Pathogenic GATA2 genetic variants utilize an obligate enhancer mechanism to distort a multilineage differentiation program.

Mutations in genes encoding transcription factors inactivate or generate ectopic activities to instigate pathogenesis. By disrupting hematopoietic stem/progenitor cells, GATA2 germline variants create a bone marrow failure and leukemia predisposition, GATA2 deficiency syndrome, yet mechanisms underlying the complex phenotypic constellation are unresolved. We used a GATA2-deficient progenitor rescue system to analyze how genetic variation influences GATA2 functions. Pathogenic variants impaired, without abrogating, GATA2-dependent transcriptional regulation. Variants promoted eosinophil and repressed monocytic differentiation without regulating mast cell and erythroid differentiation. While GATA2 and T354M required the DNA-binding C-terminal zinc finger, T354M disproportionately required the N-terminal finger and N terminus. GATA2 and T354M activated a CCAAT/Enhancer Binding Protein-ε (C/EBPε) enhancer, creating a feedforward loop operating with the T-cell Acute Lymphocyte Leukemia-1 (TAL1) transcription factor. Elevating C/EBPε partially normalized hematopoietic defects of GATA2-deficient progenitors. Thus, pathogenic germline variation discriminatively spares or compromises transcription factor attributes, and retaining an obligate enhancer mechanism distorts a multilineage differentiation program.

Artificial intelligence for ultrasound microflow imaging in breast cancer diagnosis.

PURPOSE: To develop and evaluate artificial intelligence (AI) algorithms for ultrasound (US) microflow imaging (MFI) in breast cancer diagnosis. MATERIALS AND METHODS: We retrospectively collected a dataset consisting of 516 breast lesions (364 benign and 152 malignant) in 471 women who underwent B-mode US and MFI. The internal dataset was split into training (n = 410) and test datasets (n = 106) for developing AI algorithms from deep convolutional neural networks from MFI. AI algorithms were trained to provide malignancy risk (0-100%). The developed AI algorithms were further validated with an independent external dataset of 264 lesions (229 benign and 35 malignant). The diagnostic performance of B-mode US, AI algorithms, or their combinations was evaluated by calculating the area under the receiver operating characteristic curve (AUROC). RESULTS: The AUROC of the developed three AI algorithms (0.955-0.966) was higher than that of B-mode US (0.842, P < 0.0001). The AUROC of the AI algorithms on the external validation dataset (0.892-0.920) was similar to that of the test dataset. Among the AI algorithms, no significant difference was found in all performance metrics combined with or without B-mode US. Combined B-mode US and AI algorithms had a higher AUROC (0.963-0.972) than that of B-mode US (P < 0.0001). Combining B-mode US and AI algorithms significantly decreased the false-positive rate of BI-RADS category 4A lesions from 87% to 13% (P < 0.0001). CONCLUSION: AI-based MFI diagnosed breast cancers with better performance than B-mode US, eliminating 74% of false-positive diagnoses in BI-RADS category 4A lesions.

Supply and demand: Brokerage as the new tango in home care.

The performance of home care globally is significantly impacted by the political reforms in the public and private sectors. This research investigated the Australian contexts of home care quality and the use of "brokerage" during times of change. The research utilised a qualitative post-structural approach to gather data about home care service provision through conducting semi-structured interviews of 10 Australian home care business leaders. What emerged in the discourse was how central to everyday practices was the need for business leaders to network and 'dance a political tango' to ensure quality in service provision. Illuminated was how the leaders pushed back against governmental and economic structures by using models of brokerage to compensate for economic and staffing deficiencies. This is essential for the ongoing improvement and performance of home care in the Australian social arena of caring for our most vulnerable consumers.

Antibody-mediated delivery of a viral MHC-I epitope into the cytosol of target tumor cells repurposes virus-specific CD8+ T cells for cancer immunotherapy.

