We present Imagen, a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding. Imagen builds on the power of large transformer language models in understanding text and hinges on the strength of diffusion models in high-fidelity image generation. Our key discovery is that generic large language models (e.g. T5), pretrained on text-only corpora, are surprisingly effective at encoding text for image synthesis: increasing the size of the language model in Imagen boosts both sample fidelity and imagetext alignment much more than increasing the size of the image diffusion model. Imagen achieves a new state-of-the-art FID score of 7.27 on the COCO dataset, without ever training on COCO, and human raters find Imagen samples to be on par with the COCO data itself in image-text alignment. To assess text-to-image models in greater depth, we introduce DrawBench, a comprehensive and challenging benchmark for text-to-image models. With DrawBench, we compare Imagen with recent methods including VQ-GAN+CLIP, Latent Diffusion Models, GLIDE and DALL-E 2, and find that human raters prefer Imagen over other models in side-byside comparisons, both in terms of sample quality and image-text alignment. See imagen.research.google for an overview of the results. * Equal contribution. † Core contribution.

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Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial results. Our model is a natural extension of the standard image diffusion architecture, and it enables jointly training from image and video data, which we find to reduce the variance of minibatch gradients and speed up optimization. To generate long and higher resolution videos we introduce a new conditional sampling technique for spatial and temporal video extension that performs better than previously proposed methods. We present the first results on a large text-conditioned video generation task, as well as state-of-the-art results on an established unconditional video generation benchmark. Supplementary material is available at https://video-diffusion.github.io/.

BackgroundEarly diagnosis and knowledge of infarct size is critical for the management of acute myocardial infarction (MI). We evaluated whether early elevated plasma level of macrophage migration inhibitory factor (MIF) is useful for these purposes in patients with ST‐elevation MI (STEMI).Methods and ResultsWe first studied MIF level in plasma and the myocardium in mice and determined infarct size. MI for 15 or 60 minutes resulted in 2.5‐fold increase over control values in plasma MIF levels while MIF content in the ischemic myocardium reduced by 50% and plasma MIF levels correlated with myocardium‐at‐risk and infarct size at both time‐points (P<0.01). In patients with STEMI, we obtained admission plasma samples and measured MIF, conventional troponins (TnI, TnT), high sensitive TnI (hsTnI), creatine kinase (CK), CK‐MB, and myoglobin. Infarct size was assessed by cardiac magnetic resonance (CMR) imaging. Patients with chronic stable angina and healthy volunteers were studied as controls. Of 374 STEMI patients, 68% had elevated admission MIF levels above the highest value in healthy controls (>41.6 ng/mL), a proportion similar to hsTnI (75%) and TnI (50%), but greater than other biomarkers studied (20% to 31%, all P<0.05 versus MIF). Only admission MIF levels correlated with CMR‐derived infarct size, ventricular volumes and ejection fraction (n=42, r=0.46 to 0.77, all P<0.01) at 3 day and 3 months post‐MI.ConclusionPlasma MIF levels are elevated in a high proportion of STEMI patients at the first obtainable sample and these levels are predictive of final infarct size and the extent of cardiac remodeling.

1. Since important interrelationships between haemodynamic and hormone indices are possible in cardiac failure, measurements of cardiac output, mean pulmonary artery pressure, plasma renin activity, angiotensin II and aldosterone were carried out before and during acute and chronic frusemide therapy in patients with oedematous heart failure who had been given digoxin. 2. Cardiac output fell significantly 90 min after acute frusemide infection, then returned to baseline. Mean pulmonary artery pressure declined steadily throughout the 4 h of observation. 3. These haemodynamic changes occurred in the absence of major hormonal fluctuations and related presumably to direct vascular and diuretic actions of frusemide. 4. With more chronic (8-10 days) oral frusemide therapy, reciprocal changes between haemodynamic and hormone indices were observed. As the diuretic response to frusemide diminished, cardiac output and pulmonary artery pressure declined whereas the renin-angiotensin system was activated. Statistically significant inverse correlations were observed between these haemodynamic and hormone indices. 5. In both acute and chronic phases of the study, fluctuations in aldosterone levels were regulated by the renin-angiotensin system whereas ACTH, plasma potassium and plasma sodium played, at best, supportive roles.