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.

A research team from Peking University and Peking University Shenzhen Graduate School have used artificial intelligence (AI) to quickly and accurately predict the properties of materials that could improve solar energy devices. Their algorithms were able to predictic important properties such as: conduction band minimum (CBM), valence band maximum (VBM), and bandgap of halide perovskites.

This work provides valuable insights into the rational design of halide perovskites with tailored properties. These findings can impulse the discovery of better-performing solar materials, paving the way for more affordable and efficient solar panels.