BACKGROUND: Redirecting pre-existing virus-specific cytotoxic CD8+ T lymphocytes (CTLs) to tumors by simulating a viral infection of the tumor cells has great potential for cancer immunotherapy. However, this strategy is limited by lack of amenable method for viral antigen delivery into the cytosol of target tumors. Here, we addressed the limit by developing a CD8+ T cell epitope-delivering antibody, termed a TEDbody, which was engineered to deliver a viral MHC-I epitope peptide into the cytosol of target tumor cells by fusion with a tumor-specific cytosol-penetrating antibody. METHODS: To direct human cytomegalovirus (CMV)-specific CTLs against tumors, we designed a series of TEDbodies carrying various CMV pp65 antigen-derived peptides. CMV-specific CTLs from blood of CMV-seropositive healthy donors were expanded for use in in vitro and in vivo experiments. Comprehensive cellular assays were performed to determine the presentation mechanism of TEDbody-mediated CMV peptide-MHC-I complex (CMV-pMHCI) on the surface of target tumor cells and the recognition and lysis by CMV-specific CTLs. In vivo CMV-pMHCI presentation and antitumor efficacy of TEDbody were evaluated in immunodeficient mice bearing human tumors. RESULTS: TEDbody delivered the fused epitope peptides into target tumor cells to be intracellularly processed and surface displayed in the form of CMV-pMHCI, leading to disguise target tumor cells as virally infected cells for recognition and lysis by CMV-specific CTLs. When systemically injected into tumor-bearing immunodeficient mice, TEDbody efficiently marked tumor cells with CMV-pMHCI to augment the proliferation and cytotoxic property of tumor-infiltrated CMV-specific CTLs, resulting in significant inhibition of the in vivo tumor growth by redirecting adoptively transferred CMV-specific CTLs. Further, combination of TEDbody with anti-OX40 agonistic antibody substantially enhanced the in vivo antitumor activity. CONCLUSION: Our study offers an effective technology for MHC-I antigen cytosolic delivery. TEDbody may thus have utility as a therapeutic cancer vaccine to redirect pre-existing anti-viral CTLs arising from previously exposed viral infections to attack tumors.

SARS-CoV-2 B.1.619 and B.1.620 Lineages, South Korea, 2021.

We report the rapid emergence of severe acute respiratory syndrome coronavirus 2 lineages B.1.619 and B.1.620 in South Korea. The surge in frequency in a relatively short time emphasizes the need for ongoing monitoring for new lineages to track potential increases in transmissibility and disease severity and reductions in vaccine efficacy.

Genomic evidence of SARS-CoV-2 reinfection in the Republic of Korea.

As the coronavirus disease 2019 (COVID-19) pandemic continues, reinfection is likely to become increasingly common. However, confirming COVID-19 reinfection is difficult because it requires whole-genome sequencing of both infections to identify the degrees of genetic differences. Since the first reported case of reinfection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the Republic of Korea in April 2020, four additional cases were classified as suspected reinfection cases. We performed whole-genome sequencing of viral RNA extracted from swabs obtained at the initial infection and reinfection stages of these four suspected cases. The interval between initial infection and reinfection of all four suspected cases was more than 3 months. All four patients were young (10-29 years), and they displayed mild symptoms or were asymptomatic during the initial infection and reinfection episodes. The analysis of genome sequences combined with the epidemiological results revealed that only two of the four cases were confirmed as reinfection, and both were reinfected with the Epsilon variant. Due to the prolonged COVID-19 pandemic, the possibility of reinfections with SARS-CoV-2 variants is increasing, as reported in our study. Therefore, continuous monitoring of cases is necessary.

Added value of abbreviated breast magnetic resonance imaging for assessing suspicious microcalcification on screening mammography-a prospective study.

