The implementation of clinical-decision support algorithms for medical imaging faces challenges with reliability and interpretability. Here, we establish a diagnostic tool based on a deep-learning framework for the screening of patients with common treatable blinding retinal diseases. Our framework utilizes transfer learning, which trains a neural network with a fraction of the data of conventional approaches. Applying this approach to a dataset of optical coherence tomography images, we demonstrate performance comparable to that of human experts in classifying age-related macular degeneration and diabetic macular edema. We also provide a more transparent and interpretable diagnosis by highlighting the regions recognized by the neural network. We further demonstrate the general applicability of our AI system for diagnosis of pediatric pneumonia using chest X-ray images. This tool may ultimately aid in expediting the diagnosis and referral of these treatable conditions, thereby facilitating earlier treatment, resulting in improved clinical outcomes. VIDEO ABSTRACT.

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Because environmentally degrading inorganic fertilizer use underlies current worldwide cereal yields, future agricultural sustainability demands enhanced nitrogen use efficiency. We found that genome-wide promotion of histone H3 lysine 27 trimethylation (H3K27me3) enables nitrogen-induced stimulation of rice tillering: APETALA2-domain transcription factor NGR5 (NITROGEN-MEDIATED TILLER GROWTH RESPONSE 5) facilitates nitrogen-dependent recruitment of polycomb repressive complex 2 to repress branching-inhibitory genes via H3K27me3 modification. NGR5 is a target of gibberellin receptor GIBBERELLIN INSENSITIVE DWARF1 (GID1)–promoted proteasomal destruction. DELLA proteins (characterized by the presence of a conserved aspartate-glutamate-leucine-leucine-alanine motif) competitively inhibit the GID1-NGR5 interaction and explain increased tillering of green revolution varieties. Increased NGR5 activity consequently uncouples tillering from nitrogen regulation, boosting rice yield at low nitrogen fertilization levels. NGR5 thus enables enhanced nitrogen use efficiency for improved future agricultural sustainability and food security.