A recent study highlights both the promise and limitations of the inhaled COVID-19 vaccine Ad5-XBB.1.5. Researchers found that the vaccine effectively induced strong immunoglobulin A (IgA) responses in the nasal mucosa and bloodstream, with nasal IgA showing a stronger correlation with virus-neutralizing activity than immunoglobulin G (IgG). The vaccine also boosted antigen-specific CD8⁺ T cell responses and slightly increased antibody-dependent cellular phagocytosis (ADCP). However, the study revealed that nasal IgA levels declined significantly by six months post-vaccination, and the majority of participants experienced breakthrough infections during the recent JN.1 wave. Additionally, individuals with high levels of pre-existing antibodies against adenovirus type 5 (Ad5) showed reduced neutralizing responses, indicating that vector immunity may limit the vaccine’s effectiveness. These findings underscore the challenges of achieving long-lasting mucosal immunity through current inhaled vaccine strategies. The researchers call for the development of next-generation mucosal vaccines, that can sustain strong and durable IgA responses in the nasal mucosa, offering better protection against emerging SARS-CoV-2 variants and reducing community transmission.

Cataracts are a leading cause of vision loss worldwide, and fibrosis-related complications after surgery often limit full recovery. 

New research identifies NF-kappa-B-activating protein-like (NKAPL) as a potent tumor suppressor in non-small cell lung cancer (NSCLC).

A naturally occurring metabolic compound, pyruvate, has been identified as a potent suppressor of inflammation in ulcerative colitis (UC), offering a promising new strategy for treating this chronic bowel disease.

Diffusion probabilistic models (DPMs) have achieved impressive success in high-resolution image synthesis, especially in recent large-scale text-to-image generation applications. An essential technique for improving the sample quality of DPMs is guided sampling, which usually needs a large guidance scale to obtain the best sample quality. The commonly-used fast sampler for guided

sampling is denoising diffusion implicit models (DDIM), a first-order diffusion ordinary differential equation (ODE) solver that generally needs 100 to 250 steps for high-quality samples. Although recent works propose dedicated high-order solvers and achieve a further speedup for sampling without guidance, their effectiveness for guided sampling has not been well-tested before. In this work, researchers demonstrate that previous high-order fast samplers suffer from instability issues, and they even become slower than DDIM when the guidance scale grows larger. To further speed up guided sampling, researchers propose DPM-Solver++, a high-order solver for the guided sampling of DPMs. DPM-Solver++ solves the diffusion ODE with the data prediction model and adopts thresholding methods to keep the solution matches training data distribution. Researchers further propose a multistep variant of DPM-Solver++ to address the instability issue by reducing the effective step size. Experiments show that DPM-Solver++ can generate high-quality samples within only 15 to 20 steps for guided sampling by pixel-space and latent-space DPMs.