OBJECTIVES: To investigate the added diagnostic value of abbreviated breast magnetic resonance imaging (MRI) for suspicious microcalcifications on screening mammography. METHODS: This prospective study included 80 patients with suspicious calcifications on screening mammography who underwent abbreviated MRI before undergoing breast biopsy between August 2017 and September 2020. The abbreviated protocol included one pre-contrast and the first post-contrast T1-weighted series. MRI examinations were interpreted as either positive or negative based on the visibility of any significant enhancement. The positive predictive value (PPV) was compared before and after the MRI. RESULTS: Of the 80 suspicious microcalcifications, 33.8% (27/80) were malignant and 66.2% (53/80) were false positives. Abbreviated MRI revealed 33 positive enhancement lesions, and 25 and two lesions showed true-positive and false-negative findings, respectively. Abbreviated MRI increased PPV from 33.8 (27 of 80 cases; 95% CI: 26.2%, 40.8%) to 75.8% (25 of 33 cases; 95% CI: 62.1%, 85.7%). A total of 85% (45 of 53) false-positive diagnoses were reduced after abbreviated MRI assessment. CONCLUSIONS: Abbreviated MRI added significant diagnostic value in patients with suspicious microcalcifications on screening mammography, as demonstrated by a significant increase in PPV with a potential reduction in unnecessary biopsy. KEY POINTS: • Abbreviated breast magnetic resonance imaging increased the positive predictive value of suspicious microcalcifications on screening mammography from 33.8 (27/80 cases) to 75.8% (25/33 cases) (p < .01). • Abbreviated magnetic resonance imaging helped avoid unnecessary benign biopsies in 85% (45/53 cases) of lesions without missing invasive cancer.

An All-in-One Vehicle Type and License Plate Recognition System Using YOLOv4.

In smart surveillance and urban mobility applications, camera-equipped embedded platforms with deep learning technology have demonstrated applicability and effectiveness in identifying various targets. These use cases can be found in a variety of contexts and locations. It is critical to collect relevant data from the location where the application will be deployed. In this paper, we propose an integrated vehicle type and license plate recognition system using YOLOv4, which consists of vehicle type detection, license plate detection, and license plate character detection to better support the context of Korean vehicles in multilane highway and urban environments. Using our dataset of one to four multilane images, our system detected six vehicle classes and license plates with mAP of 98.0%, 94.0%, 97.1%, and 84.6%, respectively. On our dataset and a publicly available open dataset, our system demonstrated mAP of 99.3% and 99.4% for the detected license plates, respectively. From 4K high-resolution images, our system was able to detect minuscule license plates as small as 100 pixels wide. We believe that our system can be used in densely populated regions to address the high demands for enhanced visual sensitivity in smart cities and Internet-of-Things.

Suppression of Osteoarthritis progression by post-natal Induction of Nkx3.2.

Osteoarthritis (OA) is an incurable joint disease affecting 240 million elderly population, and major unmet medical needs exist for better therapeutic options for OA. During skeletal development, Nkx3.2 has been shown to promote chondrocyte differentiation and survival, but to suppress cartilage hypertrophy and blood vessel invasion. Here we show that Nkx3.2 plays a key role in osteoarthritis (OA) pathogenesis. Marked reduction of Nkx3.2 expression was observed in three different murine OA models. Consistent with these findings, analyses of surgery-induced and age-driven OA models revealed that cartilage-specific post-natal induction of Nkx3.2 can suppress OA progression in mice. These results suggest that Nkx3.2 may serve as a promising target for OA drug development.

Texture analysis using machine learning-based 3-T magnetic resonance imaging for predicting recurrence in breast cancer patients treated with neoadjuvant chemotherapy.

OBJECTIVES: To determine whether texture analysis for magnetic resonance imaging (MRI) can predict recurrence in patients with breast cancer treated with neoadjuvant chemotherapy (NAC). METHODS: This retrospective study included 130 women who received NAC and underwent subsequent surgery for breast cancer between January 2012 and August 2017. We assessed common features, including standard morphologic MRI features and clinicopathologic features. We used a  commercial software and analyzed texture features from pretreatment and midtreatment MRI. A random forest (RF) method was performed to build a model for predicting recurrence. The diagnostic performance of this model for predicting recurrence was assessed and compared with those of five other machine learning classifiers using the Wald test. RESULTS: Of the 130 women, 21 (16.2%) developed recurrence at a median follow-up of 35.4 months. The RF classifier with common features including clinicopathologic and morphologic MRI features showed the lowest diagnostic performance (area under the receiver operating characteristic curve [AUC], 0.83). The texture analysis with the RF method showed the highest diagnostic performances for pretreatment T2-weighted images and midtreatment DWI and ADC maps showed better diagnostic performance than that of an analysis of common features (AUC, 0.94 vs. 0.83, p < 0.05). The RF model based on all sequences showed a better diagnostic performance for predicting recurrence than did the five other machine learning classifiers. CONCLUSIONS: Texture analysis using an RF model for pretreatment and midtreatment MRI may provide valuable prognostic information for predicting recurrence in patients with breast cancer treated with NAC and surgery. KEY POINTS: • RF model-based texture analysis showed a superior diagnostic performance than traditional MRI and clinicopathologic features (AUC, 0.94 vs.0.83, p < 0.05) for predicting recurrence in breast cancer after NAC. • Texture analysis using RF classifier showed the highest diagnostic performances (AUC, 0.94) for pretreatment T2-weighted images and midtreatment DWI and ADC maps. • RF model showed a better diagnostic performance for predicting recurrence than did the five other machine learning classifiers.

