Speaking out for speakers: a guide for and analysis of robot speaker design.

Despite sound being a promising modality of communication in robotics (possessing, for example, the ability to improve people's perceptions of robots and help localize robotic systems in space), its facilitator, speakers, are a seldom-explored topic of study in robotics literature. To address this gap, we conducted three explorations into physical speaker design that identified what current robot speakers lack and potential remedies, low-level design improvements, and hardware additions. Further, we detail and explore the application of speakers on three different robotic platforms (including one industrial robot used for construction), the last evaluation of which involved an empirical study that sought to better understand the implications associated with poor-quality speakers in a mock service robotics context.

Deep learning-based image quality assessment: impact on detection accuracy of prostate cancer extraprostatic extension on MRI.

Objective: To assess impact of image quality on prostate cancer extraprostatic extension (EPE) detection on MRI using a deep learning-based AI algorithm.

Materials And Methods: This retrospective, single institution study included patients who were imaged with mpMRI and subsequently underwent radical prostatectomy from June 2007 to August 2022. One genitourinary radiologist prospectively evaluated each patient using the NCI EPE grading system.

Evaluation of a Cascaded Deep Learning-based Algorithm for Prostate Lesion Detection at Biparametric MRI.

Background Multiparametric MRI (mpMRI) improves prostate cancer (PCa) detection compared with systematic biopsy, but its interpretation is prone to interreader variation, which results in performance inconsistency. Artificial intelligence (AI) models can assist in mpMRI interpretation, but large training data sets and extensive model testing are required. Purpose To evaluate a biparametric MRI AI algorithm for intraprostatic lesion detection and segmentation and to compare its performance with radiologist readings and biopsy results.

Managing Catecholamine Release Syndrome During and Following Lu-177-DOTATATE in High-Risk Pheochromocytoma Patients.

Pheochromocytomas and paragangliomas (PPGLs) are rare catecholamine-producing tumors that express somatostatin receptors (SSTR) that can be treated with lutetium-177 DOTATATE (Lu-177-TRT); however, treatment can be associated with life-threatening cardiovascular events. A patient case with management strategies for high-risk PPGL patients receiving Lu-177-TRT is described. The 78-year-old patient with metastatic paraganglioma was enrolled and treated under NCT03206060.

Outcome of Seatbelt Education and Safety Program Among Teenagers.

Despite the effectiveness of seatbelts, concerns persist about compliance, especially among teenagers. Survey data from a local high school and registry data from a level 1 trauma center were used to observe seatbelt and motor vehicle accident trends. The survey data was analyzed to gauge student's sentiments on seatbelt education.

From such great heights: The effects of substrate height and the perception of risk on lemur locomotor mechanics.

Objectives: An accident during arboreal locomotion can lead to risky falls, but it remains unclear that the extent to which primates, as adept arborealists, change their locomotion in response to the perceived risk of moving on high supports in the tree canopy. By using more stable forms of locomotion on higher substrates, primates might avoid potentially fatal consequences.

Materials And Methods: Using high-speed cameras, we recorded the quadrupedal locomotion of four wild lemur species-Eulemur rubriventer, Eulemur rufifrons, Hapalemur aureus, and Lemur catta (N = 113 total strides).

Deep Learning-Based Detection and Classification of Bone Lesions on Staging Computed Tomography in Prostate Cancer: A Development Study.

Rationale And Objectives: Efficiently detecting and characterizing metastatic bone lesions on staging CT is crucial for prostate cancer (PCa) care. However, it demands significant expert time and additional imaging such as PET/CT. We aimed to develop an ensemble of two automated deep learning AI models for 1) bone lesion detection and segmentation and 2) benign vs.

Deep Learning-Based T2-Weighted MR Image Quality Assessment and Its Impact on Prostate Cancer Detection Rates.

Background: Image quality evaluation of prostate MRI is important for successful implementation of MRI into localized prostate cancer diagnosis.

Purpose: To examine the impact of image quality on prostate cancer detection using an in-house previously developed artificial intelligence (AI) algorithm.

Study Type: Retrospective.

Plastic pollution on the world's coral reefs.

Coral reefs are losing the capacity to sustain their biological functions. In addition to other well-known stressors, such as climatic change and overfishing, plastic pollution is an emerging threat to coral reefs, spreading throughout reef food webs, and increasing disease transmission and structural damage to reef organisms. Although recognized as a global concern, the distribution and quantity of plastics trapped in the world's coral reefs remains uncertain.

Comparison of MRI-Based Staging and Pathologic Staging for Predicting Biochemical Recurrence of Prostate Cancer After Radical Prostatectomy.

