Predicting Clinician Fixations on Glaucoma OCT Reports via CNN-Based Saliency Prediction Methods.

To predict physician fixations specifically on ophthalmology optical coherence tomography (OCT) reports from eye tracking data using CNN based saliency prediction methods in order to aid in the education of ophthalmologists and ophthalmologists-in-training. Fifteen ophthalmologists were recruited to each examine 20 randomly selected OCT reports and evaluate the likelihood of glaucoma for each report on a scale of 0-100. Eye movements were collected using a Pupil Labs Core eye-tracker.

DR5 disulfide bonding as a sensor and effector of protein folding stress.

New agents are needed that selectively kill cancer cells without harming normal tissues. The TRAIL ligand and its receptors, DR5 and DR4, exhibit cancer-selective toxicity, but TRAIL analogs or agonistic antibodies targeting these receptors have not received FDA approval for cancer therapy. Small molecules for activating DR5 or DR4 independently of protein ligands may bypass some of the pharmacological limitations of these protein drugs.

Deep Learning Enables Reduced Gadolinium Dose for Contrast-Enhanced Blood-Brain Barrier Opening.

Focused ultrasound (FUS) can be used to open the blood-brain barrier (BBB), and MRI with contrast agents can detect that opening. However, repeated use of gadolinium-based contrast agents (GBCAs) presents safety concerns to patients. This study is the first to propose the idea of modeling a volume transfer constant (Ktrans) through deep learning to reduce the dosage of contrast agents.

Addressing COVID-19 Vaccine Hesitancy: The Role of Medical Students.

Unlabelled: We conducted a survey study at the Icahn School of Medicine at Mount Sinai to assess COVID-19 vaccine attitudes and behaviors among medical students. Almost all respondents (96.5%,  = 222) believed vaccines were effective and reported being asked about the COVID-19 vaccine by family members (79.

Segmentation with Residual Attention U-Net and an Edge-Enhancement Approach Preserves Cell Shape Features.

The ability to extrapolate gene expression dynamics in living single cells requires robust cell segmentation, and one of the challenges is the amorphous or irregularly shaped cell boundaries. To address this issue, we modified the U-Net architecture to segment cells in fluorescence widefield microscopy images and quantitatively evaluated its performance. We also proposed a novel loss function approach that emphasizes the segmentation accuracy on cell boundaries and encourages shape feature preservation.