Fully automated measurements of volumetric breast density adapted for BIRADS 5th edition: a comparison with visual assessment.

BACKGROUND: Since the 5th edition of BI-RADS was released, prior studies have compared BI-RADS and quantitative fully automated volumetric assessment, but with software packages that were not recalibrated according to the 5th edition. PURPOSE: To investigate mammographic density assessment of automated volumetric measurements recalibrated according to the BI-RADS 5th edition compared with visual assessment. MATERIAL AND METHODS: A total of 4000 full-field digital mammographic examinations were reviewed by three radiologists for the BI-RADS 5th edition density category by consensus after individual assessments. Volumetric density data obtained using Quantra and Volpara software were collected. The comparison of visual and volumetric density assessments was performed in total and according to the presence of cancer. RESULTS: Among 4000 examinations, 129 were mammograms of breast cancer. Compared to visual assessment, volumetric measurements showed higher category B (40.6% vs. 19.8%) in Quantra, and higher category D (40.4% vs. 14.7%) and lower category A (0.2% vs. 5.0%) in Volpara (P < 0.0001). All volumetric data showed a difference according to visually assessed categories and were correlated between the two volumetric measurements (P < 0.0001). The group with cancer showed a lower proportion of fatty breast than that without cancer: 17.8% vs. 46.9% for Quantra (P < 0.0001) and 9.3% vs. 21.5% for Volpara (P = 0.003). Both measurements showed significantly higher mean density data in the group with cancer than without cancer (P < 0.005 for all). CONCLUSION: Automated volumetric measurements adapted for the BI-RADS 5th edition showed different but correlated results with visual assessment and each other. Recalibration of volumetric measurement has not completely reflected the visual assessment.

Affinity Maturation of a T-Cell Receptor-Like Antibody Specific for a Cytomegalovirus pp65-Derived Peptide Presented by HLA-A*02:01.

Human cytomegalovirus (CMV) infection is widespread among adults (60-90%) and is usually undetected in healthy individuals without symptoms but can cause severe diseases in immunocompromised hosts. T-cell receptor (TCR)-like antibodies (Abs), which recognize complex antigens (peptide-MHC complex, pMHC) composed of MHC molecules with embedded short peptides derived from intracellular proteins, including pathogenic viral proteins, can serve as diagnostic and/or therapeutic agents. In this study, we aimed to engineer a TCR-like Ab specific for pMHC comprising a CMV pp65 protein-derived peptide (495NLVPMVATV503; hereafter, CMVpp65495-503) in complex with MHC-I molecule human leukocyte antigen (HLA)-A*02:01 (CMVpp65495-503/HLA-A*02:01) to increase affinity by sequential mutagenesis of complementarity-determining regions using yeast surface display technology. Compared with the parental Ab, the final generated Ab (C1-17) showed ~67-fold enhanced binding affinity (KD ≈ 5.2 nM) for the soluble pMHC, thereby detecting the cell surface-displayed CMVpp65495-503/HLA-A*02:01 complex with high sensitivity and exquisite specificity. Thus, the new high-affinity TCR-like Ab may be used for the detection and treatment of CMV infection.

Active Targeted Surveillance to Identify Sites of Emergence of Hantavirus.

