Holistic Multi-View Building Analysis in the Wild with Projection Pooling

We address six different classification tasks related to fine-grained building attributes: construction type, number of floors, pitch and geometry of the roof, facade material, and occupancy class. Tackling such a remote building analysis problem became possible only recently due to growing large-scale datasets of urban scenes. To this end, we introduce a new benchmarking dataset, consisting of 49426 images (top-view and street-view) of 9674 buildings. These photos are further assembled, together with the geometric metadata. The dataset showcases various real-world challenges, such as occlusions, blur, partially visible objects, and a broad spectrum of buildings. We propose a new projection pooling layer, creating a unified, top-view representation of the top-view and the side views in a high-dimensional space. It allows us to utilize the building and imagery metadata seamlessly. Introducing this layer improves classification accuracy -- compared to highly tuned baseline models -- indicating its suitability for building analysis.Comment: Accepted for publication at the 35th AAAI Conference on Artificial Intelligence (AAAI 2021

Research Staff COVID-19 Pandemic Survey-Results from the Prevention and Early Treatment of Acute Lung Injury (PETAL) Network

Objectives: There is a lack of knowledge about the challenges of researchers who continued in-person research during the early phases of the COVID-19 pandemic. Design: Electronic survey assessing work-related exposure to COVID-19, logistical challenges, and procedural changes during the first year of the COVID-19 pandemic on clinical research. Setting: National Heart, Lung, and Blood Institute-sponsored Prevention and Early Treatment of Acute Lung Injury Clinical Trial Network Centers. Subjects: Research staff at research Network Sites. Measurements and Main Results: The 37-question survey was completed by 277 individuals from 24 states between 29 September 2020, and 12 December 2020, yielding a response rate of 37.7%. Most respondents (91.5%) indicated that non-COVID-19 research was affected by COVID-19 research studies. In response to the COVID-19 pandemic, 20% of respondents were reassigned to different roles at their institution. Many survey takers were exposed to COVID-19 (56%), with more than 50% of researchers requiring a COVID-19 test and 8% testing positive. The fear of infection was 2.7-times higher compared to pre-COVID-19 times. Shortages of personal protective equipment were encountered by 34% of respondents, primarily due to lack of access to N95 masks, followed by gowns and protective eyewear. Personal protective equipment reallocation from research to clinical use was reported by 31% of respondents. Most of the respondents (88.5%), despite these logistical challenges, indicated their willingness to enroll COVID-19 patients. Conclusions: During the first year of the COVID-19 pandemic, members of the research network were engaged in COVID-19 research despite logistical challenges, limited access to personal protective equipment, and fear of exposure. The research network’s survey experience can inform ongoing policy discussions to create research enterprises that can dexterously refocus research to address the knowledge gaps associated with novel public health emergencies while mitigating the effect of pandemics on existing research projects and research personnel

C-MCG: Synthesis, Uptake Selectivity, and Primate PET of a Probe for Glutamate Carboxypeptidase II (NAALADase)

Imaging of glutamate carboxypeptidase II (GCP II), also known as N -acetylated α-linked l -amino dipeptidase (NAALADase), may enable study of glutamatergic transmission, prostate cancer, and tumor neovasculature in vivo. Our goal was to develop a probe for GCP II for use with positron emission tomography (PET). Radiosynthesis of 11 C–MeCys–C(O)–Glu or 11 C-( S )-2-[3-(( R )-1-carboxy-2-methylsulfanyl-ethyl)-ureido]-pentanedioic acid ( 11 C-MCG), an asymmetric urea and potent ( K i = 1.9 nM) inhibitor of GCP II, was performed by C-11 methylation of the free thiol. Biodistribution of 11 C-MCG was assayed in mice, and quantitative PET was performed in a baboon. 11 C-MCG was obtained in 16% radiochemical yield at the end of synthesis with specific radioactivities over 167 GBq/mmol (4000 Ci/mmol) within 30 min after the end of bombardment. At 30 min postinjection, 11 C-MCG showed 33.0 ± 5.1%, 0.4 ± 0.1%, and 1.1 ± 0.2% ID/g in mouse kidney (target tissue), muscle, and blood, respectively. Little radioactivity gained access to the brain. Blockade with unlabeled MCG or 2-(phosphonomethyl)pentanedioic acid (PMPA), another potent inhibitor of GCP II, provided sevenfold and threefold reductions, respectively, in binding to target tissue. For PET, distribution volumes (DVs) were 1.38 then 0.87 pre- and postblocker (PMPA). Little metabolism of 11 C-MCG occurred in the mouse or baboon. These results suggest that 11 C-MCG may be useful for imaging GCP II in the periphery

Evaluation of Protein Kinase Inhibitors with PLK4 Cross-Over Potential in a Pre-Clinical Model of Cancer

Polo-like kinase 4 (PLK4) is a cell cycle-regulated protein kinase (PK) recruited at the centrosome in dividing cells. Its overexpression triggers centrosome amplification, which is associated with genetic instability and carcinogenesis. In previous work, we established that PLK4 is overexpressed in pediatric embryonal brain tumors (EBT). We also demonstrated that PLK4 inhibition exerted a cytostatic effect in EBT cells. Here, we examined an array of PK inhibitors (CFI-400945, CFI-400437, centrinone, centrinone-B, R-1530, axitinib, KW-2449, and alisertib) for their potential crossover to PLK4 by comparative structural docking and activity inhibition in multiple established embryonal tumor cell lines (MON, BT-12, BT-16, DAOY, D283). Our analyses demonstrated that: (1) CFI-400437 had the greatest impact overall, but similar to CFI-400945, it is not optimal for brain exposure. Also, their phenotypic anti-cancer impact may, in part, be a consequence of the inhibition of Aurora kinases (AURKs). (2) Centrinone and centrinone B are the most selective PLK4 inhibitors but they are the least likely to penetrate the brain. (3) KW-2449, R-1530 and axitinib are the ones predicted to have moderate-to-good brain penetration. In conclusion, a new selective PLK4 inhibitor with favorable physiochemical properties for optimal brain exposure can be beneficial for the treatment of EBT