Undergraduate students participating in the UCLA Undergraduate Research Consortium for Functional Genomics (URCFG) have conducted a two-phased screen using RNA interference (RNAi) in combination with fluorescent reporter proteins to identify genes important for hematopoiesis in Drosophila. This screen disrupted the function of approximately 3500 genes and identified 137 candidate genes for which loss of function leads to observable changes in the hematopoietic development. Targeting RNAi to maturing, progenitor, and regulatory cell types identified key subsets that either limit or promote blood cell maturation. Bioinformatic analysis reveals gene enrichment in several previously uncharacterized areas, including RNA processing and export and vesicular trafficking. Lastly, the participation of students in this course-based undergraduate research experience (CURE) correlated with increased learning gains across several areas, as well as increased STEM retention, indicating that authentic, student-driven research in the form of a CURE represents an impactful and enriching pedagogical approach.
Purpose of Review Triple-negative breast cancer (TNBC) represents about 15–20% of all breast cancers and often presents as an aggressive cancer with poor prognosis compared to other forms of breast cancer. This article will review the clinical manifestations, imaging features, pathology correlation, treatment and management, and prognosis of TNBC. Recent Findings While mammography and ultrasound can be used to diagnose TNBC, MRI is the most accurate and sensitive modality to detect TNBC at nearly 100% sensitivity. Contrast-enhanced breast MRI is the optimal imaging study for assessing response to neoadjuvant chemotherapy and can be used to tailor systemic therapy. Summary Understanding the imaging appearance of TNBC is imperative to diagnose TNBC accurately and to help guide management.
Background Accurate estimation of ischemic core on baseline imaging has treatment implications in patients with acute ischemic stroke (AIS). Machine learning (ML) algorithms have shown promising results in estimating ischemic core using routine noncontrast computed tomography (NCCT). Objective We used an ML-trained algorithm to quantify ischemic core volume on NCCT in a comparative analysis to pretreatment magnetic resonance imaging (MRI) diffusion-weighted imaging (DWI) in patients with AIS. Methods Patients with AIS who had both pretreatment NCCT and MRI were enrolled. An automatic segmentation ML approach was applied using Brainomix software (Oxford, UK) to segment the ischemic voxels and calculate ischemic core volume on NCCT. Ischemic core volume was also calculated on baseline MRI DWI. Comparative analysis was performed using Bland–Altman plots and Pearson correlation. Results A total of 72 patients were included. The time-to-stroke onset time was 134.2/89.5 minutes (mean/median). The time difference between NCCT and MRI was 64.8/44.5 minutes (mean/median). In patients who presented within 1 hour from stroke onset, the ischemic core volumes were significantly (p = 0.005) underestimated by ML-NCCT. In patients presented beyond 1 hour, the ML-NCCT estimated ischemic core volumes approximated those obtained by MRI-DWI and with significant correlation ( r = 0.56, p < 0.001). Conclusion The ischemic core volumes calculated by the described ML approach on NCCT approximate those obtained by MRI in patients with AIS who present beyond 1 hour from stroke onset.
Collateral status has prognostic and treatment implications in acute ischemic stroke (AIS) patients. Unlike CTA, grading collaterals on MRA is not well studied. We aimed to evaluate the accuracy of assessing collaterals on pretreatment MRA in AIS patients against DSA. AIS patients with anterior circulation proximal arterial occlusion with baseline MRA and subsequent endovascular treatment were included. MRA collaterals were evaluated by two neuroradiologists independently using the Tan and Maas scoring systems. DSA collaterals were evaluated by using the American Society of Interventional and Therapeutic Neuroradiology grading system and were used as the reference for comparative analysis against MRA. A total of 104 patients met the inclusion criteria (59 female, age (mean ± SD): 70.8 ± 18.1). The inter-rater agreement (k) for collateral scoring was 0.49, 95% CI 0.37–0.61 for the Tan score and 0.44, 95% CI 0.26–0.62 for the Maas score. Total number (%) of sufficient vs. insufficient collaterals based on DSA was 49 (47%) and 55 (53%) respectively. Using the Tan score, 45% of patients with sufficient collaterals and 64% with insufficient collaterals were correctly identified in comparison to DSA, resulting in a poor agreement (0.09, 95% CI 0.1–0.28). Using the Maas score, only 4% of patients with sufficient collaterals and 93% with insufficient collaterals were correctly identified against DSA, resulting in poor agreement (0.03, 95% CI 0.06–0.13). Pretreatment MRA in AIS patients has limited concordance with DSA when grading collaterals using the Tan and Maas scoring systems.
Background Fistulas are an abnormal connection between two or more epithelial surfaces. When fistulization between adjacent structures occurs in the pelvis, there is almost invariably significant associated morbidity and impact on a patient’s quality of life. Imaging may aid in the diagnosis of pelvic fistulas and is essential to identify any associated pathology, define the course of the fistula, and aid in pre-surgical planning. Purpose This article aims to review the wide array of clinical and imaging presentations of fistulas in the pelvis, with a focus on the radiologists’ role in managing this challenging entity. Methods This article will review each classification type of fistula. Results Pelvic fistula is a devastating condition that causes significant morbidity and evaluation can be challenging. Conclusions Imaging, and particularly MRI, plays a vital role in the diagnosis, characterizing the course of a fistula and demonstrating associated complications, which are essential to guide treatment decisions.
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