BACKGROUND: Endemic outbreaks of hantaviruses pose a critical public health threat worldwide. Hantaan orthohantavirus (HTNV) causes hemorrhagic fever with renal syndrome (HFRS) in humans. Using comparative genomic analyses of partial and nearly complete sequences of HTNV from humans and rodents, we were able to localize, with limitations, the putative infection locations for HFRS patients. Partial sequences might not reflect precise phylogenetic positions over the whole-genome sequences; finer granularity of rodent sampling reflects more precisely the circulation of strains. METHODS: Five HFRS specimens were collected. Epidemiological surveys were conducted with the patients during hospitalization. We conducted active surveillance at suspected HFRS outbreak areas. We performed multiplex polymerase chain reaction-based next-generation sequencing to obtain the genomic sequence of HTNV from patients and rodents. The phylogeny of human- and rodent-derived HTNV was generated using the maximum likelihood method. For phylogeographic analyses, the tracing of HTNV genomes from HFRS patients was defined on the bases of epidemiological interviews, phylogenetic patterns of the viruses, and geographic locations of HTNV-positive rodents. RESULTS: The phylogeographic analyses demonstrated genetic clusters of HTNV strains from clinical specimens, with HTNV circulating in rodents at suspected sites of patient infections. CONCLUSIONS: This study demonstrates a major shift in molecular epidemiological surveillance of HTNV. Active targeted surveillance was performed at sites of suspected infections, allowing the high-resolution phylogeographic analysis to reveal the site of emergence of HTNV. We posit that this novel approach will make it possible to identify infectious sources, perform disease risk assessment, and implement preparedness against vector-borne viruses.

Texture Analysis with 3.0-T MRI for Association of Response to Neoadjuvant Chemotherapy in Breast Cancer.

Background Previous studies have suggested that texture analysis is a promising tool in the diagnosis, characterization, and assessment of treatment response in various cancer types. Therefore, application of texture analysis may be helpful for early prediction of pathologic response in breast cancer. Purpose To investigate whether texture analysis of features from MRI is associated with pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer. Materials and Methods This retrospective study included 136 women (mean age, 47.9 years; range, 31-70 years) who underwent NAC and subsequent surgery for breast cancer between January 2012 and August 2017. Patients were monitored with 3.0-T MRI before (pretreatment) and after (midtreatment) three or four cycles of NAC. Texture analysis was performed at pre- and midtreatment T2-weighted MRI, contrast material-enhanced T1-weighted MRI, diffusion-weighted MRI, and apparent diffusion coefficient (ADC) mapping by using commercial software. A random forest method was applied to build a predictive model for classifying those with pCR with use of texture parameters. Diagnostic performance for predicting pCR was assessed and compared with that of six other machine learning classifiers (adaptive boosting, decision tree, k-nearest neighbor, linear support vector machine, naive Bayes, and linear discriminant analysis) by using the Wald test and DeLong method. Results Forty of the 136 patients (29%) achieved pCR after NAC. In the prediction of pCR, the random forest classifier showed the lowest diagnostic performance with pretreatment ADC (area under the receiver operating characteristic curve [AUC], 0.53; 95% confidence interval: 0.44, 0.61) and the highest diagnostic performance with midtreatment contrast-enhanced T1-weighted MRI (AUC, 0.82; 95% confidence interval: 0.74, 0.88) among pre- and midtreatment T2-weighted MRI, contrast-enhanced T1-weighted MRI, diffusion-weighted MRI, and ADC mapping. Conclusion Texture parameters using a random forest method of contrast-enhanced T1-weighted MRI at midtreatment of neoadjuvant chemotherapy were valuable and associated with pathologic complete response in breast cancer. © RSNA, 2019 Online supplemental material is available for this article.

Kisspeptin Neuron-Specific and Self-Sustained Calcium Oscillation in the Hypothalamic Arcuate Nucleus of Neonatal Mice: Regulatory Factors of its Synchronization.

