Double-stranded RNA orbivirus disrupts the DNA-sensing cGAS-sting axis to prevent type I IFN induction.

Cyclic GMP-AMP synthase (cGAS) is a DNA sensing cellular receptor that induces IFN-I transcription in response to pathogen and host derived cytosolic DNA and can limit the replication of some RNA viruses. Some viruses have nonetheless evolved mechanisms to antagonize cGAS sensing. In this study, we evaluated the interaction between Bluetongue virus (BTV), the prototypical dsRNA virus of the Orbivirus genus and the Sedoreoviridae family, and cGAS.

Bluetongue virus serotype 12 in sheep and cattle in the Netherlands in 2024 - A BTV serotype reported in Europe for the first time.

Bluetongue (BT) is a viral vector borne disease primarily affecting ruminants such as sheep, cattle, and goats. On 3 September 2023, the Netherlands reported the first case of bluetongue virus serotype 3 (BTV-3/NET2023)), after being BTV free for eleven years. Vaccination with inactivated BT vaccines for serotype 3 has been applied in the Netherlands since May 2024.

Modulation of Biomaterial-Associated Fibrosis by Means of Combined Physicochemical Material Properties.

Biomaterial-associated fibrosis remains a significant challenge in medical implants. To optimize implant design, understanding the interplay between biomaterials and host cells during the foreign body response (FBR) is crucial. Material properties are known to influence cellular behavior and can be used to manipulate cell responses, but predicting the right combination for the desired outcomes is challenging.

Diamond Surfaces with Lateral Gradients for Systematic Optimization of Surface Chemistry for Relaxometry - a Low-Pressure Plasma-Based Approach.

Diamond is increasingly popular because of its unique material properties. Diamond defects called nitrogen vacancy (NV) centers allow for measurements with unprecedented sensitivity. However, to achieve ideal sensing performance, NV centers need to be within nanometers from the surface and are thus strongly dependent on the local surface chemistry.

Large language models predict human sensory judgments across six modalities.

Determining the extent to which the perceptual world can be recovered from language is a longstanding problem in philosophy and cognitive science. We show that state-of-the-art large language models can unlock new insights into this problem by providing a lower bound on the amount of perceptual information that can be extracted from language. Specifically, we elicit pairwise similarity judgments from GPT models across six psychophysical datasets.