of cell wall, which means YuaB can be used as very efficient anchoring motif. Using surface expressed YuaB-His6 tag, removal of divalent metal ion, Cu2+ and Ni2+, was tried to test its possibility for the environmental application of developed system.

Somatic Mutations in TSC1 and TSC2 Cause Focal Cortical Dysplasia.

Focal cortical dysplasia (FCD) is a major cause of the sporadic form of intractable focal epilepsies that require surgical treatment. It has recently been reported that brain somatic mutations in MTOR account for 15%-25% of FCD type II (FCDII), characterized by cortical dyslamination and dysmorphic neurons. However, the genetic etiologies of FCDII-affected individuals who lack the MTOR mutation remain unclear. Here, we performed deep hybrid capture and amplicon sequencing (read depth of 100×-20,012×) of five important mTOR pathway genes-PIK3CA, PIK3R2, AKT3, TSC1, and TSC2-by using paired brain and saliva samples from 40 FCDII individuals negative for MTOR mutations. We found that 5 of 40 individuals (12.5%) had brain somatic mutations in TSC1 (c.64C>T [p.Arg22Trp] and c.610C>T [p.Arg204Cys]) and TSC2 (c.4639G>A [p.Val1547Ile]), and these results were reproducible on two different sequencing platforms. All identified mutations induced hyperactivation of the mTOR pathway by disrupting the formation or function of the TSC1-TSC2 complex. Furthermore, in utero CRISPR-Cas9-mediated genome editing of Tsc1 or Tsc2 induced the development of spontaneous behavioral seizures, as well as cytomegalic neurons and cortical dyslamination. These results show that brain somatic mutations in TSC1 and TSC2 cause FCD and that in utero application of the CRISPR-Cas9 system is useful for generating neurodevelopmental disease models of somatic mutations in the brain.

Ginkgetin, a biflavone from Ginkgo biloba leaves, prevents adipogenesis through STAT5-mediated PPARγ and C/EBPα regulation.

Adipogenesis involved in hypertrophy and hyperplasia of adipocytes is responsible for expanding the mass of adipose tissues in obese individuals. Peroxisome proliferator-activated receptor γ (PPARγ) and CCAAT/enhancer-binding protein α (C/EBPα) are two principal transcription factors induced by delicate signaling pathways, including signal transducer and activator of transcription 5 (STAT5), in adipogenesis. Here, we demonstrated a novel role of ginkgetin, a biflavone from Ginkgo biloba leaves, as a STAT5 inhibitor that blocks the differentiation of preadipocytes into adipocytes. During the differentiation of 3T3-L1 cells, ginkgetin treatment during the first 2 days markedly inhibited the formation of lipid-bearing adipocytes. PPARγ and C/EBPα expression was decreased in 3T3-L1 cells during adipogenesis following ginkgetin treatment, whereas no change was observed in C/EBPß or C/EBPδ expression. Inhibition of PPARγ and C/EBPα expression by ginkgetin occurred through the prevention of STAT5 activation during the initiation phase of adipogenesis. In addition, ginkgetin-mediated the inhibition of adipogenesis was recapitulated in the differentiation of primary preadipocytes. Lastly, we confirmed the inhibitory effects of ginkgetin on the hypertrophy of white adipose tissues from high-fat diet-fed mice. These results indicate that ginkgetin is a potential anti-adipogenesis and anti-obesity drug.

Association between Breslow thickness and dermoscopic findings in acral melanoma.

BACKGROUND: Dermoscopy is a useful tool for the diagnosis of acral melanomas (AMs). However, little is known about the influence of tumor thickness on the dermoscopic findings of AM. OBJECTIVE: To investigate the affect Breslow thickness (BT) has on the dermoscopic patterns of AM. METHODS: Data on cases of AM on the glabrous skin were collected from 4 university hospitals. We investigated the frequency of each dermoscopic feature of AM according to the BT. Statistical analysis was performed to investigate the association between the specific dermoscopic patterns and BT. RESULTS: Multivariable analysis revealed that the colors red (odds ratio [OR] 16.482, 95% confidence interval [CI] 3.605-99.016); blue (OR 7.092; 95% CI 1.707-37.435); and white (OR 5.048, 95% CI 1.152-22.897) were more common in AM with BT >2 mm than those with BT ≤2 mm. Regarding patterns, atypical vascular (OR 34.589, 95% CI 6.458-305.852); blue-white veils (OR 9.605, 95% CI 1.971-72.062); and ulcers (OR 5.084, 95% CI 1.145-24.152) were more frequently detected in cases with BT >2 mm than those with BT ≤2 mm. LIMITATIONS: A retrospective study design and small sample size. CONCLUSION: This study showed an association between dermoscopic patterns and tumor thickness among patients with AM. Dermoscopy can be a useful adjuvant tool for predicting BT in AM.

Evaluation of extracapsular extension in prostate cancer using qualitative and quantitative multiparametric MRI.