INTRODUCTION: Synchronous and pulsatile neural activation of kisspeptin neurons in the arcuate nucleus (ARN) are important components of the gonadotropin-releasing hormone pulse generator, the final common pathway for central regulation of mammalian reproduction. However, whether ARN kisspeptin neurons can intrinsically generate self-sustained synchronous oscillations from the early neonatal period and how they are regulated remain unclear. OBJECTIVE: This study aimed to examine the endogenous rhythmicity of ARN kisspeptin neurons and its neural regulation using a neonatal organotypic slice culture model. METHODS: We monitored calcium (Ca2+) dynamics in real-time from individual ARN kisspeptin neurons in neonatal organotypic explant cultures of Kiss1-IRES-Cre mice transduced with genetically encoded Ca2+ indicators. Pharmacological approaches were employed to determine the regulations of kisspeptin neuron-specific Ca2+ oscillations. A chemogenetic approach was utilized to assess the contribution of ARN kisspeptin neurons to the population dynamics. RESULTS: ARN kisspeptin neurons in neonatal organotypic cultures exhibited a robust synchronized Ca2+ oscillation with a period of approximately 3 min. Kisspeptin neuron-specific Ca2+ oscillations were dependent on voltage-gated sodium channels and regulated by endoplasmic reticulum-dependent Ca2+ homeostasis. Chemogenetic inhibition of kisspeptin neurons abolished synchronous Ca2+ oscillations, but the autocrine actions of the neuropeptides were marginally effective. Finally, neonatal ARN kisspeptin neurons were regulated by N-methyl-D-aspartate and gamma-aminobutyric acid receptor-mediated neurotransmission. CONCLUSION: These data demonstrate that ARN kisspeptin neurons in organotypic cultures can generate synchronized and self-sustained Ca2+ oscillations. These oscillations controlled by multiple regulators within the ARN are a novel ultradian rhythm generator that is active during the early neonatal period.

Prediction of axillary response by monitoring with ultrasound and MRI during and after neoadjuvant chemotherapy in breast cancer patients.

PURPOSE: To investigate whether monitoring with ultrasound and MR imaging before, during and after neoadjuvant chemotherapy (NAC) can predict axillary response in breast cancer patients. MATERIALS AND METHODS: A total of 131 breast cancer patients with clinically positive axillary lymph node (LN) who underwent NAC and subsequent surgery were enrolled. They had ultrasound and 3.0 T-MR examinations before, during and after NAC. After reviewing ultrasound and MR images, axillary LN features and tumour size (T size) were noted. According to LN status after surgery, imaging features and their diagnostic performances were analysed. RESULTS: Of the 131 patients, 60 (45.8%) had positive LNs after surgery. Pre-NAC T size at ultrasound and MR was different in positive LN status after surgery (p < 0.01). There were significant differences in mid- and post-NAC number, cortical thickness (CxT), T size and T size reduction at ultrasound and mid- and post-NAC CxT, hilum, T size and T size reduction, and post-NAC ratio of diameter at MR (p < 0.03). On multivariate analysis, pre-NAC MR T size (OR, 1.03), mid-NAC ultrasound T size (OR, 1.05) and CxT (OR, 1.53), and post-NAC MR T size (OR, 1.06) and CxT (OR, 1.64) were independently associated with positive LN (p < 0.004). Combined mid-NAC ultrasound T size and CxT showed the best diagnostic performance with AUC of 0.760. CONCLUSION: Monitoring ultrasound and MR axillary LNs and T size can be useful to predict axillary response to NAC in breast cancer patients. KEY POINTS: • Monitoring morphologic features of LNs is useful to predict axillary response. • Monitoring tumour size by imaging is useful to predict axillary response. • The axillary ultrasound during NAC showed the highest diagnostic performance.

Discovery of novel heat shock protein (Hsp90) inhibitors based on luminespib with potent antitumor activity.

A series of isosteric surrogates of the 4-phenyl group in luminespib were investigated as new scaffolds of the Hsp90 inhibitor for the discovery of novel antitumor agents. Among the synthesized surrogates of isoxazole and pyrazole, compounds 4a, 5e and 12b exhibited potent Hsp90 inhibition in ATPase activity and Her2 degradation assays and significant antitumor activity in A2780 and HCT116 cell lines. Animal studies indicated that compared to luminespib, their activities were superior in A2780 or NCI-H1975 tumor xenograft models. A molecular modeling study demonstrated that compound 4a could fit nicely into the N-terminal ATP binding pocket.