Currently most clinical models for predicting biochemical recurrence (BCR) of prostate cancer (PCa) after radical prostatectomy (RP) incorporate staging information from RP specimens, creating a gap in preoperative risk assessment. The purpose of our study was to compare the utility of presurgical staging information from MRI and postsurgical staging information from RP pathology in predicting BCR in patients with PCa. This retrospective study included 604 patients (median age, 60 years) with PCa who underwent prostate MRI before RP from June 2007 to December 2018.

Exploration of Imaging Biomarkers for Metabolically-Targeted Osteosarcoma Therapy in a Murine Xenograft Model.

Osteosarcoma (OS) is an aggressive pediatric cancer with unmet therapeutic needs. Glutaminase 1 (GLS1) inhibition, alone and in combination with metformin, disrupts the bioenergetic demands of tumor progression and metastasis, showing promise for clinical translation. Three positron emission tomography (PET) clinical imaging agents, [F]fluoro-2-deoxy-2-D-glucose ([F]FDG), 3'-[F]fluoro-3'-deoxythymidine ([F]FLT), and (2S, 4R)-4-[F]fluoroglutamine ([F]GLN), were evaluated in the MG63.

Jumping performance in tree squirrels: Insights into primate evolution.

Morphological traits suggesting powerful jumping abilities are characteristic of early crown primate fossils. Because tree squirrels lack certain 'primatelike' grasping features but frequently travel on the narrow terminal branches of trees, they make a viable extant model for an early stage of primate evolution. Here, we explore biomechanical determinants of jumping performance in the arboreal Eastern gray squirrel (Sciurus carolinensis, n = 3) as a greater understanding of the biomechanical strategies that squirrels use to modulate jumping performance could inform theories of selection for increased jumping ability during early primate evolution.

sp. nov. (Perciformes: Labridae), a New Species of Striped Hogfish from Tahiti, with Range Extensions for Two Congeners.

A new labrid fish, sp. nov., the fifth species within the genus, is herein described from two specimens collected at a depth of 140 m from a mesophotic coral ecosystem in Tahiti, French Polynesia.

Prospective Evaluation of PI-RADS Version 2.1 for Prostate Cancer Detection and Investigation of Multiparametric MRI-derived Markers.

Background Data regarding the prospective performance of Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 alone and in combination with quantitative MRI features for prostate cancer detection is limited. Purpose To assess lesion-based clinically significant prostate cancer (csPCa) rates in different PI-RADS version 2.

Assembly rules of coral reef fish communities along the depth gradient.

Coral reefs are home to some of the most studied ecological assemblages on the planet. However, differences in large-scale assembly rules have never been studied using empirical quantitative data stratified along the depth gradient of reefs. Consequently, little is known about the small- and regional-scale effects of depth on coral reef assemblages.

Automated 360-degree goniophotography with the NIDEK Gonioscope GS-1 for glaucoma.

This study was registered with ClinicalTrials.gov (ID: NCT03715231). A total of 20 participants (37 eyes) who were 18 or older and had glaucoma or were glaucoma suspects were enrolled from the NYU Langone Eye Center and Bellevue Hospital.

The Imaginative Work of Craig Gosling: A Memorial Showcase.

This JBC Memorial Showcase features the award-winning medical and zoological illustrations by AMI member Craig Gosling, who passed away on July 11, 2021. Craig was extremely active in the Association of Medical Illustrators. Craig was an AMI Past President and served on the Board of Governors.

Predicting Outcomes of Indeterminate Bone Lesions on F-DCFPyL PSMA PET/CT Scans in the Setting of High-Risk Primary or Recurrent Prostate Cancer.

Indeterminate bone lesions (IBLs) on prostate-specific membrane antigen (PSMA) PET/CT are common. This study aimed to define variables that predict whether such lesions are likely malignant or benign using features on PSMA PET/CT. F-DCFPyL PET/CT imaging was performed on 243 consecutive patients with high-risk primary or biochemically recurrent prostate cancer.

The Low Rate of Adherence to Checklist for Artificial Intelligence in Medical Imaging Criteria Among Published Prostate MRI Artificial Intelligence Algorithms.

Objective: To determine the rigor, generalizability, and reproducibility of published classification and detection artificial intelligence (AI) models for prostate cancer (PCa) on MRI using the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) guidelines, a 42-item checklist that is considered a measure of best practice for presenting and reviewing medical imaging AI research.

Materials And Methods: This review searched English literature for studies proposing PCa AI detection and classification models on MRI. Each study was evaluated with the CLAIM checklist.