PURPOSE: To investigate the value of multiparametric magnetic resonance imaging (mpMRI) for extracapsular extension (ECE) in prostate cancer (PCa). MATERIALS AND METHODS: In all, 292 patients who received radical prostatectomy and underwent preoperative mpMRI at 3T were enrolled retrospectively. For determining the associations with ECE, the likelihood of ECE was assessed qualitatively on T2 -weighted imaging (T2 WI) and combined T2 WI and diffusion-weighted imaging (DWI) or dynamic contrast-enhanced imaging (DCEI). Quantitative MRI parameters were measured in PCa based on histopathological findings. Two models for detecting ECE including imaging and clinical parameters were developed using multivariate analysis: Model 1 excluding combined T2 WI and DWI and DCEI and Model 2 excluding combined T2 WI and DWI, and combined T2 WI and DCEI. Diagnostic performance of imaging parameters and models was evaluated using the area under the receiver operating characteristics curve (Az). RESULTS: For detecting ECE, the specificity, accuracy, and Az of combined T2 WI and DWI or DCEI were statistically better than those of T2 WI (P < 0.05), and all quantitative MRI parameters showed a statistical difference between the patients with and without ECE (P < 0.05). On multivariate analysis, significant independent markers in Model 1 were combined T2 WI and DWI, combined T2 WI and DCEI, and Ktrans (P < 0.05). In Model 2, significant markers were combined T2 WI and DWI and DCEI, Ktrans , Kep , and Ve (P < 0.05). The Az values of models 1 and 2 were 0.944 and 0.957, respectively. CONCLUSION: mpMRI may be useful to improve diagnostic accuracy of the models for determining the associations with ECE in PCa. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;45:1760-1770.

Identification of sennoside A as a novel inhibitor of the slingshot (SSH) family proteins related to cancer metastasis.

Phospho-cofilin (p-cofilin), which has a phosphate group on Ser-3, is involved in actin polymerization. Its dephosphorylated form promotes filopodia formation and cell migration by enhancing actin depolymerization. Protein phosphatase slingshot homologs (SSHs), known as dual-specificity phosphatases, catalyze hydrolytic removal of the Ser-3 phosphate group from phospho-cofilin. Aberrant SSH activity results in cancer metastasis, implicating SSHs as potential therapeutic targets for cancer metastasis. In this study, we screened 658 natural products purified from traditional oriental medicinal plants to identify three potent SSH inhibitors with submicromolar or single-digit micromolar Ki values: gossypol, hypericin, and sennoside A. The three compounds were purified from cottonseed, Saint John's wort, and rhubarb, respectively. Sennoside A markedly increased cofilin phosphorylation in pancreatic cancer cells, leading to impaired actin dynamics in pancreatic cancer cells with or without EGF stimulation and reduced motility and invasiveness in vitro and in vivo. Collaboratively, these results demonstrate that sennoside A is a novel inhibitor of SSHs and suggest that it may be valuable in the development of pharmaceutical drugs for treating cancer metastasis.

CT and microbiologic follow-up in primary multidrug-resistant pulmonary tuberculosis.

BACKGROUND: Little attention has been paid to the initial and follow-up computed tomography (CT) features in primary multi-drug resistant tuberculosis (pMDR-TB) setting. PURPOSE: To describe serial CT findings and clinical course of pMDR-TB with antibiotic treatment. MATERIAL AND METHODS: For the last 10 years, 340 MDR-TB patients were managed in a tertiary referral hospital. Among them, we included 44 (27 men, 17 women; mean age, 40 years; age range, 20-81 years) pMDR-TB patients; 37 treated with chemotherapy only and seven treated with medical therapy plus surgery. CT findings were evaluated regarding tree-in-bud sign, acinar nodule, peribronchial, segmental or lobar consolidation and cavity, and their extent. Sputum negative conversion rates and serial CT scores were assessed. To compare changes in disease extent between initial and follow-up CT studies, paired t-test was performed. RESULTS: Two most frequent patterns of lung abnormality were tree-in-bud sign (37 of 44, 84.1%) and acinar nodule (41 of 44, 93.2%). Among 37 patients treated with chemotherapy only, 36 showed negative sputum conversion within 3 months after second-line drug commencement, maintained for >12 months. The other seven undergoing surgery during medical treatment showed excellent outcome with negative conversion achieved within one month after surgery and maintained for >12 months. CT scores showed significant decrease on serial CT studies (P < 0.001) in all. CONCLUSION: In pMDR-TB, two most frequent abnormal CT patterns are tree-in-bud sign and acinar nodule. In 98% of patients, negative sputum conversion is achieved, and CT score also shows decrease in extent after TB chemotherapy.

Surface display of bacterial tyrosinase on spores of Bacillus subtilis using CotE as an anchor protein.

Tyrosinases, copper-containing monooxygenases, are widely used enzymes for industrial, medical, and environmental applications. We report the first functional surface display of Bacillus megaterium tyrosinase on Bacillus subtilis spores using CotE as an anchor protein. Flow Cytometry was used to verify surface expression of tyrosinase on the purified spores. Moreover, tyrosinase activity of the displayed enzyme on B. subtilis spores was monitored in the presence of L-tyrosine (substrate) and CuSO4 (inducer). The stability of the spore-displayed tyrosinase was then evaluated after 15 days maintenance of the spores at room temperature, and no significant decrease in the enzyme activity was observed. In addition, the tyrosinase-expressing spores could be repeatedly used with 62% retained enzymatic activity after six times washing with Tris-HCl buffer. This genetically immobilized tyrosinase on the spores would make a new advance in industrial, medical, and environmental applications.