Grayscale Ultrasound Radiomic Features and Shear-Wave Elastography Radiomic Features in Benign and Malignant Breast Masses.

PURPOSE: To identify and compare diagnostic performance of radiomic features between grayscale ultrasound (US) and shear-wave elastography (SWE) in breast masses. MATERIALS AND METHODS: We retrospectively collected 328 pathologically confirmed breast masses in 296 women who underwent grayscale US and SWE before biopsy or surgery. A representative SWE image of the mass displayed with a grayscale image in split-screen mode was selected. An ROI was delineated around the mass boundary on the grayscale image and copied and pasted to the SWE image by a dedicated breast radiologist for lesion segmentation. A total of 730 candidate radiomic features including first-order statistics and textural and wavelet features were extracted from each image. LASSO regression was used for data dimension reduction and feature selection. Univariate and multivariate logistic regression was performed to identify independent radiomic features, differentiating between benign and malignant masses with calculation of the AUC. RESULTS: Of 328 breast masses, 205 (62.5 %) were benign and 123 (37.5 %) were malignant. Following radiomic feature selection, 22 features from grayscale and 6 features from SWE remained. On univariate analysis, all 6 SWE radiomic features (P < 0.0001) and 21 of 22 grayscale radiomic features (P < 0.03) were significantly different between benign and malignant masses. After multivariate analysis, three grayscale radiomic features and two SWE radiomic features were independently associated with malignant breast masses. The AUC was 0.929 for grayscale US and 0.992 for SWE (P < 0.001). CONCLUSION: US radiomic features may have the potential to improve diagnostic performance for breast masses, but further investigation of independent and larger datasets is needed.

DRG2 Deficient Mice Exhibit Impaired Motor Behaviors with Reduced Striatal Dopamine Release.

Developmentally regulated GTP-binding protein 2 (DRG2) was first identified in the central nervous system of mice. However, the physiological function of DRG2 in the brain remains largely unknown. Here, we demonstrated that knocking out DRG2 impairs the function of dopamine neurons in mice. DRG2 was strongly expressed in the neurons of the dopaminergic system such as those in the striatum (Str), ventral tegmental area (VTA), and substantia nigra (SN), and on neuronal cell bodies in high-density regions such as the hippocampus (HIP), cerebellum, and cerebral cortex in the mouse brain. DRG2 knockout (KO) mice displayed defects in motor function in motor coordination and rotarod tests and increased anxiety. However, unexpectedly, DRG2 depletion did not affect the dopamine (DA) neuron population in the SN, Str, or VTA region or dopamine synthesis in the Str region. We further demonstrated that dopamine release was significantly diminished in the Str region of DRG2 KO mice and that treatment of DRG2 KO mice with l-3,4-dihydroxyphenylalanine (L-DOPA), a dopamine precursor, rescued the behavioral motor deficiency in DRG2 KO mice as observed with the rotarod test. This is the first report to identify DRG2 as a key regulator of dopamine release from dopamine neurons in the mouse brain.

Multiplex PCR-Based Next-Generation Sequencing and Global Diversity of Seoul Virus in Humans and Rats.

Seoul virus (SEOV) poses a worldwide public health threat. This virus, which is harbored by Rattus norvegicus and R. rattus rats, is the causative agent of hemorrhagic fever with renal syndrome (HFRS) in humans, which has been reported in Asia, Europe, the Americas, and Africa. Defining SEOV genome sequences plays a critical role in development of preventive and therapeutic strategies against the unique worldwide hantavirus. We applied multiplex PCR-based next-generation sequencing to obtain SEOV genome sequences from clinical and reservoir host specimens. Epidemiologic surveillance of R. norvegicus rats in South Korea during 2000-2016 demonstrated that the serologic prevalence of enzootic SEOV infections was not significant on the basis of sex, weight (age), and season. Viral loads of SEOV in rats showed wide dissemination in tissues and dynamic circulation among populations. Phylogenetic analyses showed the global diversity of SEOV and possible genomic configuration of genetic exchanges.